{ "cells": [ { "cell_type": "markdown", "id": "98c2d7c4-faad-4be2-add7-4e44784f078c", "metadata": {}, "source": [ "## Task" ] }, { "cell_type": "markdown", "id": "75cb873e-68c2-45cf-bd17-2e0a9a26a7e3", "metadata": {}, "source": [ "You are provided with registration data of 2298 mobile subscribers at base stations within one month. \n", "\n", "The data format is as follows:\n", "* `lac`: Location Area Code (LAC). The Location Area Code, abbreviated as LAC is the unique number given to each location area within the network. The served area of a cellular radio access network is usually divided into location areas, consisting of one or several radio cells.\n", "* `cid`: Cell ID (CID). A GSM Cell ID (CID) is a generally unique number used to identify each base transceiver station (BTS) or sector of a BTS within a location area code (LAC) if not within a GSM network.\n", "* `ts`: UNIX-time. Means the number of seconds elapsed from 01.01.1970 to the event in question.\n", "* `fulldate`: Date\n", "* `hash_id`: Mobile user ID\n", "\n", "The data is divided into two parts by the `fulldate` field:\n", "1) from the 1st to the 14th of the month;\n", "2) from the 16th to the 30th of the month.\n", "\n", "Each part uses its own system for assigning identifiers to subscribers, which leads to the fact that the same subscriber in different parts of the sample has different identifiers: from 1st to 14th - one, from 16th to 30th - another." ] }, { "cell_type": "markdown", "id": "72a62db0-57c5-45b0-a1c8-03d30580fb1d", "metadata": {}, "source": [ "Develop an algorithm that will establish a unique correspondence between identifiers from the first and second parts of the sample. \n", "\n", "The expected result is a table of correspondences of the form `id1 - id2` in *.csv format, where `id1` is an identifier from the first part of the selection, `id2` is an identifier from the second part of the selection. \n", "To help you, a standard of 491 pairs of `id1` and `id2` is provided. You need to determine the remaining 1000+ matches." ] }, { "cell_type": "markdown", "id": "b6c9d040-16d5-4e69-86e6-b199fcf85f56", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "## Imports" ] }, { "cell_type": "code", "execution_count": 1, "id": "ae6c958b-9856-40cd-95e3-a7c7ea710bba", "metadata": {}, "outputs": [], "source": [ "# !pip install category_encoders eli5" ] }, { "cell_type": "code", "execution_count": 2, "id": "15c1c34e-027a-42e7-b0c2-d7014830f7ca", "metadata": {}, "outputs": [], "source": [ "import os\n", "import sys\n", "import warnings\n", "\n", "import eli5\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "from sklearn.exceptions import ConvergenceWarning\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import precision_score, recall_score\n", "from sklearn.model_selection import train_test_split\n", "from tqdm.notebook import tqdm" ] }, { "cell_type": "code", "execution_count": 3, "id": "00d15379", "metadata": {}, "outputs": [], "source": [ "from utils.memory_utils import reduce_mem_usage\n", "from utils.time_utils import get_time_features, time_features\n", "from utils.train_utils import fit_and_score, tf_idf_transform" ] }, { "cell_type": "code", "execution_count": 4, "id": "e7eb4972-3257-4505-8044-d1a9dba7d742", "metadata": {}, "outputs": [], "source": [ "sns.set(rc={\"figure.dpi\": 100, \"savefig.dpi\": 300})\n", "sns.set_context(\"notebook\")\n", "sns.set_style(\"ticks\")\n", "\n", "%matplotlib inline\n", "%config InlineBackend.figure_format = 'retina'\n", "\n", "tqdm.pandas()" ] }, { "cell_type": "code", "execution_count": 5, "id": "a1b430b3-b120-4880-bfce-f7bf60083ae3", "metadata": {}, "outputs": [], "source": [ "ConvergenceWarning(\"ignore\")\n", "\n", "warnings.filterwarnings(\"ignore\")\n", "if not sys.warnoptions:\n", " warnings.simplefilter(\"ignore\")\n", " os.environ[\n", " \"PYTHONWARNINGS\"\n", " ] = \"ignore::UserWarning,ignore::ConvergenceWarning,ignore::RuntimeWarning\"" ] }, { "cell_type": "code", "execution_count": 6, "id": "6bb257e1-557f-43ae-9e44-b0f0ef1240f3", "metadata": {}, "outputs": [], "source": [ "SEED = 42" ] }, { "cell_type": "markdown", "id": "8153867e-46f0-4c38-845c-abfb485ca1fa", "metadata": {}, "source": [ "## Paths" ] }, { "cell_type": "markdown", "id": "970f6037-20e3-42e9-9ab5-3bd1bc42bb5f", "metadata": {}, "source": [ "### Input" ] }, { "cell_type": "code", "execution_count": 7, "id": "de925bd9-6694-48da-bde6-37d6ed175d01", "metadata": {}, "outputs": [], "source": [ "RELATIVE_PATH = \"../data/\"" ] }, { "cell_type": "code", "execution_count": 8, "id": "7b0d40d2-7a60-427c-800f-af56ceb7f6c6", "metadata": {}, "outputs": [], "source": [ "DATA_PATH_PARQUET = os.path.join(RELATIVE_PATH, \"01_data.parquet\")\n", "REFERENCE_PATH_PARQUET = os.path.join(RELATIVE_PATH, \"02_etalon.parquet\")" ] }, { "cell_type": "markdown", "id": "d45e5b81-3df9-4bcc-969a-bae5ede391e1", "metadata": {}, "source": [ "### Output" ] }, { "cell_type": "code", "execution_count": 9, "id": "75cda383-963f-48e7-8df3-9c561673c290", "metadata": {}, "outputs": [], "source": [ "FINAL_MAPPING_PATH_CSV = os.path.join(RELATIVE_PATH, \"final_mapping.csv\")" ] }, { "cell_type": "markdown", "id": "0847670e-ac3d-411d-816a-f9ad0d380757", "metadata": {}, "source": [ "## Loading Data" ] }, { "cell_type": "markdown", "id": "98047347-3e10-4ebe-b0af-162cd8dd54b1", "metadata": {}, "source": [ "I've re-saved files in `parquet` format for faster loading (6x) and less memory consumption while storing (5x) (notebook `01_optimizing_storage.ipynb`)" ] }, { "cell_type": "code", "execution_count": 10, "id": "7e817005-1f68-400e-bc34-cbdcfaffa6f1", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 9153692 entries, 0 to 9153691\n", "Data columns (total 5 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 lac int64 \n", " 1 cid int64 \n", " 2 ts float64\n", " 3 fulldate object \n", " 4 hash_id int64 \n", "dtypes: float64(1), int64(3), object(1)\n", "memory usage: 349.2+ MB\n" ] } ], "source": [ "data = pd.read_parquet(DATA_PATH_PARQUET)\n", "data.info()" ] }, { "cell_type": "code", "execution_count": 11, "id": "5cfeda92-4525-42e9-a3fc-3d45b63a9fb9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 491 entries, 0 to 490\n", "Data columns (total 2 columns):\n", " # Column Non-Null Count Dtype\n", "--- ------ -------------- -----\n", " 0 id1 491 non-null int64\n", " 1 id2 491 non-null int64\n", "dtypes: int64(2)\n", "memory usage: 7.8 KB\n" ] } ], "source": [ "reference = pd.read_parquet(REFERENCE_PATH_PARQUET)\n", "reference.info()" ] }, { "cell_type": "markdown", "id": "2251a881-0455-41e2-905a-ee3b2e9da8e4", "metadata": {}, "source": [ "## Dataset Overview" ] }, { "cell_type": "code", "execution_count": 12, "id": "23ff09ef-c29f-423d-9ae6-eb0be495cacf", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " lac cid ts fulldate hash_id\n", "5020211 9732 198732291 1.538248e+09 2018-09-29 2193027\n", "1751775 9731 198722053 1.536042e+09 2018-09-04 1167117\n", "6373931 9934 197611523 1.537859e+09 2018-09-25 2129824\n", "7344952 9745 10301 1.537101e+09 2018-09-16 2893856\n", "5139826 9713 198838786 1.537440e+09 2018-09-20 2677662\n", "8988177 7716 60325 1.537241e+09 2018-09-18 2862389\n", "7552833 9716 198688516 1.537810e+09 2018-09-24 2521886\n", "4635300 9937 249030668 1.537884e+09 2018-09-25 2571471\n", "64115 9716 31422 1.536637e+09 2018-09-11 1213812\n", "6502056 9785 198067460 1.537098e+09 2018-09-16 2841115" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.sample(n=10, random_state=SEED)" ] }, { "cell_type": "markdown", "id": "f61a23bf-4aa1-469e-9059-2c10af8a21e6", "metadata": { "tags": [] }, "source": [ "## Dataset Close Look" ] }, { "cell_type": "markdown", "id": "bdb4bd5a-1861-4673-b79e-85768d178a0d", "metadata": {}, "source": [ "In this section, let's look at what columns we have, what type they are, how many non-zero values, etc." ] }, { "cell_type": "markdown", "id": "43d5d8cf-f518-4013-aacd-7abac73333bf", "metadata": {}, "source": [ "### Reference" ] }, { "cell_type": "code", "execution_count": 13, "id": "b7408179-0fc2-4ce4-87dc-cddcf69f2158", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 333, "width": 873 }, "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "reference.hist(figsize=(15, 5), bins=100)" ] }, { "cell_type": "markdown", "id": "199c69a8-1a86-41be-ba93-38c5e28bebe9", "metadata": {}, "source": [ "We will not be able to find any dependencies in reference's data" ] }, { "cell_type": "markdown", "id": "d79f11b9-74be-4245-af57-8188f3c5cebb", "metadata": {}, "source": [ "### Data" ] }, { "cell_type": "code", "execution_count": 16, "id": "1662f574-48a5-4ba0-b54e-4daacfd1607c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "RangeIndex: 9153692 entries, 0 to 9153691\n", "Data columns (total 5 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 lac int64 \n", " 1 cid int64 \n", " 2 ts float64\n", " 3 fulldate object \n", " 4 hash_id int64 \n", "dtypes: float64(1), int64(3), object(1)\n", "memory usage: 349.2+ MB\n" ] } ], "source": [ "data.info()" ] }, { "cell_type": "markdown", "id": "1e7ddec3-dde7-40d7-89af-aaf491b8eb96", "metadata": {}, "source": [ "Fields:\n", "* `lac`: Location Area Code (LAC). The Location Area Code, abbreviated as LAC is the unique number given to each location area within the network. The served area of a cellular radio access network is usually divided into location areas, consisting of one or several radio cells.\n", "* `cid`: Cell ID (CID). A GSM Cell ID (CID) is a generally unique number used to identify each base transceiver station (BTS) or sector of a BTS within a location area code (LAC) if not within a GSM network.\n", "* `ts`: UNIX-time. Means the number of seconds elapsed from 01.01.1970 to the event in question.\n", "* `fulldate`: Date\n", "* `hash_id`: Mobile user ID" ] }, { "cell_type": "markdown", "id": "eac55ae4-bb78-4553-97f7-84ef2800254d", "metadata": { "tags": [] }, "source": [ "#### `lac`" ] }, { "cell_type": "code", "execution_count": 17, "id": "b329c3ae-6bf0-4a3a-a4dd-fa56b8c84c65", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 9153692.000000\n", "mean 8950.529107\n", "std 1377.873462\n", "min 3302.000000\n", "1% 5015.000000\n", "5% 5061.000000\n", "25% 7752.000000\n", "50% 9716.000000\n", "75% 9772.000000\n", "95% 9935.000000\n", "99% 9942.000000\n", "99.9% 9976.000000\n", "max 43000.000000\n", "Name: lac, dtype: object" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"lac\"].describe(\n", " percentiles=[0.01, 0.05, 0.25, 0.5, 0.75, 0.95, 0.99, 0.999]\n", ").apply(lambda x: format(x, \"f\"))" ] }, { "cell_type": "code", "execution_count": 18, "id": "c2971523-ab08-44e8-a19b-52119e01c5a3", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 262, "width": 375 }, "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "data[data[\"lac\"] <= 9976][\"lac\"].hist(bins=100)" ] }, { "cell_type": "markdown", "id": "affe9eb7-4963-44e2-8726-96663e8c034c", "metadata": {}, "source": [ "There are only a few popular ranges of values for `lac`" ] }, { "cell_type": "code", "execution_count": 20, "id": "bcdbf3bb-8b33-477b-956b-ab3d44f529d6", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "9716 951184\n", "9734 567379\n", "7716 537042\n", "9916 534000\n", "9934 490347\n", " ... \n", "23131 1\n", "23120 1\n", "9109 1\n", "9560 1\n", "9101 1\n", "Name: lac, Length: 364, dtype: int64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"lac\"].value_counts()" ] }, { "cell_type": "markdown", "id": "d4a7dbc0-5b7b-4bb0-91cb-a1f4d1ff21ff", "metadata": {}, "source": [ "We can see that we have 364 unique locations, although some of them are not very popular, while some of them are." ] }, { "cell_type": "markdown", "id": "5e7f0051-aa3d-4909-a05a-ba31d9ee1c7b", "metadata": {}, "source": [ "There are some outliers" ] }, { "cell_type": "code", "execution_count": 21, "id": "2718e228-a079-44ef-af99-c62b7e4919ba", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "41800 31\n", "43000 22\n", "41801 19\n", "23130 4\n", "23111 3\n", "23141 2\n", "23120 1\n", "23131 1\n", "Name: lac, dtype: int64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[data[\"lac\"] > 9976][\"lac\"].value_counts()" ] }, { "cell_type": "markdown", "id": "cb748aca-6064-4596-8254-6b4a722c6d98", "metadata": {}, "source": [ "#### `cid`" ] }, { "cell_type": "code", "execution_count": 22, "id": "845cfe2e-bdeb-4620-8cba-6a5b8e36a223", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3323 33830\n", "33104 24805\n", "3253 23217\n", "33102 21505\n", "14642 19027\n", " ... \n", "61225 1\n", "36645 1\n", "231806230 1\n", "197768708 1\n", "28596 1\n", "Name: cid, Length: 75052, dtype: int64" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"cid\"].value_counts()" ] }, { "cell_type": "markdown", "id": "4add314e-cdb6-44ec-a6ce-d2c76048fdb9", "metadata": {}, "source": [ "We have a lot of unique values" ] }, { "cell_type": "code", "execution_count": 23, "id": "2e470c91-9f76-4179-8502-7d6925976fb5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 275, "width": 373 }, "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "data[\"cid\"].hist()" ] }, { "cell_type": "code", "execution_count": 24, "id": "b66ef867-9d52-41f8-8da0-79737b01fd9a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 9153692.000000\n", "mean 110670504.759660\n", "std 98943536.660267\n", "min 1.000000\n", "1% 517.000000\n", "5% 2317.000000\n", "25% 32048.000000\n", "36% 62477.000000\n", "36.94% 65522.000000\n", "36.95% 858479.000000\n", "50% 129608451.000000\n", "75% 198014732.000000\n", "95% 232057857.000000\n", "99% 253467908.000000\n", "99.9% 254263301.000000\n", "max 254855684.000000\n", "Name: cid, dtype: object" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"cid\"].describe(\n", " percentiles=[0.01, 0.05, 0.25, 0.36, 0.3694, 0.3695, 0.5, 0.75, 0.95, 0.99, 0.999]\n", ").apply(lambda x: format(x, \"f\"))" ] }, { "cell_type": "markdown", "id": "34d3894e-fdad-4c26-85b6-f22714dc00ad", "metadata": {}, "source": [ "Strange difference between 36.94 and 36.95 percentile. Let's find out more about `cid`" ] }, { "cell_type": "markdown", "id": "4d044181-ae7d-42cf-bdab-d5a7158ce4f1", "metadata": {}, "source": [ "##### Fixing CID" ] }, { "cell_type": "markdown", "id": "18e7b437-6d03-404e-9400-0062d3f364df", "metadata": {}, "source": [ "Long cell ID vs. short cell ID \n", "The formula for the long cell ID is as follows: \n", "Long CID = 65536 * RNC + CID \n", "\n", "RNC: the Radio Network Controller \n", "CID: a short cell ID (an integer in the range of 0 to 65535) \n", "\n", "If you have the Long CID, you can get RNC and CID in the following way: \n", "RNC = Long CID / 65536 (integer division) \n", "CID = Long CID mod 65536 (modulo operation) \n", "\n", "Example for long cell ID 66808694: \n", "RNC = 66808694 / 65536 = 1019 \n", "CID = 66808694 mod 65536 = 27510 " ] }, { "cell_type": "markdown", "id": "2b834d18-7498-4351-a95b-8c11b02a1451", "metadata": {}, "source": [ "Aha. We have Long and Short CID mixed. Let's make all Long CID Short." ] }, { "cell_type": "code", "execution_count": 25, "id": "209d16c7-327c-4576-b3d8-b4696ce779f2", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5f25041beff74704a917e1af6c1d71bb", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/9153692 [00:00 65535 else cid\n", ")" ] }, { "cell_type": "code", "execution_count": 26, "id": "3863a76e-151d-4f28-8a24-99b8698e2eb8", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "count 9153692.000000\n", "mean 28729.860331\n", "std 19928.071245\n", "min 1.000000\n", "25% 10273.000000\n", "50% 28965.000000\n", "75% 45571.000000\n", "max 65534.000000\n", "Name: cid, dtype: object" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"cid\"].describe().apply(lambda x: format(x, \"f\"))" ] }, { "cell_type": "code", "execution_count": 27, "id": "ae326477-ef6d-4ab9-b855-4183004e90a9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3323 33830\n", "25861 26781\n", "33104 24805\n", "30466 23887\n", "3253 23217\n", " ... \n", "42709 1\n", "61044 1\n", "23468 1\n", "15264 1\n", "27058 1\n", "Name: cid, Length: 38926, dtype: int64" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"cid\"].value_counts()" ] }, { "cell_type": "markdown", "id": "55536706-8306-4ae1-b42a-55ae1d429632", "metadata": {}, "source": [ "Now it looks better" ] }, { "cell_type": "code", "execution_count": 28, "id": "75d45d2b-70c7-4881-9fbf-388edbeb9b38", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 262, "width": 380 }, "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "data[\"cid\"].hist()" ] }, { "cell_type": "markdown", "id": "52248b50-3e44-45c4-b42a-6c22e1e644f5", "metadata": {}, "source": [ "#### `lac` and `cid` interaction" ] }, { "cell_type": "code", "execution_count": 29, "id": "f067f559-dad6-42ae-b4fc-1c62a9348193", "metadata": {}, "outputs": [], "source": [ "lac_cid_group = (\n", " pd.DataFrame(data.groupby([\"lac\", \"cid\"])[\"cid\"].count())\n", " .rename(columns={\"cid\": \"count\"})\n", " .reset_index()\n", ")" ] }, { "cell_type": "code", "execution_count": 30, "id": "07043e6a-3697-41a3-bd0b-e35fe3351494", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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laccidcount
35000127
109865029116
13378503712
158825047133
465179000171
46681900111
46872900211
534359054125
541979071135
575409704117
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\n", "
" ], "text/plain": [ " lac cid count\n", "3 5000 1 27\n", "10986 5029 1 16\n", "13378 5037 1 2\n", "15882 5047 1 33\n", "46517 9000 1 71\n", "46681 9001 1 1\n", "46872 9002 1 1\n", "53435 9054 1 25\n", "54197 9071 1 35\n", "57540 9704 1 17\n", "59837 9715 1 22\n", "63461 9733 1 6\n", "67446 9746 1 6\n", "68400 9748 1 8\n", "68937 9751 1 112\n", "73291 9773 1 7\n", "75695 9790 1 280\n", "76526 9795 1 28\n", "78712 9915 1 30\n", "81516 9950 1 6" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "with pd.option_context(\"display.max_rows\", None, \"display.max_columns\", None):\n", " display(lac_cid_group.sort_values(by=[\"cid\", \"lac\"]).iloc[:20])" ] }, { "cell_type": "markdown", "id": "cca57584-58be-4e69-927d-0ba9d31b809b", "metadata": {}, "source": [ "The same `cid` can belong to different `lac`, which is strange. But it can be fine, if for every `lac` there is its own `cid`" ] }, { "cell_type": "code", "execution_count": 31, "id": "0c540046-ac05-4d37-979f-97143a11728d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(82191, 3)" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "lac_cid_group.shape" ] }, { "cell_type": "markdown", "id": "d7bf4c2c-d1b1-4a89-a933-64e0ad31b0a4", "metadata": {}, "source": [ "There are 82191 unique combinations of `lac` and `cid`" ] }, { "cell_type": "markdown", "id": "1c421d51-ef49-40ec-95a7-008bd5139ba8", "metadata": {}, "source": [ "Let's create a feature, where `lac` and `cid` will be together" ] }, { "cell_type": "code", "execution_count": 32, "id": "5bcb0638-fdeb-450b-a1bb-c62ff037317f", "metadata": {}, "outputs": [], "source": [ "data[\"lac_cid\"] = data[\"lac\"].astype(\"str\") + \"_\" + data[\"cid\"].astype(\"str\")" ] }, { "cell_type": "markdown", "id": "509527cc-4ac9-451a-baa4-93da6cb7df5e", "metadata": {}, "source": [ "#### `ts`" ] }, { "cell_type": "markdown", "id": "3dd4ecb0-5a56-4466-83d5-be691a18c0d6", "metadata": {}, "source": [ "`ts` column will be transformed into `datetime` format in the next section" ] }, { "cell_type": "markdown", "id": "76f5ab22-a5ac-4bbb-b056-91bf1022e693", "metadata": {}, "source": [ "#### `fulldate`" ] }, { "cell_type": "markdown", "id": "4770e871-a73f-4a5c-a129-f72dee4d6799", "metadata": {}, "source": [ "`fulldate` column will be transformed into `datetime` format in the next section" ] }, { "cell_type": "markdown", "id": "5449a5f0-ebaa-4fdb-9245-61e394e015f1", "metadata": {}, "source": [ "#### `hash_id`" ] }, { "cell_type": "code", "execution_count": 33, "id": "ca46f511-964f-45f0-9e92-6532d12c4a60", "metadata": {}, "outputs": [], "source": [ "unique_hash_ids = data[\"hash_id\"].unique()" ] }, { "cell_type": "code", "execution_count": 34, "id": "fa7171a8-b115-44bb-9832-12320dc2db90", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1088711 34138\n", "2187102 30128\n", "2674156 18115\n", "2102524 13183\n", "1819111 12862\n", " ... \n", "1968066 4\n", "1255062 4\n", "1754876 3\n", "1534909 2\n", "1570683 1\n", "Name: hash_id, Length: 4542, dtype: int64" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[\"hash_id\"].value_counts()" ] }, { "cell_type": "markdown", "id": "4109669c-1959-44d6-a757-fc2df1ee1a37", "metadata": {}, "source": [ "We know that there are reference out of $491$ pairs, which makes $982$ IDs that have direct matching" ] }, { "cell_type": "markdown", "id": "6a23eea2-8608-425b-b03a-7eec14f6415b", "metadata": {}, "source": [ "We also know that there are $1000+$ more pairs.\n", "\n", "Maybe we have **IDs** that **don't have a match**. " ] }, { "cell_type": "markdown", "id": "0e58f952-86e7-4faf-9904-005a47de79b2", "metadata": {}, "source": [ "## Data transformation" ] }, { "cell_type": "markdown", "id": "ee7f85bb-e721-4343-8686-6a2b2430344d", "metadata": {}, "source": [ "### Saving a bit of memory" ] }, { "cell_type": "markdown", "id": "4b5b1fd5-5b07-4c6d-88ae-c1c0b2944f47", "metadata": {}, "source": [ "As soon as our dataset is not optimally stored, we can optimize memory consumption." ] }, { "cell_type": "code", "execution_count": 35, "id": "3fa7f5ee-c4e1-4eee-b813-92d1701a0dfb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Memory usage of dataframe is 349.19 MB\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "723acf46d65145fb91466c003fe8eeca", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%| | 0/5 [00:00\n", "RangeIndex: 9153692 entries, 0 to 9153691\n", "Data columns (total 6 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 lac int32 \n", " 1 cid int32 \n", " 2 datetime_ts datetime64[ns]\n", " 3 hash_id int32 \n", " 4 lac_cid category \n", " 5 fulldate datetime64[ns]\n", "dtypes: category(1), datetime64[ns](2), int32(3)\n", "memory usage: 282.0 MB\n" ] } ], "source": [ "data.info()" ] }, { "cell_type": "markdown", "id": "b2d391d9-a623-41a9-85b1-1e466384d3dd", "metadata": {}, "source": [ "#### Date and Time features extraction" ] }, { "cell_type": "code", "execution_count": 38, "id": "82d20b1e-23c0-4c3c-9cc8-c1ddac75f550", "metadata": {}, "outputs": [], "source": [ "datetime_features, datetime_feature_names = get_time_features(\n", " data[\"fulldate\"], data[\"datetime_ts\"]\n", ")" ] }, { "cell_type": "code", "execution_count": 39, "id": "0d89250f-92b6-425f-9a7e-9a58c65c52a5", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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hourmorningdayeveningnightweekdayweekend
07100040
17100050
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" ], "text/plain": [ " hour morning day evening night weekday weekend\n", "0 7 1 0 0 0 4 0\n", "1 7 1 0 0 0 5 0\n", "2 9 1 0 0 0 2 0\n", "3 7 1 0 0 0 7 1\n", "4 9 1 0 0 0 3 0" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "datetime_features.head()" ] }, { "cell_type": "code", "execution_count": 40, "id": "0db1ac62-baaf-498f-8db5-ecb9a4f0393e", "metadata": {}, "outputs": [], "source": [ "data = pd.concat([data, datetime_features], axis=1)" ] }, { "cell_type": "markdown", "id": "711ddce7-286d-45e3-bee1-540c78e02822", "metadata": { "tags": [] }, "source": [ "#### Checking data integrity" ] }, { "cell_type": "code", "execution_count": 41, "id": "869bb52e-db93-4fec-9dfb-8024e9c367ea", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
lacciddatetime_tshash_idlac_cidfulldatehourmorningdayeveningnightweekdayweekend
\n", "
" ], "text/plain": [ "Empty DataFrame\n", "Columns: [lac, cid, datetime_ts, hash_id, lac_cid, fulldate, hour, morning, day, evening, night, weekday, weekend]\n", "Index: []" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[(data[\"fulldate\"].dt.day == 15) | (data[\"fulldate\"].dt.day == 31)]" ] }, { "cell_type": "markdown", "id": "7af7a0dd-462e-446c-a562-bb17efe2e0ea", "metadata": {}, "source": [ "As promised, the data was split into two parts by day: \n", "* from the $1^{st}$ to the $14^{th}$ of the month\n", "* from the $16^{th}$ to the $30^{th}$ of the month \n", "\n", "So there are no $15$ and $31$ days in the sample. It's fine." ] }, { "cell_type": "code", "execution_count": 42, "id": "05bc171a-63dc-4576-a0ee-874ec4876d3d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[datetime.date(2018, 9, 1),\n", " datetime.date(2018, 9, 2),\n", " datetime.date(2018, 9, 3),\n", " datetime.date(2018, 9, 4),\n", " datetime.date(2018, 9, 5),\n", " datetime.date(2018, 9, 6),\n", " datetime.date(2018, 9, 7),\n", " datetime.date(2018, 9, 8),\n", " datetime.date(2018, 9, 9),\n", " datetime.date(2018, 9, 10),\n", " datetime.date(2018, 9, 11),\n", " datetime.date(2018, 9, 12),\n", " datetime.date(2018, 9, 13),\n", " datetime.date(2018, 9, 14),\n", " datetime.date(2018, 9, 16),\n", " datetime.date(2018, 9, 17),\n", " datetime.date(2018, 9, 18),\n", " datetime.date(2018, 9, 19),\n", " datetime.date(2018, 9, 20),\n", " datetime.date(2018, 9, 21),\n", " datetime.date(2018, 9, 22),\n", " datetime.date(2018, 9, 23),\n", " datetime.date(2018, 9, 24),\n", " datetime.date(2018, 9, 25),\n", " datetime.date(2018, 9, 26),\n", " datetime.date(2018, 9, 27),\n", " datetime.date(2018, 9, 28),\n", " datetime.date(2018, 9, 29),\n", " datetime.date(2018, 9, 30)]" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sorted(data[\"fulldate\"].dt.date.unique())" ] }, { "cell_type": "markdown", "id": "c2d2dd35-6bb6-43be-9215-195073b50fb8", "metadata": {}, "source": [ "We have one full month - $\\text{September 2018}$, except $15$ and $31$ days, as stated before." ] }, { "cell_type": "markdown", "id": "efc9e51d-c639-461a-b435-44bf2aa4cdc2", "metadata": {}, "source": [ "There are $\\text{61 297}$ records for which date from `fulldate` column doesn't match the date, which was obtained from `ts` column. \n", "Not fine!" ] }, { "cell_type": "code", "execution_count": 43, "id": "31f60060-cb19-49a4-a3f1-e710aac5f7a8", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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lacciddatetime_tshash_idlac_cidfulldatehourmorningdayeveningnightweekdayweekend
07755359502018-09-08 07:10:5613613967755_359502018-09-137100040
17755359502018-09-08 07:10:5613613967755_359502018-09-147100050
27752192032018-09-03 09:31:4413613967752_192032018-09-049100020
37755359502018-09-08 07:10:5613613967755_359502018-09-097100071
47752192032018-09-03 09:31:4413613967752_192032018-09-059100030
..........................................
9153681774665512018-09-24 16:14:5622413187746_65512018-09-2616010030
91536847716118702018-09-13 18:22:5622413187716_118702018-09-1618010071
91536857716118702018-09-13 18:22:5622413187716_118702018-09-1918010030
9153686774665512018-09-24 16:14:5622413187746_65512018-09-2816010050
91536917716118702018-09-13 18:22:5622413187716_118702018-09-1718010010
\n", "

61297 rows × 13 columns

\n", "
" ], "text/plain": [ " lac cid datetime_ts hash_id lac_cid fulldate \\\n", "0 7755 35950 2018-09-08 07:10:56 1361396 7755_35950 2018-09-13 \n", "1 7755 35950 2018-09-08 07:10:56 1361396 7755_35950 2018-09-14 \n", "2 7752 19203 2018-09-03 09:31:44 1361396 7752_19203 2018-09-04 \n", "3 7755 35950 2018-09-08 07:10:56 1361396 7755_35950 2018-09-09 \n", "4 7752 19203 2018-09-03 09:31:44 1361396 7752_19203 2018-09-05 \n", "... ... ... ... ... ... ... \n", "9153681 7746 6551 2018-09-24 16:14:56 2241318 7746_6551 2018-09-26 \n", "9153684 7716 11870 2018-09-13 18:22:56 2241318 7716_11870 2018-09-16 \n", "9153685 7716 11870 2018-09-13 18:22:56 2241318 7716_11870 2018-09-19 \n", "9153686 7746 6551 2018-09-24 16:14:56 2241318 7746_6551 2018-09-28 \n", "9153691 7716 11870 2018-09-13 18:22:56 2241318 7716_11870 2018-09-17 \n", "\n", " hour morning day evening night weekday weekend \n", "0 7 1 0 0 0 4 0 \n", "1 7 1 0 0 0 5 0 \n", "2 9 1 0 0 0 2 0 \n", "3 7 1 0 0 0 7 1 \n", "4 9 1 0 0 0 3 0 \n", "... ... ... ... ... ... ... ... \n", "9153681 16 0 1 0 0 3 0 \n", "9153684 18 0 1 0 0 7 1 \n", "9153685 18 0 1 0 0 3 0 \n", "9153686 16 0 1 0 0 5 0 \n", "9153691 18 0 1 0 0 1 0 \n", "\n", "[61297 rows x 13 columns]" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data[data[\"fulldate\"].dt.date != data[\"datetime_ts\"].dt.date]" ] }, { "cell_type": "markdown", "id": "96b02910-4b9b-4bad-8f0c-e71893235706", "metadata": {}, "source": [ "And there are some records for which splitting in two groups could be ambiguous. \n", "For example, `fulldate` is `2018-09-19` and `datetime_ts` is `2018-09-13`. Using one column data should be in one partition and using other column data should be in another partition." ] }, { "cell_type": "markdown", "id": "c0b50192-5d23-4d15-b11d-4152a437bfa8", "metadata": {}, "source": [ "### User journeys creation from `lac_cid` feature" ] }, { "cell_type": "markdown", "id": "3bece659-3ce8-4b73-bfd7-fa6ab1fb7c63", "metadata": {}, "source": [ "I've found out that we can create a list of `lac_cid` values for every user in sorted order (by `datetime_ts` column). \n", "It will show how every specific user was registered on different base stations along the way of time." ] }, { "cell_type": "markdown", "id": "699deec9-eef5-4505-ad6a-5200b5c59934", "metadata": {}, "source": [ "For example, let's take one `hash_id`" ] }, { "cell_type": "code", "execution_count": 44, "id": "0a5f953d-3de3-4744-aaeb-b38d754a51ff", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1361396" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "unique_hash_ids[0]" ] }, { "cell_type": "markdown", "id": "c7d34d2e-0155-4e13-9cfe-6198d09f8886", "metadata": {}, "source": [ "And look at the path for user $1361396$" ] }, { "cell_type": "code", "execution_count": 45, "id": "b65ccfba-f3d9-4655-859c-61c8e7633223", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'5007_7088 7752_19207 7752_19203 7752_19203 7752_19203 7752_19207 7752_19207 7752_19203 7755_23103 7755_23103 7755_23103 7755_35950 7755_35950 7755_35950 7755_35950 7755_35950 7755_35950 7755_35950'" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\" \".join(\n", " data[data[\"hash_id\"] == 1361396].sort_values(by=\"datetime_ts\")[\"lac_cid\"].values\n", ")" ] }, { "cell_type": "markdown", "id": "23eda193-7d33-4704-aa59-0653123ec257", "metadata": {}, "source": [ "Let's do this for every user in our dataset. \n", "We can save the whole path for every user, but probably we will be good with only part of it. \n", "\n", "The length of the path could be some arbitrary number like 100 or 200, or it could be some statistic, like mean/median/specific percentile of the length distribution across users. \n", "\n", "For now, let's take median value for the dataset. " ] }, { "cell_type": "code", "execution_count": 46, "id": "74b25fc4-99ee-499e-a68f-9d59599d55c1", "metadata": {}, "outputs": [], "source": [ "user_journeys = {}" ] }, { "cell_type": "code", "execution_count": 47, "id": "7926ee37-367e-4ada-86cc-9e6ae4e5c48c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1450" ] }, "execution_count": 47, "metadata": {}, "output_type": "execute_result" } ], "source": [ "n_journeys = int(data.groupby(\"hash_id\")[\"lac_cid\"].count().median())\n", "n_journeys" ] }, { "cell_type": "code", "execution_count": 48, "id": "5ec7529f-4519-4eab-8f7f-a484531b9b9c", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "e3a614ec4dab4d839404b97062594a09", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Creating user journeys: 0%| | 0/4542 [00:00\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
lacciddatetime_tshash_idlac_cidfulldatehourmorningdayeveningnightweekdayweekenduser_journey
50202119732271392018-09-29 19:07:4421930279732_271392018-09-29190010619732_27139 9732_27168 9732_27139 9732_27168 97...
17517759731169012018-09-04 06:19:4411671179731_169012018-09-0460001209091_52008 9060_16643 9091_52008 5091_64312 90...
63739319934204832018-09-25 07:00:1621298249934_204832018-09-2571000207716_38835 9716_31069 7716_48445 9716_61958 77...
73449529745103012018-09-16 12:33:0428938569745_103012018-09-16120100717716_3323 7716_9553 9716_34606 7716_3323 7716_...
5139826971325622018-09-20 10:35:4426776629713_25622018-09-20101000409716_30230 9716_17210 9716_3145 7716_3155 9716...
89881777716603252018-09-18 03:22:4028623897716_603252018-09-1830001207716_60325 7716_9553 7716_60325 7716_9553 7716...
75528339716489002018-09-24 17:27:2825218869716_489002018-09-24170100107730_460 7716_2147 9716_30220 9716_36733 7730_...
46353009937594042018-09-25 13:54:0825714719937_594042018-09-25130100209758_23298 9734_14852 9758_23298 9734_14849 97...
641159716314222018-09-11 03:33:2012138129716_314222018-09-1130001207716_60475 9716_31422 7716_60475 9716_31422 77...
65020569785176682018-09-16 11:46:0828411159785_176682018-09-16111000719716_9218 9716_9218 7716_3579 7716_3579 9716_3...
\n", "" ], "text/plain": [ " lac cid datetime_ts hash_id lac_cid fulldate \\\n", "5020211 9732 27139 2018-09-29 19:07:44 2193027 9732_27139 2018-09-29 \n", "1751775 9731 16901 2018-09-04 06:19:44 1167117 9731_16901 2018-09-04 \n", "6373931 9934 20483 2018-09-25 07:00:16 2129824 9934_20483 2018-09-25 \n", "7344952 9745 10301 2018-09-16 12:33:04 2893856 9745_10301 2018-09-16 \n", "5139826 9713 2562 2018-09-20 10:35:44 2677662 9713_2562 2018-09-20 \n", "8988177 7716 60325 2018-09-18 03:22:40 2862389 7716_60325 2018-09-18 \n", "7552833 9716 48900 2018-09-24 17:27:28 2521886 9716_48900 2018-09-24 \n", "4635300 9937 59404 2018-09-25 13:54:08 2571471 9937_59404 2018-09-25 \n", "64115 9716 31422 2018-09-11 03:33:20 1213812 9716_31422 2018-09-11 \n", "6502056 9785 17668 2018-09-16 11:46:08 2841115 9785_17668 2018-09-16 \n", "\n", " hour morning day evening night weekday weekend \\\n", "5020211 19 0 0 1 0 6 1 \n", "1751775 6 0 0 0 1 2 0 \n", "6373931 7 1 0 0 0 2 0 \n", "7344952 12 0 1 0 0 7 1 \n", "5139826 10 1 0 0 0 4 0 \n", "8988177 3 0 0 0 1 2 0 \n", "7552833 17 0 1 0 0 1 0 \n", "4635300 13 0 1 0 0 2 0 \n", "64115 3 0 0 0 1 2 0 \n", "6502056 11 1 0 0 0 7 1 \n", "\n", " user_journey \n", "5020211 9732_27139 9732_27168 9732_27139 9732_27168 97... \n", "1751775 9091_52008 9060_16643 9091_52008 5091_64312 90... \n", "6373931 7716_38835 9716_31069 7716_48445 9716_61958 77... \n", "7344952 7716_3323 7716_9553 9716_34606 7716_3323 7716_... \n", "5139826 9716_30230 9716_17210 9716_3145 7716_3155 9716... \n", "8988177 7716_60325 7716_9553 7716_60325 7716_9553 7716... \n", "7552833 7730_460 7716_2147 9716_30220 9716_36733 7730_... \n", "4635300 9758_23298 9734_14852 9758_23298 9734_14849 97... \n", "64115 7716_60475 9716_31422 7716_60475 9716_31422 77... \n", "6502056 9716_9218 9716_9218 7716_3579 7716_3579 9716_3... " ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.sample(10, random_state=SEED)" ] }, { "cell_type": "code", "execution_count": 51, "id": "47e44e1e-d63b-4734-a896-da091b6c5cb0", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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4542 rows × 25 columns

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" ], "text/plain": [ "hour reg_hour_0 reg_hour_1 reg_hour_2 reg_hour_3 reg_hour_4 \\\n", "hash_id \n", "1000773 0.000000 0.000000 0.017241 0.025862 0.008621 \n", "1000808 0.041284 0.041284 0.041284 0.041284 0.050459 \n", "1000868 0.028777 0.028777 0.032374 0.035971 0.035971 \n", "1001103 0.027027 0.000000 0.000000 0.000000 0.081081 \n", "1001168 0.043103 0.025862 0.017241 0.051724 0.051724 \n", "... ... ... ... ... ... \n", "2998617 0.000000 0.008475 0.008475 0.033898 0.042373 \n", "2999034 0.005405 0.005405 0.016216 0.054054 0.059459 \n", "2999248 0.008163 0.016327 0.008163 0.036735 0.053061 \n", "2999753 0.017045 0.011364 0.005682 0.017045 0.045455 \n", "2999841 0.000000 0.000000 0.000000 0.000000 0.021739 \n", "\n", "hour reg_hour_5 reg_hour_6 reg_hour_7 reg_hour_8 reg_hour_9 ... \\\n", "hash_id ... \n", "1000773 0.017241 0.034483 0.077586 0.051724 0.077586 ... \n", "1000808 0.055046 0.050459 0.013761 0.018349 0.032110 ... \n", "1000868 0.043165 0.046763 0.039568 0.039568 0.046763 ... \n", "1001103 0.081081 0.081081 0.081081 0.081081 0.081081 ... \n", "1001168 0.068966 0.025862 0.034483 0.017241 0.025862 ... \n", "... ... ... ... ... ... ... \n", "2998617 0.033898 0.050847 0.076271 0.076271 0.059322 ... \n", "2999034 0.054054 0.059459 0.070270 0.064865 0.059459 ... \n", "2999248 0.057143 0.053061 0.057143 0.057143 0.053061 ... \n", "2999753 0.051136 0.068182 0.056818 0.028409 0.034091 ... \n", "2999841 0.108696 0.043478 0.021739 0.043478 0.086957 ... \n", "\n", "hour reg_hour_15 reg_hour_16 reg_hour_17 reg_hour_18 reg_hour_19 \\\n", "hash_id \n", "1000773 0.051724 0.068966 0.077586 0.060345 0.068966 \n", "1000808 0.055046 0.059633 0.045872 0.055046 0.059633 \n", "1000868 0.043165 0.050360 0.046763 0.050360 0.046763 \n", "1001103 0.054054 0.054054 0.000000 0.000000 0.000000 \n", "1001168 0.043103 0.060345 0.051724 0.043103 0.025862 \n", "... ... ... ... ... ... \n", "2998617 0.008475 0.025424 0.042373 0.076271 0.076271 \n", "2999034 0.043243 0.059459 0.064865 0.048649 0.021622 \n", "2999248 0.053061 0.057143 0.053061 0.048980 0.044898 \n", "2999753 0.062500 0.068182 0.045455 0.062500 0.039773 \n", "2999841 0.086957 0.065217 0.021739 0.152174 0.108696 \n", "\n", "hour reg_hour_20 reg_hour_21 reg_hour_22 reg_hour_23 reg_hour_total \n", "hash_id \n", "1000773 0.094828 0.008621 0.000000 0.000000 116.0 \n", "1000808 0.059633 0.059633 0.055046 0.050459 218.0 \n", "1000868 0.046763 0.043165 0.039568 0.050360 278.0 \n", "1001103 0.000000 0.000000 0.054054 0.000000 37.0 \n", "1001168 0.034483 0.051724 0.051724 0.060345 116.0 \n", "... ... ... ... ... ... \n", "2998617 0.110169 0.050847 0.000000 0.000000 118.0 \n", "2999034 0.010811 0.005405 0.005405 0.005405 185.0 \n", "2999248 0.016327 0.028571 0.028571 0.008163 245.0 \n", "2999753 0.062500 0.034091 0.028409 0.022727 176.0 \n", "2999841 0.000000 0.000000 0.000000 0.000000 46.0 \n", "\n", "[4542 rows x 25 columns]" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hour_tf = time_features(data, column=\"hour\", prefix=\"reg_hour\", add_total_count=True)\n", "hour_tf" ] }, { "cell_type": "code", "execution_count": 52, "id": "16d8c105-f9a5-4ce2-908f-afe578985bbb", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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4542 rows × 25 columns

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" ], "text/plain": [ "hour reg_hour_0 reg_hour_1 reg_hour_2 reg_hour_3 reg_hour_4 \\\n", "hash_id \n", "1000773 0.000000 0.000000 0.017241 0.025862 0.008621 \n", "1000808 0.041284 0.041284 0.041284 0.041284 0.050459 \n", "1000868 0.028777 0.028777 0.032374 0.035971 0.035971 \n", "1001103 0.027027 0.000000 0.000000 0.000000 0.081081 \n", "1001168 0.043103 0.025862 0.017241 0.051724 0.051724 \n", "... ... ... ... ... ... \n", "2998617 0.000000 0.008475 0.008475 0.033898 0.042373 \n", "2999034 0.005405 0.005405 0.016216 0.054054 0.059459 \n", "2999248 0.008163 0.016327 0.008163 0.036735 0.053061 \n", "2999753 0.017045 0.011364 0.005682 0.017045 0.045455 \n", "2999841 0.000000 0.000000 0.000000 0.000000 0.021739 \n", "\n", "hour reg_hour_5 reg_hour_6 reg_hour_7 reg_hour_8 reg_hour_9 ... \\\n", "hash_id ... \n", "1000773 0.017241 0.034483 0.077586 0.051724 0.077586 ... \n", "1000808 0.055046 0.050459 0.013761 0.018349 0.032110 ... \n", "1000868 0.043165 0.046763 0.039568 0.039568 0.046763 ... \n", "1001103 0.081081 0.081081 0.081081 0.081081 0.081081 ... \n", "1001168 0.068966 0.025862 0.034483 0.017241 0.025862 ... \n", "... ... ... ... ... ... ... \n", "2998617 0.033898 0.050847 0.076271 0.076271 0.059322 ... \n", "2999034 0.054054 0.059459 0.070270 0.064865 0.059459 ... \n", "2999248 0.057143 0.053061 0.057143 0.057143 0.053061 ... \n", "2999753 0.051136 0.068182 0.056818 0.028409 0.034091 ... \n", "2999841 0.108696 0.043478 0.021739 0.043478 0.086957 ... \n", "\n", "hour reg_hour_15 reg_hour_16 reg_hour_17 reg_hour_18 reg_hour_19 \\\n", "hash_id \n", "1000773 0.051724 0.068966 0.077586 0.060345 0.068966 \n", "1000808 0.055046 0.059633 0.045872 0.055046 0.059633 \n", "1000868 0.043165 0.050360 0.046763 0.050360 0.046763 \n", "1001103 0.054054 0.054054 0.000000 0.000000 0.000000 \n", "1001168 0.043103 0.060345 0.051724 0.043103 0.025862 \n", "... ... ... ... ... ... \n", "2998617 0.008475 0.025424 0.042373 0.076271 0.076271 \n", "2999034 0.043243 0.059459 0.064865 0.048649 0.021622 \n", "2999248 0.053061 0.057143 0.053061 0.048980 0.044898 \n", "2999753 0.062500 0.068182 0.045455 0.062500 0.039773 \n", "2999841 0.086957 0.065217 0.021739 0.152174 0.108696 \n", "\n", "hour reg_hour_20 reg_hour_21 reg_hour_22 reg_hour_23 reg_hour_total \n", "hash_id \n", "1000773 0.094828 0.008621 0.000000 0.000000 116.0 \n", "1000808 0.059633 0.059633 0.055046 0.050459 218.0 \n", "1000868 0.046763 0.043165 0.039568 0.050360 278.0 \n", "1001103 0.000000 0.000000 0.054054 0.000000 37.0 \n", "1001168 0.034483 0.051724 0.051724 0.060345 116.0 \n", "... ... ... ... ... ... \n", "2998617 0.110169 0.050847 0.000000 0.000000 118.0 \n", "2999034 0.010811 0.005405 0.005405 0.005405 185.0 \n", "2999248 0.016327 0.028571 0.028571 0.008163 245.0 \n", "2999753 0.062500 0.034091 0.028409 0.022727 176.0 \n", "2999841 0.000000 0.000000 0.000000 0.000000 46.0 \n", "\n", "[4542 rows x 25 columns]" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [ "weekday_tf = time_features(\n", " data, column=\"weekday\", prefix=\"reg_weekday\", add_total_count=True\n", ")\n", "hour_tf" ] }, { "cell_type": "code", "execution_count": 53, "id": "adcc1791-8090-4b80-b798-d2472a4bb000", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "hash_id\n", "1000773 44\n", "1000808 26\n", "1000868 51\n", "1001103 24\n", "1001168 31\n", " ..\n", "2998617 27\n", "2999034 27\n", "2999248 69\n", "2999753 50\n", "2999841 12\n", "Name: lac, Length: 4542, dtype: int64" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.groupby(\"hash_id\")[\"lac\"].nunique()" ] }, { "cell_type": "code", "execution_count": 54, "id": "191bcb21-6e3e-45c0-8fe3-a3aa8b58db4f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "hash_id\n", "1000773 381\n", "1000808 170\n", "1000868 499\n", "1001103 145\n", "1001168 130\n", " ... \n", "2998617 288\n", "2999034 111\n", "2999248 638\n", "2999753 394\n", "2999841 30\n", "Name: cid, Length: 4542, dtype: int64" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.groupby(\"hash_id\")[\"cid\"].nunique()" ] }, { "cell_type": "code", "execution_count": 55, "id": "5cb1400a-8782-4e2d-b73b-c12a04f785f0", "metadata": {}, "outputs": [], "source": [ "# data = data.join(tf, on=\"hash_id\")" ] }, { "cell_type": "code", "execution_count": 56, "id": "00bf8ddf", "metadata": {}, "outputs": [], "source": [ "# data = data.join(lac_counts, on=\"hash_id\")" ] }, { "cell_type": "code", "execution_count": 57, "id": "e26db2c8-b438-4cd2-907c-fe29fcfd958c", "metadata": {}, "outputs": [], "source": [ "# data = data.join(cid_counts, on=\"hash_id\")" ] }, { "cell_type": "markdown", "id": "8c5faddc-1c17-43d2-b217-b239df472e92", "metadata": {}, "source": [ "## Splitting data" ] }, { "cell_type": "markdown", "id": "12f8c7fe-c841-4f1e-9994-ff7927cce603", "metadata": {}, "source": [ "### Splitting" ] }, { "cell_type": "markdown", "id": "b75aff7b-be95-4dd7-a4c5-429c4db7480e", "metadata": {}, "source": [ "Let's prepare `hash_id`'s that will indicate that the row is in train dataset." ] }, { "cell_type": "code", "execution_count": 58, "id": "cd53b18b-bee7-43b5-809e-74012569ae6b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(491, 2)\n" ] } ], "source": [ "train_ind = reference.values.flatten()\n", "\n", "assert len(train_ind) == len(np.unique(train_ind))\n", "print(reference.shape)" ] }, { "cell_type": "markdown", "id": "5d2dcfd6-548a-43af-a6ca-0232b4e1a9c0", "metadata": {}, "source": [ "#### Training dataset" ] }, { "cell_type": "markdown", "id": "c4bb15a9-e5f5-480c-ba04-7bf5a96db15f", "metadata": {}, "source": [ "Slicing data to get training data" ] }, { "cell_type": "code", "execution_count": 59, "id": "dd2ce160-0153-496a-8d6e-2fdf3ca83ed5", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2019095, 14)" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data = data.loc[data[\"hash_id\"].isin(train_ind)]\n", "train_data.shape" ] }, { "cell_type": "code", "execution_count": 60, "id": "8df793df-3571-4e42-a889-6cfce0ead273", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(983406, 14)" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data_left = train_data.loc[\n", " train_data[\"hash_id\"].isin(reference[\"id1\"])\n", "].reset_index(drop=True)\n", "train_data_left.shape" ] }, { "cell_type": "code", "execution_count": 61, "id": "fa1d2f31-0009-4894-b44a-c0afe7e70956", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1035689, 14)" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data_right = train_data.loc[\n", " train_data[\"hash_id\"].isin(reference[\"id2\"])\n", "].reset_index(drop=True)\n", "train_data_right.shape" ] }, { "cell_type": "markdown", "id": "37ed8e8b-26e3-4629-9b77-d596ab4a6c52", "metadata": {}, "source": [ "Both `train_data_left` and `train_data_right` can serve as a training labelled dataset and as a test labelled dataset. \n", "It can be reasonable to take right dataset, because it contains more data." ] }, { "cell_type": "markdown", "id": "1e7391c9-f505-4c37-955a-f98cb49c89a4", "metadata": {}, "source": [ "#### New ID for training dataset" ] }, { "cell_type": "markdown", "id": "bc41db79-ee54-4d72-ba12-223a9b386343", "metadata": {}, "source": [ "Let's fix the problem, where the user has a different ID in different samples for training dataset" ] }, { "cell_type": "code", "execution_count": 62, "id": "f7dd52fe-1fa6-4441-8cad-0d2272bdaee4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(491, 3)" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "reference[\"new_id\"] = list(range(reference.shape[0]))\n", "reference.shape" ] }, { "cell_type": "code", "execution_count": 63, "id": "851e000e-5b60-4c59-81e1-4e04d1d3cac3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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id1id2new_id
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" ], "text/plain": [ " id1 id2 new_id\n", "0 1361396 2695335 0\n", "1 1795864 2458905 1\n", "2 1543059 2730453 2\n", "3 1028066 2539971 3\n", "4 1533076 2712514 4" ] }, "execution_count": 63, "metadata": {}, "output_type": "execute_result" } ], "source": [ "reference.head()" ] }, { "cell_type": "markdown", "id": "4932d641-4916-470a-8b13-57b847f114c7", "metadata": {}, "source": [ "Now we map the ID's to new ID, which will be the same across left and right training datasets for easier evaluation." ] }, { "cell_type": "code", "execution_count": 102, "id": "93d2d0e9-bbed-47ec-ad49-447d88a1daad", "metadata": {}, "outputs": [], "source": [ "left_map = dict(zip(reference[\"id1\"], reference[\"new_id\"]))\n", "right_map = dict(zip(reference[\"id2\"], reference[\"new_id\"]))" ] }, { "cell_type": "code", "execution_count": 65, "id": "5a58f3c8-ca67-492f-9ef5-dc64d096f689", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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lacciddatetime_tshash_idlac_cidfulldatehourmorningdayeveningnightweekdayweekenduser_journey
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lacciddatetime_tshash_idlac_cidfulldatehourmorningdayeveningnightweekdayweekenduser_journey
07755231032018-09-25 20:05:2007755_231032018-09-25200010207755_23103 7755_23103 7755_23103 7755_23103 77...
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" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data_right[\"hash_id\"] = train_data_right[\"hash_id\"].map(right_map)\n", "train_data_right.head()" ] }, { "cell_type": "code", "execution_count": 67, "id": "12ef2ce2-f398-4b48-ad69-8c01432e5053", "metadata": {}, "outputs": [], "source": [ "assert train_data_left[\"hash_id\"].nunique() == train_data_right[\"hash_id\"].nunique()" ] }, { "cell_type": "markdown", "id": "6910334c-7c9d-4d39-96bb-ca3d1d69ed62", "metadata": {}, "source": [ "We still have the same number of classes in left and train datasets" ] }, { "cell_type": "markdown", "id": "deeec8bf-02dd-433a-8e15-d6697022e112", "metadata": { "tags": [] }, "source": [ "#### Testing dataset" ] }, { "cell_type": "markdown", "id": "62668c83-4069-476f-b41e-9250616120a1", "metadata": {}, "source": [ "Slicing to get testing data" ] }, { "cell_type": "code", "execution_count": 68, "id": "976f0349-2788-471c-a959-2370d13430d4", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(7134597, 14)" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_data = data.loc[~data[\"hash_id\"].isin(train_ind)]\n", "test_data.shape" ] }, { "cell_type": "code", "execution_count": 69, "id": "13e04f66-5be4-46b3-9525-e63ed5b96197", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3393052, 14)" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_data_left = test_data.loc[\n", " test_data[\"fulldate\"].dt.day.isin(list(range(1, 15)))\n", "].reset_index(drop=True)\n", "test_data_left.shape" ] }, { "cell_type": "code", "execution_count": 70, "id": "4c8f9c0e-edd8-43ae-b01f-7569f055dfb2", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(3741545, 14)" ] }, "execution_count": 70, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_data_right = test_data.loc[\n", " test_data[\"fulldate\"].dt.day.isin(list(range(16, 31)))\n", "].reset_index(drop=True)\n", "test_data_right.shape" ] }, { "cell_type": "code", "execution_count": 71, "id": "3358c1af-3d21-43a6-8742-f54cf45623e7", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(1757, 1803)" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_data_left[\"hash_id\"].nunique(), test_data_right[\"hash_id\"].nunique()" ] }, { "cell_type": "markdown", "id": "93798c13-fafa-403c-958c-610d28672b33", "metadata": {}, "source": [ "This time we have more unique classes in the right dataset" ] }, { "cell_type": "markdown", "id": "477cbbed-1c22-4198-8e65-3ec5f805c405", "metadata": {}, "source": [ "## Modelling" ] }, { "cell_type": "markdown", "id": "eac148dd-e03e-4654-8b9b-ba3d1533eb33", "metadata": {}, "source": [ "### Preparing data" ] }, { "cell_type": "markdown", "id": "b5345867-7c2e-4727-aef4-48e1069fd82f", "metadata": {}, "source": [ "We'll be dropping duplicates as long as we need only user journey which is unique for every user ID." ] }, { "cell_type": "markdown", "id": "ee1c7090-c73c-48be-aec5-bb317d622988", "metadata": {}, "source": [ "We'll be using right dataset for training as long as it has more data." ] }, { "cell_type": "code", "execution_count": 72, "id": "17450432-f694-427c-b192-8c07b2003b21", "metadata": { "tags": [] }, "outputs": [], "source": [ "X_train = train_data_right.drop_duplicates([\"hash_id\", \"user_journey\"])\n", "X_test = train_data_left.drop_duplicates([\"hash_id\", \"user_journey\"])\n", "\n", "y_train = X_train[\"hash_id\"].values\n", "y_test = X_test[\"hash_id\"].values\n", "train_journeys = X_train[\"user_journey\"].values\n", "test_journeys = X_test[\"user_journey\"].values" ] }, { "cell_type": "markdown", "id": "29024e3f-2634-4c1e-b512-4f6ade82882e", "metadata": {}, "source": [ "### TF-IDF for user journeys" ] }, { "cell_type": "markdown", "id": "96957444-4063-472b-9ea3-5ba429747b0d", "metadata": {}, "source": [ "These are untuned parameters for TF-IDF with which I've started" ] }, { "cell_type": "code", "execution_count": 73, "id": "320d7eb2-78fb-4f5a-a16e-b1aec382a15c", "metadata": {}, "outputs": [], "source": [ "vectorizer_params = {\n", " \"ngram_range\": (1, 3),\n", " \"max_features\": 50_000,\n", " \"tokenizer\": lambda s: s.split(),\n", "}" ] }, { "cell_type": "code", "execution_count": 74, "id": "c0fae983-15fb-461e-b768-610f5b45f54f", "metadata": {}, "outputs": [], "source": [ "vectorizer = TfidfVectorizer(**vectorizer_params)\n", "X_train_tfidf = vectorizer.fit_transform(train_journeys)" ] }, { "cell_type": "code", "execution_count": 75, "id": "74ef5820-e96c-4808-8fc6-690b6fdea2df", "metadata": {}, "outputs": [], "source": [ "X_test_tfidf = vectorizer.transform(test_journeys)" ] }, { "cell_type": "markdown", "id": "8349a8dd-0327-4a73-a1b1-eb5c3edca43a", "metadata": {}, "source": [ "### Logistic Regression" ] }, { "cell_type": "code", "execution_count": 76, "id": "a9cee078-3f40-4063-9dee-cd09c8d9c732", "metadata": {}, "outputs": [], "source": [ "clf = LogisticRegression(\n", " C=1,\n", " random_state=SEED,\n", " n_jobs=-1,\n", " verbose=2,\n", " multi_class=\"multinomial\", # to solve the task like Softmax Classifier\n", " solver=\"sag\", # for faster training\n", ")" ] }, { "cell_type": "code", "execution_count": 77, "id": "03ea741b-e54a-46f2-876a-5b2608c2f80a", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 16 concurrent workers.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "convergence after 13 epochs took 7 seconds\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[Parallel(n_jobs=-1)]: Done 1 out of 1 | elapsed: 7.3s finished\n" ] }, { "data": { "text/html": [ "
LogisticRegression(C=1, multi_class='multinomial', n_jobs=-1, random_state=42,\n",
       "                   solver='sag', verbose=2)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "LogisticRegression(C=1, multi_class='multinomial', n_jobs=-1, random_state=42,\n", " solver='sag', verbose=2)" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clf.fit(X_train_tfidf, y_train)" ] }, { "cell_type": "code", "execution_count": 78, "id": "10c2c29a-6698-4302-bc66-33e709a0d904", "metadata": {}, "outputs": [], "source": [ "y_pred = clf.predict(X_test_tfidf)" ] }, { "cell_type": "code", "execution_count": 79, "id": "cb0ebe0a-be36-4f48-9507-299c1683ee63", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.8339103869653768" ] }, "execution_count": 79, "metadata": {}, "output_type": "execute_result" } ], "source": [ "precision_score(y_test, y_pred, average=\"macro\")" ] }, { "cell_type": "code", "execution_count": 80, "id": "63b63bb8-655e-4329-a53f-ce7c44f0476b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.879837067209776" ] }, "execution_count": 80, "metadata": {}, "output_type": "execute_result" } ], "source": [ "recall_score(y_test, y_pred, average=\"macro\")" ] }, { "cell_type": "markdown", "id": "781d5980-405f-43cc-a419-9f9ef264f76d", "metadata": {}, "source": [ "Pretty decent performance, huh?" ] }, { "cell_type": "markdown", "id": "903312ee-0b87-48d6-bd50-ca2dc1874ad4", "metadata": {}, "source": [ "I've tried another classifiers like KNN, Extreme Random Trees, Random Forest, but their performance is nowhere near as good as LogReg's performance." ] }, { "cell_type": "markdown", "id": "8e3a4747-d411-4c64-a261-d58521e9a4d1", "metadata": {}, "source": [ "#### Results analysis" ] }, { "cell_type": "code", "execution_count": 81, "id": "addc02cb-472a-40c4-8167-6d098cbfbb83", "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", "\n", "\n", "\n", " \n", "\n", " \n", "\n", " \n", "\n", " \n", "\n", " \n", "\n", " \n", "\n", "\n", " \n", "\n", " \n", "\n", " \n", "\n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", 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y=429\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=430\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=431\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=432\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=433\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=434\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=435\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=436\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=437\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=438\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=439\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=440\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=441\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=442\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=443\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=444\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=445\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=446\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=447\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=448\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=449\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=450\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=451\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=452\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=453\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=454\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=455\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=456\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=457\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=458\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=459\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=460\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=461\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=462\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=463\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=464\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=465\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=466\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=467\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=468\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=469\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=470\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=471\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=472\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=473\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=474\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=475\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=476\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=477\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=478\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=479\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=480\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=481\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=482\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=483\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=484\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=485\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=486\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=487\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=488\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=489\n", " \n", "\n", "\n", "top features\n", " \n", " \n", " \n", " y=490\n", " \n", "\n", "\n", "top features\n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.571\n", " \n", " 7752_19203\n", "
\n", " +0.510\n", " \n", " 7755_23103\n", "
\n", " +0.378\n", " \n", " 7755_23103 7755_23103\n", "
\n", " +0.362\n", " \n", " 7752_19203 7752_19203\n", "
\n", " +0.242\n", " \n", " 7755_23103 7752_19203\n", "
\n", " +0.242\n", " \n", " 7755_23103 7755_23103 7752_19203\n", "
\n", " +0.080\n", " \n", " 7745_1383\n", "
\n", " +0.057\n", " \n", " 7745_1383 9752_19207\n", "
\n", " +0.041\n", " \n", " 9752_19207\n", "
\n", " … 1 more positive …\n", "
\n", " … 49990 more negative …\n", "
\n", " -0.009\n", " \n", " 9752_14633\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.436\n", " \n", " 9752_836\n", "
\n", " +0.386\n", " \n", " 9752_34914\n", "
\n", " +0.227\n", " \n", " 7755_9519\n", "
\n", " +0.206\n", " \n", " 9752_34914 9752_836\n", "
\n", " +0.184\n", " \n", " 7755_9519 7755_35295\n", "
\n", " +0.178\n", " \n", " 7738_2112\n", "
\n", " +0.174\n", " \n", " 9752_836 9752_34914\n", "
\n", " +0.174\n", " \n", " 7738_6486\n", "
\n", " +0.168\n", " \n", " 7755_35295\n", "
\n", " +0.166\n", " \n", " 7755_35295 7755_9519\n", "
\n", " … 286 more positive …\n", "
\n", " … 49705 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.524\n", " \n", " 9716_61258\n", "
\n", " +0.373\n", " \n", " 7716_17211\n", "
\n", " +0.279\n", " \n", " 7716_32974\n", "
\n", " +0.250\n", " \n", " 9716_61258 7716_17211\n", "
\n", " +0.219\n", " \n", " 7716_32952\n", "
\n", " +0.208\n", " \n", " 7716_32974 9716_61258\n", "
\n", " +0.168\n", " \n", " 7752_8571\n", "
\n", " +0.138\n", " \n", " 7716_17211 9716_61258\n", "
\n", " +0.133\n", " \n", " 9716_61258 7716_32974\n", "
\n", " +0.125\n", " \n", " 7765_33462\n", "
\n", " … 364 more positive …\n", "
\n", " … 49627 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.504\n", " \n", " 9716_2265\n", "
\n", " +0.436\n", " \n", " 9701_7835\n", "
\n", " +0.401\n", " \n", " 9716_2265 9716_2265\n", "
\n", " +0.349\n", " \n", " 9701_7835 9701_7835\n", "
\n", " +0.224\n", " \n", " 9716_2265 9716_2265 9716_2265\n", "
\n", " +0.168\n", " \n", " 9752_15576\n", "
\n", " +0.156\n", " \n", " 9701_27526\n", "
\n", " +0.155\n", " \n", " 9752_15570\n", "
\n", " +0.150\n", " \n", " 9764_21896\n", "
\n", " +0.145\n", " \n", " 9007_55646\n", "
\n", " … 19 more positive …\n", "
\n", " … 49972 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.574\n", " \n", " 7755_6972\n", "
\n", " +0.278\n", " \n", " 7755_6970\n", "
\n", " +0.216\n", " \n", " 7716_62504\n", "
\n", " +0.203\n", " \n", " 7716_33248\n", "
\n", " +0.193\n", " \n", " 9716_30646\n", "
\n", " +0.175\n", " \n", " 7772_775\n", "
\n", " +0.172\n", " \n", " 7755_6970 7755_6972\n", "
\n", " +0.159\n", " \n", " 7716_21029\n", "
\n", " +0.136\n", " \n", " 7716_2460\n", "
\n", " +0.132\n", " \n", " 9716_30646 7716_62504\n", "
\n", " … 204 more positive …\n", "
\n", " … 49787 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.302\n", " \n", " 9716_31062\n", "
\n", " +0.277\n", " \n", " 9752_14642\n", "
\n", " +0.272\n", " \n", " 9752_14641\n", "
\n", " +0.241\n", " \n", " 9752_3227\n", "
\n", " +0.226\n", " \n", " 9752_14641 9752_14642\n", "
\n", " +0.204\n", " \n", " 9700_30033\n", "
\n", " +0.189\n", " \n", " 9700_30159\n", "
\n", " +0.175\n", " \n", " 7730_380 9716_31062\n", "
\n", " +0.157\n", " \n", " 7730_3507\n", "
\n", " +0.155\n", " \n", " 9716_33838\n", "
\n", " … 110 more positive …\n", "
\n", " … 49881 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.446\n", " \n", " 9700_6532\n", "
\n", " +0.329\n", " \n", " 7700_4206\n", "
\n", " +0.267\n", " \n", " 7745_46879 7745_46879\n", "
\n", " +0.267\n", " \n", " 7745_46876\n", "
\n", " +0.262\n", " \n", " 7745_46879\n", "
\n", " +0.245\n", " \n", " 5061_1930 5061_1930\n", "
\n", " +0.201\n", " \n", " 7745_46879 7745_46879 7745_46879\n", "
\n", " +0.195\n", " \n", " 5061_1930\n", "
\n", " +0.184\n", " \n", " 5061_416\n", "
\n", " +0.172\n", " \n", " 7752_180\n", "
\n", " … 49 more positive …\n", "
\n", " … 49942 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.503\n", " \n", " 9700_8631\n", "
\n", " +0.397\n", " \n", " 7700_8356\n", "
\n", " +0.367\n", " \n", " 9700_8631 7700_8356\n", "
\n", " +0.276\n", " \n", " 7700_8356 9700_8631\n", "
\n", " +0.207\n", " \n", " 7762_32120\n", "
\n", " +0.184\n", " \n", " 7700_8356 9700_8631 7700_8356\n", "
\n", " +0.184\n", " \n", " 7762_32125\n", "
\n", " +0.184\n", " \n", " 9700_8631 7700_8356 9700_8631\n", "
\n", " +0.165\n", " \n", " 7784_18225\n", "
\n", " +0.148\n", " \n", " 7700_49383\n", "
\n", " … 118 more positive …\n", "
\n", " … 49873 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.443\n", " \n", " 7752_3249\n", "
\n", " +0.428\n", " \n", " 9752_3227\n", "
\n", " +0.320\n", " \n", " 9752_3227 7752_3249\n", "
\n", " +0.302\n", " \n", " 7746_33265\n", "
\n", " +0.250\n", " \n", " 9746_35024\n", "
\n", " +0.231\n", " \n", " 7752_3249 9752_3227\n", "
\n", " +0.217\n", " \n", " 7752_3250\n", "
\n", " +0.178\n", " \n", " 7746_33265 9746_35024\n", "
\n", " +0.160\n", " \n", " 9746_35024 7746_33265\n", "
\n", " +0.124\n", " \n", " 7752_3249 9752_3227 7752_3249\n", "
\n", " … 83 more positive …\n", "
\n", " … 49908 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.393\n", " \n", " 9739_41987\n", "
\n", " +0.272\n", " \n", " 9739_9217\n", "
\n", " +0.269\n", " \n", " 9739_48386\n", "
\n", " +0.269\n", " \n", " 9739_27909\n", "
\n", " +0.240\n", " \n", " 9935_53505\n", "
\n", " +0.237\n", " \n", " 9935_53516\n", "
\n", " +0.194\n", " \n", " 9935_8449\n", "
\n", " +0.158\n", " \n", " 7752_2306\n", "
\n", " +0.125\n", " \n", " 7755_2984\n", "
\n", " +0.120\n", " \n", " 9935_53505 9935_53516\n", "
\n", " … 905 more positive …\n", "
\n", " … 49086 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.305\n", " \n", " 9701_42242\n", "
\n", " +0.281\n", " \n", " 5008_15876\n", "
\n", " +0.262\n", " \n", " 9734_30466\n", "
\n", " +0.248\n", " \n", " 9734_30486\n", "
\n", " +0.206\n", " \n", " 5005_2927\n", "
\n", " +0.195\n", " \n", " 7747_6288\n", "
\n", " +0.189\n", " \n", " 9734_30486 9734_30466\n", "
\n", " +0.182\n", " \n", " 9701_42245\n", "
\n", " +0.179\n", " \n", " 9701_46339\n", "
\n", " +0.169\n", " \n", " 7700_1152\n", "
\n", " … 483 more positive …\n", "
\n", " … 49508 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.511\n", " \n", " 9739_61700\n", "
\n", " +0.360\n", " \n", " 7755_38450\n", "
\n", " +0.278\n", " \n", " 9739_61700 7755_38450\n", "
\n", " +0.256\n", " \n", " 7755_38450 9739_61700\n", "
\n", " +0.196\n", " \n", " 9739_61700 9739_61700\n", "
\n", " +0.191\n", " \n", " 9740_28676\n", "
\n", " +0.185\n", " \n", " 9739_61700 7755_38450 9739_61700\n", "
\n", " +0.174\n", " \n", " 7715_15371\n", "
\n", " +0.167\n", " \n", " 9937_62724\n", "
\n", " +0.153\n", " \n", " 5025_65284\n", "
\n", " … 485 more positive …\n", "
\n", " … 49506 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.397\n", " \n", " 9716_1797\n", "
\n", " +0.311\n", " \n", " 9716_33026\n", "
\n", " +0.309\n", " \n", " 9916_65284\n", "
\n", " +0.252\n", " \n", " 9716_1794\n", "
\n", " +0.247\n", " \n", " 9716_30212\n", "
\n", " +0.245\n", " \n", " 9916_65322\n", "
\n", " +0.181\n", " \n", " 9916_65322 9916_65284\n", "
\n", " +0.149\n", " \n", " 9716_30209\n", "
\n", " +0.149\n", " \n", " 7752_8747\n", "
\n", " +0.144\n", " \n", " 9716_33026 9716_1797\n", "
\n", " … 889 more positive …\n", "
\n", " … 49102 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.534\n", " \n", " 7757_2258\n", "
\n", " +0.360\n", " \n", " 9937_38145\n", "
\n", " +0.334\n", " \n", " 9937_38148\n", "
\n", " +0.294\n", " \n", " 7757_1154\n", "
\n", " +0.267\n", " \n", " 9937_55810\n", "
\n", " +0.201\n", " \n", " 9757_1144\n", "
\n", " +0.160\n", " \n", " 9937_38146\n", "
\n", " +0.153\n", " \n", " 9937_38156\n", "
\n", " +0.131\n", " \n", " 9757_1146\n", "
\n", " +0.131\n", " \n", " 9937_38148 7757_2258\n", "
\n", " … 318 more positive …\n", "
\n", " … 49673 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.473\n", " \n", " 5085_27553\n", "
\n", " +0.397\n", " \n", " 7754_26705\n", "
\n", " +0.279\n", " \n", " 9700_14256\n", "
\n", " +0.265\n", " \n", " 5085_27556\n", "
\n", " +0.196\n", " \n", " 9700_14256 7754_26705\n", "
\n", " +0.164\n", " \n", " 7754_26705 9700_14256\n", "
\n", " +0.160\n", " \n", " 9754_10283\n", "
\n", " +0.159\n", " \n", " 5012_17137\n", "
\n", " +0.138\n", " \n", " 7754_26703\n", "
\n", " +0.138\n", " \n", " 5085_27553 5085_27553\n", "
\n", " … 316 more positive …\n", "
\n", " … 49675 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.483\n", " \n", " 9935_22560\n", "
\n", " +0.428\n", " \n", " 9935_22531\n", "
\n", " +0.381\n", " \n", " 9935_22560 9935_22531\n", "
\n", " +0.368\n", " \n", " 9935_22531 9935_22560\n", "
\n", " +0.248\n", " \n", " 9935_22531 9935_22560 9935_22531\n", "
\n", " +0.240\n", " \n", " 9935_22560 9935_22531 9935_22560\n", "
\n", " +0.163\n", " \n", " 7716_17265\n", "
\n", " +0.109\n", " \n", " 9935_22560 9935_22560\n", "
\n", " +0.100\n", " \n", " 9935_22531 9935_22531\n", "
\n", " +0.099\n", " \n", " 9716_61956\n", "
\n", " … 556 more positive …\n", "
\n", " … 49435 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.419\n", " \n", " 9937_37644\n", "
\n", " +0.379\n", " \n", " 9937_37633\n", "
\n", " +0.250\n", " \n", " 9937_37635\n", "
\n", " +0.244\n", " \n", " 9937_37633 9937_37644\n", "
\n", " +0.229\n", " \n", " 9739_24326\n", "
\n", " +0.221\n", " \n", " 9739_9217\n", "
\n", " +0.209\n", " \n", " 9937_37644 9937_37633\n", "
\n", " +0.158\n", " \n", " 5074_64629\n", "
\n", " +0.144\n", " \n", " 9739_24326 9739_9217\n", "
\n", " +0.128\n", " \n", " 9739_9217 9739_24326\n", "
\n", " … 656 more positive …\n", "
\n", " … 49335 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.416\n", " \n", " 5015_56952\n", "
\n", " +0.326\n", " \n", " 9752_15576\n", "
\n", " +0.290\n", " \n", " 7755_35295\n", "
\n", " +0.265\n", " \n", " 9752_15570\n", "
\n", " +0.223\n", " \n", " 5015_53391\n", "
\n", " +0.205\n", " \n", " 7755_9519\n", "
\n", " +0.195\n", " \n", " 5069_53397\n", "
\n", " +0.149\n", " \n", " 5015_56952 5069_53397\n", "
\n", " +0.149\n", " \n", " 5069_53392\n", "
\n", " +0.149\n", " \n", " 7752_15573\n", "
\n", " … 187 more positive …\n", "
\n", " … 49804 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.454\n", " \n", " 9797_12971\n", "
\n", " +0.382\n", " \n", " 7797_46515\n", "
\n", " +0.302\n", " \n", " 7797_46515 9797_12971\n", "
\n", " +0.291\n", " \n", " 9797_12971 7797_46515\n", "
\n", " +0.199\n", " \n", " 7797_46515 9797_12971 7797_46515\n", "
\n", " +0.168\n", " \n", " 9797_12971 7797_46515 9797_12971\n", "
\n", " +0.168\n", " \n", " 9797_12971 9797_12971\n", "
\n", " +0.154\n", " \n", " 7743_33033\n", "
\n", " +0.139\n", " \n", " 7797_46515 7797_46515 9797_12971\n", "
\n", " +0.132\n", " \n", " 7716_745\n", "
\n", " … 222 more positive …\n", "
\n", " … 49769 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.457\n", " \n", " 9716_37506\n", "
\n", " +0.448\n", " \n", " 9716_37501\n", "
\n", " +0.237\n", " \n", " 9716_37506 9716_37501\n", "
\n", " +0.220\n", " \n", " 9716_1841\n", "
\n", " +0.206\n", " \n", " 7716_2147\n", "
\n", " +0.187\n", " \n", " 7716_2147 9716_37506\n", "
\n", " +0.178\n", " \n", " 9742_28347\n", "
\n", " +0.174\n", " \n", " 9752_47576\n", "
\n", " +0.145\n", " \n", " 9716_37506 7716_2147\n", "
\n", " +0.145\n", " \n", " 9716_1841 9716_37501\n", "
\n", " … 164 more positive …\n", "
\n", " … 49827 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.347\n", " \n", " 7752_28340\n", "
\n", " +0.336\n", " \n", " 7742_39295\n", "
\n", " +0.328\n", " \n", " 7716_44972\n", "
\n", " +0.250\n", " \n", " 7716_44971\n", "
\n", " +0.250\n", " \n", " 7700_33799\n", "
\n", " +0.223\n", " \n", " 7746_14898\n", "
\n", " +0.194\n", " \n", " 7742_39295 7752_28340\n", "
\n", " +0.164\n", " \n", " 7752_28340 7742_39295\n", "
\n", " +0.160\n", " \n", " 7716_44972 7716_44972\n", "
\n", " +0.154\n", " \n", " 7700_4700\n", "
\n", " … 233 more positive …\n", "
\n", " … 49758 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.466\n", " \n", " 9716_62468\n", "
\n", " +0.398\n", " \n", " 9716_13059\n", "
\n", " +0.227\n", " \n", " 5031_24577\n", "
\n", " +0.211\n", " \n", " 9934_39425\n", "
\n", " +0.210\n", " \n", " 9716_25376\n", "
\n", " +0.186\n", " \n", " 9716_25347\n", "
\n", " +0.181\n", " \n", " 9716_62468 9716_13059\n", "
\n", " +0.179\n", " \n", " 9716_13059 9716_62468\n", "
\n", " +0.178\n", " \n", " 5011_12377\n", "
\n", " +0.134\n", " \n", " 9716_28673\n", "
\n", " … 655 more positive …\n", "
\n", " … 49336 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.373\n", " \n", " 7752_46005\n", "
\n", " +0.317\n", " \n", " 7716_1840\n", "
\n", " +0.243\n", " \n", " 7716_25988\n", "
\n", " +0.232\n", " \n", " 9716_6429\n", "
\n", " +0.228\n", " \n", " 9716_33844\n", "
\n", " +0.197\n", " \n", " 9752_10360\n", "
\n", " +0.193\n", " \n", " 7716_1843\n", "
\n", " +0.186\n", " \n", " 7752_10367\n", "
\n", " +0.183\n", " \n", " 7742_54601\n", "
\n", " +0.165\n", " \n", " 7752_14305\n", "
\n", " … 168 more positive …\n", "
\n", " … 49823 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.266\n", " \n", " 7755_38818\n", "
\n", " +0.246\n", " \n", " 5061_1581\n", "
\n", " +0.236\n", " \n", " 5061_1930\n", "
\n", " +0.229\n", " \n", " 5061_1588\n", "
\n", " +0.222\n", " \n", " 5061_1790\n", "
\n", " +0.206\n", " \n", " 5061_1584 5061_1588\n", "
\n", " +0.195\n", " \n", " 5061_1587\n", "
\n", " +0.177\n", " \n", " 5061_1692\n", "
\n", " +0.174\n", " \n", " 5061_1584\n", "
\n", " +0.171\n", " \n", " 5061_1693\n", "
\n", " … 121 more positive …\n", "
\n", " … 49870 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.654\n", " \n", " 7716_6434\n", "
\n", " +0.311\n", " \n", " 9716_39387\n", "
\n", " +0.299\n", " \n", " 9716_4101\n", "
\n", " +0.211\n", " \n", " 7716_6434 7716_6434\n", "
\n", " +0.159\n", " \n", " 7716_6434 9716_39387\n", "
\n", " +0.156\n", " \n", " 9716_4101 7716_6434\n", "
\n", " +0.151\n", " \n", " 7716_6434 9716_4101\n", "
\n", " +0.147\n", " \n", " 9716_39387 7716_6434\n", "
\n", " +0.143\n", " \n", " 9716_19972\n", "
\n", " +0.128\n", " \n", " 7716_3976\n", "
\n", " … 623 more positive …\n", "
\n", " … 49368 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.363\n", " \n", " 9909_39684\n", "
\n", " +0.355\n", " \n", " 9909_64769\n", "
\n", " +0.291\n", " \n", " 9935_48385\n", "
\n", " +0.285\n", " \n", " 9916_51457\n", "
\n", " +0.256\n", " \n", " 9909_39684 9909_64769\n", "
\n", " +0.236\n", " \n", " 9909_64769 9909_39684\n", "
\n", " +0.207\n", " \n", " 9716_33832\n", "
\n", " +0.149\n", " \n", " 9909_39684 9909_64769 9909_39684\n", "
\n", " +0.149\n", " \n", " 9909_12034\n", "
\n", " +0.147\n", " \n", " 9716_7172\n", "
\n", " … 689 more positive …\n", "
\n", " … 49302 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.341\n", " \n", " 9732_40196\n", "
\n", " +0.305\n", " \n", " 9916_9985\n", "
\n", " +0.271\n", " \n", " 7700_33791\n", "
\n", " +0.266\n", " \n", " 9732_40193\n", "
\n", " +0.256\n", " \n", " 9701_49156\n", "
\n", " +0.249\n", " \n", " 9916_9996\n", "
\n", " +0.205\n", " \n", " 9701_49153\n", "
\n", " +0.191\n", " \n", " 7700_33793\n", "
\n", " +0.151\n", " \n", " 9916_9987\n", "
\n", " +0.128\n", " \n", " 7755_14939\n", "
\n", " … 812 more positive …\n", "
\n", " … 49179 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.383\n", " \n", " 7743_2582\n", "
\n", " +0.281\n", " \n", " 9716_6430\n", "
\n", " +0.255\n", " \n", " 9716_1822\n", "
\n", " +0.242\n", " \n", " 9752_23293\n", "
\n", " +0.239\n", " \n", " 7716_6440\n", "
\n", " +0.204\n", " \n", " 9743_2546\n", "
\n", " +0.201\n", " \n", " 9752_980\n", "
\n", " +0.189\n", " \n", " 5048_56775\n", "
\n", " +0.189\n", " \n", " 9716_1822 9716_6430\n", "
\n", " +0.182\n", " \n", " 9743_2544\n", "
\n", " … 285 more positive …\n", "
\n", " … 49706 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.445\n", " \n", " 5033_3467\n", "
\n", " +0.333\n", " \n", " 9033_40874\n", "
\n", " +0.320\n", " \n", " 9752_509\n", "
\n", " +0.259\n", " \n", " 9033_40874 5033_3467\n", "
\n", " +0.241\n", " \n", " 7752_517\n", "
\n", " +0.191\n", " \n", " 9746_37926\n", "
\n", " +0.185\n", " \n", " 9752_509 7752_517\n", "
\n", " +0.185\n", " \n", " 5033_3467 9033_40874\n", "
\n", " +0.174\n", " \n", " 7746_31256\n", "
\n", " +0.165\n", " \n", " 9746_38504\n", "
\n", " … 175 more positive …\n", "
\n", " … 49816 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.416\n", " \n", " 7716_3669\n", "
\n", " +0.384\n", " \n", " 7755_307\n", "
\n", " +0.305\n", " \n", " 7755_4963\n", "
\n", " +0.278\n", " \n", " 7755_307 7716_3669\n", "
\n", " +0.195\n", " \n", " 7716_3669 7755_307\n", "
\n", " +0.185\n", " \n", " 7755_57579\n", "
\n", " +0.178\n", " \n", " 7755_55451\n", "
\n", " +0.174\n", " \n", " 7752_45684\n", "
\n", " +0.158\n", " \n", " 7752_8571\n", "
\n", " +0.143\n", " \n", " 7752_846\n", "
\n", " … 226 more positive …\n", "
\n", " … 49765 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.387\n", " \n", " 9794_58114\n", "
\n", " +0.365\n", " \n", " 9794_60674\n", "
\n", " +0.260\n", " \n", " 9734_30486\n", "
\n", " +0.232\n", " \n", " 9794_60694\n", "
\n", " +0.227\n", " \n", " 9734_30466 9734_30486\n", "
\n", " +0.226\n", " \n", " 9734_30486 9734_30466\n", "
\n", " +0.210\n", " \n", " 9734_30466\n", "
\n", " +0.203\n", " \n", " 9916_59905\n", "
\n", " +0.186\n", " \n", " 9734_30466 9734_30486 9734_30466\n", "
\n", " +0.170\n", " \n", " 9734_30486 9734_30466 9734_30486\n", "
\n", " … 489 more positive …\n", "
\n", " … 49502 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.465\n", " \n", " 9734_14880\n", "
\n", " +0.456\n", " \n", " 9734_14851\n", "
\n", " +0.367\n", " \n", " 9734_14880 9734_14851\n", "
\n", " +0.367\n", " \n", " 9734_14851 9734_14880\n", "
\n", " +0.283\n", " \n", " 9734_14880 9734_14851 9734_14880\n", "
\n", " +0.250\n", " \n", " 9734_14851 9734_14880 9734_14851\n", "
\n", " +0.151\n", " \n", " 9734_14880 9734_14880\n", "
\n", " +0.119\n", " \n", " 9734_14880 9734_14880 9734_14851\n", "
\n", " +0.117\n", " \n", " 9734_14851 9734_14880 9734_14880\n", "
\n", " +0.110\n", " \n", " 9734_14851 9734_14851\n", "
\n", " … 621 more positive …\n", "
\n", " … 49370 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.493\n", " \n", " 7716_39211\n", "
\n", " +0.394\n", " \n", " 9734_39958\n", "
\n", " +0.303\n", " \n", " 9701_45313\n", "
\n", " +0.196\n", " \n", " 9734_39938\n", "
\n", " +0.158\n", " \n", " 9716_65299\n", "
\n", " +0.158\n", " \n", " 9716_65298\n", "
\n", " +0.154\n", " \n", " 9701_24854\n", "
\n", " +0.154\n", " \n", " 9701_24837\n", "
\n", " +0.143\n", " \n", " 9701_24834\n", "
\n", " +0.123\n", " \n", " 7716_39211 9734_39958\n", "
\n", " … 631 more positive …\n", "
\n", " … 49360 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.385\n", " \n", " 9937_46604\n", "
\n", " +0.358\n", " \n", " 9937_46593\n", "
\n", " +0.271\n", " \n", " 9937_46604 9937_46593\n", "
\n", " +0.271\n", " \n", " 9937_46593 9937_46604\n", "
\n", " +0.226\n", " \n", " 9734_33284\n", "
\n", " +0.215\n", " \n", " 9734_33286\n", "
\n", " +0.206\n", " \n", " 9937_46604 9937_46593 9937_46604\n", "
\n", " +0.206\n", " \n", " 9937_46593 9937_46604 9937_46593\n", "
\n", " +0.171\n", " \n", " 9734_12801\n", "
\n", " +0.147\n", " \n", " 9734_12812\n", "
\n", " … 812 more positive …\n", "
\n", " … 49179 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.426\n", " \n", " 9937_43011\n", "
\n", " +0.385\n", " \n", " 9937_43040\n", "
\n", " +0.328\n", " \n", " 9937_43040 9937_43011\n", "
\n", " +0.319\n", " \n", " 9937_43011 9937_43040\n", "
\n", " +0.263\n", " \n", " 9937_43011 9937_43040 9937_43011\n", "
\n", " +0.250\n", " \n", " 9937_43040 9937_43011 9937_43040\n", "
\n", " +0.185\n", " \n", " 9716_39941\n", "
\n", " +0.175\n", " \n", " 9739_22531\n", "
\n", " +0.173\n", " \n", " 9937_34817\n", "
\n", " +0.111\n", " \n", " 9716_39941 9739_22531\n", "
\n", " … 887 more positive …\n", "
\n", " … 49104 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.456\n", " \n", " 9742_46003\n", "
\n", " +0.355\n", " \n", " 7755_19649\n", "
\n", " +0.353\n", " \n", " 9742_21276\n", "
\n", " +0.274\n", " \n", " 9742_46003 9742_21276\n", "
\n", " +0.209\n", " \n", " 9742_21276 9742_46003\n", "
\n", " +0.196\n", " \n", " 7755_19994\n", "
\n", " +0.183\n", " \n", " 9742_25658\n", "
\n", " +0.171\n", " \n", " 9742_25657\n", "
\n", " +0.157\n", " \n", " 9742_22555 9742_46003\n", "
\n", " +0.157\n", " \n", " 9742_46003 9742_21276 9742_46003\n", "
\n", " … 228 more positive …\n", "
\n", " … 49763 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.432\n", " \n", " 9734_5378\n", "
\n", " +0.382\n", " \n", " 9734_5378 9734_5398\n", "
\n", " +0.365\n", " \n", " 9734_5398 9734_5378\n", "
\n", " +0.349\n", " \n", " 9734_5398\n", "
\n", " +0.300\n", " \n", " 9734_5398 9734_5378 9734_5398\n", "
\n", " +0.294\n", " \n", " 9734_5378 9734_5398 9734_5378\n", "
\n", " +0.124\n", " \n", " 9734_12801\n", "
\n", " +0.111\n", " \n", " 7716_3252\n", "
\n", " +0.102\n", " \n", " 9734_33283\n", "
\n", " +0.088\n", " \n", " 9734_12801 9734_5378\n", "
\n", " … 935 more positive …\n", "
\n", " … 49056 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.518\n", " \n", " 9716_26295\n", "
\n", " +0.322\n", " \n", " 7755_33269\n", "
\n", " +0.298\n", " \n", " 7755_33269 9716_26295\n", "
\n", " +0.284\n", " \n", " 9716_26295 7755_33269\n", "
\n", " +0.258\n", " \n", " 9953_37016\n", "
\n", " +0.203\n", " \n", " 9716_31989\n", "
\n", " +0.176\n", " \n", " 7755_33269 9716_26295 7755_33269\n", "
\n", " +0.157\n", " \n", " 9953_37016 9716_26295\n", "
\n", " +0.149\n", " \n", " 9716_26295 7755_33269 9716_26295\n", "
\n", " +0.142\n", " \n", " 9716_26295 9953_37016\n", "
\n", " … 184 more positive …\n", "
\n", " … 49807 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.353\n", " \n", " 9716_15875\n", "
\n", " +0.323\n", " \n", " 9736_48386\n", "
\n", " +0.312\n", " \n", " 9736_48406\n", "
\n", " +0.298\n", " \n", " 9716_15904\n", "
\n", " +0.240\n", " \n", " 9716_50689\n", "
\n", " +0.238\n", " \n", " 9736_48406 9736_48386\n", "
\n", " +0.234\n", " \n", " 9736_48386 9736_48406\n", "
\n", " +0.171\n", " \n", " 9736_27137\n", "
\n", " +0.145\n", " \n", " 9716_15875 9716_15904\n", "
\n", " +0.141\n", " \n", " 9716_15875 9716_50689\n", "
\n", " … 758 more positive …\n", "
\n", " … 49233 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.346\n", " \n", " 5061_10365\n", "
\n", " +0.261\n", " \n", " 5061_1731\n", "
\n", " +0.258\n", " \n", " 5061_1777\n", "
\n", " +0.224\n", " \n", " 7772_1255\n", "
\n", " +0.217\n", " \n", " 5061_960\n", "
\n", " +0.194\n", " \n", " 7772_101\n", "
\n", " +0.169\n", " \n", " 5061_1631\n", "
\n", " +0.169\n", " \n", " 5061_1779\n", "
\n", " +0.166\n", " \n", " 7730_2745\n", "
\n", " +0.160\n", " \n", " 5061_1721\n", "
\n", " … 119 more positive …\n", "
\n", " … 49872 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.610\n", " \n", " 7716_60475\n", "
\n", " +0.281\n", " \n", " 9716_32507\n", "
\n", " +0.276\n", " \n", " 7716_60475 7716_60475\n", "
\n", " +0.268\n", " \n", " 9716_31427\n", "
\n", " +0.245\n", " \n", " 9716_31427 7716_60475\n", "
\n", " +0.243\n", " \n", " 7716_60475 9716_31427\n", "
\n", " +0.201\n", " \n", " 9716_32507 7716_60475\n", "
\n", " +0.201\n", " \n", " 7716_60475 9716_32507\n", "
\n", " +0.140\n", " \n", " 7716_60475 9716_31427 7716_60475\n", "
\n", " +0.129\n", " \n", " 7716_60475 7716_60475 9716_31427\n", "
\n", " … 174 more positive …\n", "
\n", " … 49817 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.477\n", " \n", " 9716_17232\n", "
\n", " +0.319\n", " \n", " 5018_60001\n", "
\n", " +0.319\n", " \n", " 5022_51696\n", "
\n", " +0.265\n", " \n", " 9716_17232 9716_17232\n", "
\n", " +0.247\n", " \n", " 9752_870\n", "
\n", " +0.192\n", " \n", " 5018_50832\n", "
\n", " +0.180\n", " \n", " 9754_12579\n", "
\n", " +0.167\n", " \n", " 9716_31063\n", "
\n", " +0.128\n", " \n", " 5022_9923\n", "
\n", " +0.128\n", " \n", " 9754_46662\n", "
\n", " … 131 more positive …\n", "
\n", " … 49860 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.554\n", " \n", " 7701_4998\n", "
\n", " +0.484\n", " \n", " 7701_4998 7701_4998\n", "
\n", " +0.415\n", " \n", " 7701_4998 7701_4998 7701_4998\n", "
\n", " +0.245\n", " \n", " 7716_32952\n", "
\n", " +0.195\n", " \n", " 7787_44160\n", "
\n", " +0.119\n", " \n", " 7799_2566\n", "
\n", " +0.098\n", " \n", " 7716_61255\n", "
\n", " +0.086\n", " \n", " 9716_61253\n", "
\n", " +0.079\n", " \n", " 7752_6246\n", "
\n", " +0.071\n", " \n", " 7730_460\n", "
\n", " … 50 more positive …\n", "
\n", " … 49941 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.562\n", " \n", " 7754_2891\n", "
\n", " +0.366\n", " \n", " 7700_801\n", "
\n", " +0.296\n", " \n", " 9701_2817\n", "
\n", " +0.176\n", " \n", " 9716_1797\n", "
\n", " +0.173\n", " \n", " 9016_50311\n", "
\n", " +0.166\n", " \n", " 9754_1671\n", "
\n", " +0.155\n", " \n", " 5016_5566\n", "
\n", " +0.143\n", " \n", " 9701_40451\n", "
\n", " +0.142\n", " \n", " 7754_2891 7700_801\n", "
\n", " +0.127\n", " \n", " 7754_2891 7754_2891\n", "
\n", " … 557 more positive …\n", "
\n", " … 49434 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.378\n", " \n", " 9916_42753\n", "
\n", " +0.331\n", " \n", " 9916_42764\n", "
\n", " +0.307\n", " \n", " 5047_12545\n", "
\n", " +0.292\n", " \n", " 9916_42753 9916_42764\n", "
\n", " +0.268\n", " \n", " 9916_42764 9916_42753\n", "
\n", " +0.242\n", " \n", " 9916_42753 9916_42764 9916_42753\n", "
\n", " +0.231\n", " \n", " 9916_42764 9916_42753 9916_42764\n", "
\n", " +0.193\n", " \n", " 5047_45313\n", "
\n", " +0.186\n", " \n", " 5032_7579\n", "
\n", " +0.164\n", " \n", " 9031_5132\n", "
\n", " … 630 more positive …\n", "
\n", " … 49361 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.399\n", " \n", " 9716_3841\n", "
\n", " +0.292\n", " \n", " 9716_50689\n", "
\n", " +0.289\n", " \n", " 9937_32260\n", "
\n", " +0.286\n", " \n", " 9790_59393\n", "
\n", " +0.240\n", " \n", " 9716_3841 9716_50689\n", "
\n", " +0.228\n", " \n", " 9716_50689 9716_3841\n", "
\n", " +0.195\n", " \n", " 9790_38916\n", "
\n", " +0.187\n", " \n", " 7716_49282\n", "
\n", " +0.159\n", " \n", " 9716_4102\n", "
\n", " +0.152\n", " \n", " 9942_15873\n", "
\n", " … 861 more positive …\n", "
\n", " … 49130 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.623\n", " \n", " 9935_14850\n", "
\n", " +0.357\n", " \n", " 9752_10502\n", "
\n", " +0.319\n", " \n", " 9752_10502 9935_14850\n", "
\n", " +0.310\n", " \n", " 9935_14850 9752_10502\n", "
\n", " +0.220\n", " \n", " 9935_14850 9935_14850\n", "
\n", " +0.195\n", " \n", " 9935_14850 9752_10502 9935_14850\n", "
\n", " +0.163\n", " \n", " 9752_10502 9935_14850 9752_10502\n", "
\n", " +0.131\n", " \n", " 9716_55558\n", "
\n", " +0.127\n", " \n", " 9752_10507\n", "
\n", " +0.120\n", " \n", " 9935_14850 9935_14850 9752_10502\n", "
\n", " … 363 more positive …\n", "
\n", " … 49628 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.444\n", " \n", " 7752_7903\n", "
\n", " +0.381\n", " \n", " 9934_8963\n", "
\n", " +0.321\n", " \n", " 9916_1794\n", "
\n", " +0.312\n", " \n", " 9916_1796\n", "
\n", " +0.210\n", " \n", " 9916_1814\n", "
\n", " +0.192\n", " \n", " 9734_16641\n", "
\n", " +0.180\n", " \n", " 7752_49241\n", "
\n", " +0.130\n", " \n", " 7752_7903 9934_8963\n", "
\n", " +0.126\n", " \n", " 9934_8961\n", "
\n", " +0.126\n", " \n", " 7752_7904\n", "
\n", " … 838 more positive …\n", "
\n", " … 49153 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.339\n", " \n", " 9900_64001\n", "
\n", " +0.318\n", " \n", " 9900_64012\n", "
\n", " +0.263\n", " \n", " 9716_33093\n", "
\n", " +0.263\n", " \n", " 9734_48386\n", "
\n", " +0.260\n", " \n", " 9734_48406\n", "
\n", " +0.212\n", " \n", " 9900_64012 9900_64001\n", "
\n", " +0.198\n", " \n", " 9900_64001 9900_64012\n", "
\n", " +0.146\n", " \n", " 9734_48388\n", "
\n", " +0.131\n", " \n", " 9900_64012 9900_64001 9900_64012\n", "
\n", " +0.130\n", " \n", " 9734_30467\n", "
\n", " … 714 more positive …\n", "
\n", " … 49277 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.361\n", " \n", " 9739_52741\n", "
\n", " +0.332\n", " \n", " 9934_32257\n", "
\n", " +0.318\n", " \n", " 9739_52738\n", "
\n", " +0.260\n", " \n", " 9739_52758\n", "
\n", " +0.172\n", " \n", " 9739_52741 9739_52738\n", "
\n", " +0.172\n", " \n", " 9916_20993\n", "
\n", " +0.155\n", " \n", " 5010_54991\n", "
\n", " +0.146\n", " \n", " 9739_52738 9739_52741\n", "
\n", " +0.139\n", " \n", " 9916_55809\n", "
\n", " +0.126\n", " \n", " 9074_48900\n", "
\n", " … 922 more positive …\n", "
\n", " … 49069 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.513\n", " \n", " 9916_20226\n", "
\n", " +0.460\n", " \n", " 9916_20246\n", "
\n", " +0.345\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.340\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.252\n", " \n", " 9916_20226 9916_20246 9916_20226\n", "
\n", " +0.241\n", " \n", " 9916_20246 9916_20226 9916_20246\n", "
\n", " +0.097\n", " \n", " 9916_15884\n", "
\n", " +0.097\n", " \n", " 9916_20226 9916_20226\n", "
\n", " +0.092\n", " \n", " 9916_20246 9916_20246\n", "
\n", " +0.079\n", " \n", " 9716_28684\n", "
\n", " … 660 more positive …\n", "
\n", " … 49331 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.503\n", " \n", " 9935_63776\n", "
\n", " +0.468\n", " \n", " 9935_63747\n", "
\n", " +0.337\n", " \n", " 9935_63776 9935_63747\n", "
\n", " +0.336\n", " \n", " 9935_63747 9935_63776\n", "
\n", " +0.218\n", " \n", " 9935_63776 9935_63747 9935_63776\n", "
\n", " +0.205\n", " \n", " 9935_63747 9935_63776 9935_63747\n", "
\n", " +0.166\n", " \n", " 9935_63750\n", "
\n", " +0.102\n", " \n", " 9935_63776 9935_63776\n", "
\n", " +0.099\n", " \n", " 9935_59916\n", "
\n", " +0.088\n", " \n", " 9734_5388\n", "
\n", " … 731 more positive …\n", "
\n", " … 49260 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.370\n", " \n", " 7716_55676\n", "
\n", " +0.346\n", " \n", " 7716_31789\n", "
\n", " +0.333\n", " \n", " 7757_2653\n", "
\n", " +0.272\n", " \n", " 9953_6544\n", "
\n", " +0.211\n", " \n", " 7746_6550\n", "
\n", " +0.204\n", " \n", " 9746_16330\n", "
\n", " +0.178\n", " \n", " 5022_19797\n", "
\n", " +0.175\n", " \n", " 9757_2637\n", "
\n", " +0.159\n", " \n", " 9953_6544 7716_55676\n", "
\n", " +0.158\n", " \n", " 5022_19797 5022_19797\n", "
\n", " … 133 more positive …\n", "
\n", " … 49858 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.336\n", " \n", " 5025_57348\n", "
\n", " +0.261\n", " \n", " 9776_35331\n", "
\n", " +0.259\n", " \n", " 7752_762\n", "
\n", " +0.207\n", " \n", " 9776_35360\n", "
\n", " +0.200\n", " \n", " 9916_52225\n", "
\n", " +0.192\n", " \n", " 9041_278\n", "
\n", " +0.162\n", " \n", " 7752_6247\n", "
\n", " +0.161\n", " \n", " 9734_33312\n", "
\n", " +0.159\n", " \n", " 9041_37142\n", "
\n", " +0.149\n", " \n", " 9916_52229\n", "
\n", " … 742 more positive …\n", "
\n", " … 49249 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.406\n", " \n", " 9937_55328\n", "
\n", " +0.396\n", " \n", " 9937_55299\n", "
\n", " +0.376\n", " \n", " 9937_55299 9937_55328\n", "
\n", " +0.373\n", " \n", " 9937_55328 9937_55299\n", "
\n", " +0.304\n", " \n", " 9937_55328 9937_55299 9937_55328\n", "
\n", " +0.279\n", " \n", " 9937_55299 9937_55328 9937_55299\n", "
\n", " +0.245\n", " \n", " 9732_63233\n", "
\n", " +0.135\n", " \n", " 9732_61187\n", "
\n", " +0.094\n", " \n", " 9732_61187 9732_63233\n", "
\n", " +0.091\n", " \n", " 9937_55299 9937_55299\n", "
\n", " … 571 more positive …\n", "
\n", " … 49420 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.534\n", " \n", " 5018_19769\n", "
\n", " +0.321\n", " \n", " 7752_1389\n", "
\n", " +0.229\n", " \n", " 9916_15876\n", "
\n", " +0.191\n", " \n", " 5018_19766\n", "
\n", " +0.190\n", " \n", " 5018_19762\n", "
\n", " +0.179\n", " \n", " 9011_35074\n", "
\n", " +0.155\n", " \n", " 7759_30123\n", "
\n", " +0.143\n", " \n", " 9047_42303\n", "
\n", " +0.137\n", " \n", " 9716_7180\n", "
\n", " +0.136\n", " \n", " 7752_1388\n", "
\n", " … 167 more positive …\n", "
\n", " … 49824 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.626\n", " \n", " 7755_33346\n", "
\n", " +0.258\n", " \n", " 9752_14633\n", "
\n", " +0.235\n", " \n", " 9700_8607\n", "
\n", " +0.219\n", " \n", " 7755_33346 7755_33346\n", "
\n", " +0.209\n", " \n", " 7755_38846 7755_33346\n", "
\n", " +0.193\n", " \n", " 7755_38846\n", "
\n", " +0.136\n", " \n", " 9700_13319\n", "
\n", " +0.134\n", " \n", " 7755_33346 9700_30157\n", "
\n", " +0.132\n", " \n", " 7755_35296\n", "
\n", " +0.131\n", " \n", " 9752_14633 9700_8607\n", "
\n", " … 121 more positive …\n", "
\n", " … 49870 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.429\n", " \n", " 7755_35295\n", "
\n", " +0.422\n", " \n", " 7755_14939\n", "
\n", " +0.286\n", " \n", " 7755_33344\n", "
\n", " +0.254\n", " \n", " 7755_14939 7755_33344\n", "
\n", " +0.239\n", " \n", " 7755_14939 7755_35295\n", "
\n", " +0.228\n", " \n", " 7755_35295 7755_14939\n", "
\n", " +0.227\n", " \n", " 7755_35888\n", "
\n", " +0.148\n", " \n", " 7755_33346\n", "
\n", " +0.141\n", " \n", " 7755_35295 7755_14939 7755_33344\n", "
\n", " +0.141\n", " \n", " 7755_35888 7755_14939\n", "
\n", " … 155 more positive …\n", "
\n", " … 49836 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.419\n", " \n", " 9716_33842\n", "
\n", " +0.302\n", " \n", " 9716_33847\n", "
\n", " +0.279\n", " \n", " 9716_33842 9716_33842\n", "
\n", " +0.253\n", " \n", " 9716_33842 9716_33842 9716_33842\n", "
\n", " +0.242\n", " \n", " 9716_6428\n", "
\n", " +0.226\n", " \n", " 9752_12947\n", "
\n", " +0.207\n", " \n", " 7730_3803\n", "
\n", " +0.202\n", " \n", " 9752_14633 9752_12947\n", "
\n", " +0.180\n", " \n", " 7730_3803 7730_3507\n", "
\n", " +0.161\n", " \n", " 7755_15802\n", "
\n", " … 88 more positive …\n", "
\n", " … 49903 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.456\n", " \n", " 7755_861\n", "
\n", " +0.433\n", " \n", " 7752_3251\n", "
\n", " +0.232\n", " \n", " 7755_36181\n", "
\n", " +0.223\n", " \n", " 7755_863\n", "
\n", " +0.206\n", " \n", " 7752_3251 9752_2903\n", "
\n", " +0.180\n", " \n", " 7760_36465\n", "
\n", " +0.178\n", " \n", " 7752_5130\n", "
\n", " +0.166\n", " \n", " 9752_2903\n", "
\n", " +0.165\n", " \n", " 7760_56271\n", "
\n", " +0.159\n", " \n", " 7755_865\n", "
\n", " … 144 more positive …\n", "
\n", " … 49847 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.383\n", " \n", " 9746_31872\n", "
\n", " +0.315\n", " \n", " 7746_1772\n", "
\n", " +0.260\n", " \n", " 9758_17184\n", "
\n", " +0.207\n", " \n", " 9716_19990\n", "
\n", " +0.206\n", " \n", " 9758_28166\n", "
\n", " +0.162\n", " \n", " 9902_52748\n", "
\n", " +0.162\n", " \n", " 9758_28192\n", "
\n", " +0.162\n", " \n", " 9758_17155\n", "
\n", " +0.161\n", " \n", " 9716_19970\n", "
\n", " +0.145\n", " \n", " 9754_12576\n", "
\n", " … 807 more positive …\n", "
\n", " … 49184 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.371\n", " \n", " 9734_12801\n", "
\n", " +0.314\n", " \n", " 9734_12812\n", "
\n", " +0.258\n", " \n", " 9734_12812 9734_12801\n", "
\n", " +0.253\n", " \n", " 9734_12801 9734_12812\n", "
\n", " +0.231\n", " \n", " 9734_12812 9734_12801 9734_12812\n", "
\n", " +0.226\n", " \n", " 9916_65026\n", "
\n", " +0.220\n", " \n", " 9916_65046\n", "
\n", " +0.220\n", " \n", " 9734_12801 9734_12812 9734_12801\n", "
\n", " +0.159\n", " \n", " 9734_33281\n", "
\n", " +0.144\n", " \n", " 9916_65046 9916_65026\n", "
\n", " … 925 more positive …\n", "
\n", " … 49066 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.474\n", " \n", " 9935_44292\n", "
\n", " +0.459\n", " \n", " 7752_2306\n", "
\n", " +0.301\n", " \n", " 7752_2306 9935_44292\n", "
\n", " +0.282\n", " \n", " 9935_44292 7752_2306\n", "
\n", " +0.254\n", " \n", " 9935_8449\n", "
\n", " +0.164\n", " \n", " 7752_2306 9935_44292 7752_2306\n", "
\n", " +0.156\n", " \n", " 9935_44292 7752_2306 9935_44292\n", "
\n", " +0.132\n", " \n", " 9732_39172\n", "
\n", " +0.122\n", " \n", " 9935_8449 9935_44292\n", "
\n", " +0.113\n", " \n", " 9935_44292 9935_8449\n", "
\n", " … 368 more positive …\n", "
\n", " … 49623 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.473\n", " \n", " 9934_56321\n", "
\n", " +0.361\n", " \n", " 9934_35846\n", "
\n", " +0.334\n", " \n", " 9934_35843\n", "
\n", " +0.269\n", " \n", " 7752_3622\n", "
\n", " +0.235\n", " \n", " 9934_52225\n", "
\n", " +0.212\n", " \n", " 9934_52236\n", "
\n", " +0.167\n", " \n", " 9934_35843 9934_35846\n", "
\n", " +0.161\n", " \n", " 9934_35846 9934_35843\n", "
\n", " +0.157\n", " \n", " 9934_35872\n", "
\n", " +0.143\n", " \n", " 7752_36201\n", "
\n", " … 637 more positive …\n", "
\n", " … 49354 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.650\n", " \n", " 9005_44856\n", "
\n", " +0.325\n", " \n", " 9026_41063\n", "
\n", " +0.325\n", " \n", " 9026_49321\n", "
\n", " +0.217\n", " \n", " 9026_49321 9005_44856\n", "
\n", " +0.217\n", " \n", " 9026_41063 9005_44856\n", "
\n", " +0.208\n", " \n", " 9005_44856 9026_49321\n", "
\n", " +0.192\n", " \n", " 9005_44856 9026_41063\n", "
\n", " +0.150\n", " \n", " 9005_44856 9026_49321 9005_44856\n", "
\n", " +0.108\n", " \n", " 9005_44856 9026_41063 9005_44856\n", "
\n", " +0.108\n", " \n", " 9005_44856 9005_44856\n", "
\n", " … 76 more positive …\n", "
\n", " … 49915 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.374\n", " \n", " 9909_50689\n", "
\n", " +0.356\n", " \n", " 9909_50700\n", "
\n", " +0.289\n", " \n", " 9937_59404\n", "
\n", " +0.246\n", " \n", " 9937_59393\n", "
\n", " +0.192\n", " \n", " 9909_50689 9909_50700\n", "
\n", " +0.184\n", " \n", " 9937_59393 9937_59404\n", "
\n", " +0.174\n", " \n", " 9909_50700 9909_50689\n", "
\n", " +0.172\n", " \n", " 9937_59404 9937_59393\n", "
\n", " +0.166\n", " \n", " 9734_37633\n", "
\n", " +0.145\n", " \n", " 9734_61702\n", "
\n", " … 785 more positive …\n", "
\n", " … 49206 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.378\n", " \n", " 9732_27138\n", "
\n", " +0.370\n", " \n", " 9732_27138 9732_27158\n", "
\n", " +0.368\n", " \n", " 9732_27158 9732_27138\n", "
\n", " +0.348\n", " \n", " 9732_27158\n", "
\n", " +0.293\n", " \n", " 9732_27158 9732_27138 9732_27158\n", "
\n", " +0.293\n", " \n", " 9732_27138 9732_27158 9732_27138\n", "
\n", " +0.173\n", " \n", " 9754_43521\n", "
\n", " +0.173\n", " \n", " 9732_27141\n", "
\n", " +0.169\n", " \n", " 9754_43532\n", "
\n", " +0.121\n", " \n", " 9754_43532 9754_43521\n", "
\n", " … 665 more positive …\n", "
\n", " … 49326 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.392\n", " \n", " 7700_6190\n", "
\n", " +0.370\n", " \n", " 9701_64772\n", "
\n", " +0.275\n", " \n", " 7700_6191\n", "
\n", " +0.202\n", " \n", " 9701_24864\n", "
\n", " +0.184\n", " \n", " 9701_14082\n", "
\n", " +0.179\n", " \n", " 9701_45314\n", "
\n", " +0.177\n", " \n", " 9701_14102\n", "
\n", " +0.177\n", " \n", " 9900_26625\n", "
\n", " +0.159\n", " \n", " 9701_24835\n", "
\n", " +0.154\n", " \n", " 9701_64780\n", "
\n", " … 578 more positive …\n", "
\n", " … 49413 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.566\n", " \n", " 7700_5871\n", "
\n", " +0.390\n", " \n", " 7700_55154\n", "
\n", " +0.216\n", " \n", " 9934_27137\n", "
\n", " +0.212\n", " \n", " 9732_27137\n", "
\n", " +0.160\n", " \n", " 9732_27148\n", "
\n", " +0.148\n", " \n", " 9934_27137 5050_16641\n", "
\n", " +0.147\n", " \n", " 9934_29445\n", "
\n", " +0.146\n", " \n", " 7700_55154 7700_5871\n", "
\n", " +0.136\n", " \n", " 7700_5871 7700_55154\n", "
\n", " +0.136\n", " \n", " 5050_16641\n", "
\n", " … 379 more positive …\n", "
\n", " … 49612 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.348\n", " \n", " 9716_1797\n", "
\n", " +0.308\n", " \n", " 9716_43778\n", "
\n", " +0.185\n", " \n", " 9913_45846\n", "
\n", " +0.179\n", " \n", " 9701_42242\n", "
\n", " +0.159\n", " \n", " 9913_45826\n", "
\n", " +0.158\n", " \n", " 9716_1796\n", "
\n", " +0.147\n", " \n", " 9716_64516\n", "
\n", " +0.136\n", " \n", " 9735_13059\n", "
\n", " +0.134\n", " \n", " 9735_13088\n", "
\n", " +0.130\n", " \n", " 9716_43778 9716_1797\n", "
\n", " … 1012 more positive …\n", "
\n", " … 48979 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.539\n", " \n", " 9935_53505\n", "
\n", " +0.519\n", " \n", " 9935_8449\n", "
\n", " +0.325\n", " \n", " 9935_8449 9935_53505\n", "
\n", " +0.316\n", " \n", " 9935_53505 9935_8449\n", "
\n", " +0.183\n", " \n", " 9935_53505 9935_8449 9935_53505\n", "
\n", " +0.182\n", " \n", " 9935_8449 9935_53505 9935_8449\n", "
\n", " +0.143\n", " \n", " 9935_8449 9935_8449\n", "
\n", " +0.133\n", " \n", " 9935_53516\n", "
\n", " +0.128\n", " \n", " 9935_53505 9935_53505\n", "
\n", " +0.109\n", " \n", " 9935_8449 9935_53505 9935_53505\n", "
\n", " … 512 more positive …\n", "
\n", " … 49479 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.607\n", " \n", " 7746_31431\n", "
\n", " +0.337\n", " \n", " 7716_65294\n", "
\n", " +0.256\n", " \n", " 7716_902\n", "
\n", " +0.255\n", " \n", " 7716_2268\n", "
\n", " +0.224\n", " \n", " 7746_31431 7746_31431\n", "
\n", " +0.184\n", " \n", " 7716_65294 7746_31431\n", "
\n", " +0.181\n", " \n", " 7746_31431 7716_65294\n", "
\n", " +0.178\n", " \n", " 7746_31431 7716_902\n", "
\n", " +0.173\n", " \n", " 7746_31431 7716_2268\n", "
\n", " +0.165\n", " \n", " 7716_2268 7746_31431\n", "
\n", " … 327 more positive …\n", "
\n", " … 49664 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.511\n", " \n", " 7716_44974\n", "
\n", " +0.252\n", " \n", " 5091_64313\n", "
\n", " +0.242\n", " \n", " 9091_52009\n", "
\n", " +0.227\n", " \n", " 9716_33092\n", "
\n", " +0.222\n", " \n", " 9716_33092 7716_44974\n", "
\n", " +0.199\n", " \n", " 7716_44974 9716_33092\n", "
\n", " +0.186\n", " \n", " 9716_33093\n", "
\n", " +0.163\n", " \n", " 9091_52009 5091_64313\n", "
\n", " +0.160\n", " \n", " 7752_21238\n", "
\n", " +0.158\n", " \n", " 5091_64313 9091_52009\n", "
\n", " … 452 more positive …\n", "
\n", " … 49539 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.495\n", " \n", " 9716_3151\n", "
\n", " +0.490\n", " \n", " 7716_3161\n", "
\n", " +0.268\n", " \n", " 9716_3151 7716_3161\n", "
\n", " +0.259\n", " \n", " 7716_3161 9716_3151\n", "
\n", " +0.220\n", " \n", " 7716_3161 7716_3161\n", "
\n", " +0.171\n", " \n", " 9716_3151 9716_3151\n", "
\n", " +0.153\n", " \n", " 9934_56076\n", "
\n", " +0.141\n", " \n", " 7716_3161 9716_3151 7716_3161\n", "
\n", " +0.126\n", " \n", " 9716_3151 7716_3161 9716_3151\n", "
\n", " +0.126\n", " \n", " 9716_3151 7716_3161 7716_3161\n", "
\n", " … 601 more positive …\n", "
\n", " … 49390 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.594\n", " \n", " 5024_42692\n", "
\n", " +0.490\n", " \n", " 9024_63888\n", "
\n", " +0.200\n", " \n", " 5024_42692 5024_42692\n", "
\n", " +0.190\n", " \n", " 9024_63888 5024_42692\n", "
\n", " +0.179\n", " \n", " 7752_15944\n", "
\n", " +0.175\n", " \n", " 5024_42692 9024_63888\n", "
\n", " +0.172\n", " \n", " 9024_63891\n", "
\n", " +0.172\n", " \n", " 5024_7820\n", "
\n", " +0.154\n", " \n", " 9024_42697\n", "
\n", " +0.147\n", " \n", " 9024_63888 9024_63888\n", "
\n", " … 448 more positive …\n", "
\n", " … 49543 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.397\n", " \n", " 5061_1930\n", "
\n", " +0.289\n", " \n", " 7760_46585\n", "
\n", " +0.286\n", " \n", " 5061_1693\n", "
\n", " +0.222\n", " \n", " 5061_1690\n", "
\n", " +0.186\n", " \n", " 5061_414\n", "
\n", " +0.186\n", " \n", " 5061_1930 5061_1930\n", "
\n", " +0.184\n", " \n", " 7755_30220\n", "
\n", " +0.180\n", " \n", " 5061_1187\n", "
\n", " +0.166\n", " \n", " 5061_1928\n", "
\n", " +0.163\n", " \n", " 5061_1171\n", "
\n", " … 73 more positive …\n", "
\n", " … 49918 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.580\n", " \n", " 9716_31987\n", "
\n", " +0.346\n", " \n", " 9716_31987 9716_31987\n", "
\n", " +0.252\n", " \n", " 9752_31489\n", "
\n", " +0.230\n", " \n", " 9752_14633 9752_31489\n", "
\n", " +0.201\n", " \n", " 7755_38846 9716_33847\n", "
\n", " +0.180\n", " \n", " 9752_31489 9700_8601\n", "
\n", " +0.168\n", " \n", " 9716_31987 9716_31987 7755_15806\n", "
\n", " +0.168\n", " \n", " 9716_31986 9716_31987\n", "
\n", " +0.168\n", " \n", " 9716_31987 7755_15806\n", "
\n", " +0.159\n", " \n", " 9716_33847\n", "
\n", " … 100 more positive …\n", "
\n", " … 49891 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.447\n", " \n", " 7753_62669\n", "
\n", " +0.409\n", " \n", " 7716_3579\n", "
\n", " +0.343\n", " \n", " 7753_6136\n", "
\n", " +0.312\n", " \n", " 7716_3579 7753_62669\n", "
\n", " +0.306\n", " \n", " 7753_62669 7716_3579\n", "
\n", " +0.181\n", " \n", " 7716_3579 7753_62669 7716_3579\n", "
\n", " +0.152\n", " \n", " 7753_62669 7716_3579 7753_62669\n", "
\n", " +0.143\n", " \n", " 7716_3579 7753_6136\n", "
\n", " +0.138\n", " \n", " 7753_6136 7716_3579\n", "
\n", " +0.125\n", " \n", " 7716_3579 7716_3579\n", "
\n", " … 358 more positive …\n", "
\n", " … 49633 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.650\n", " \n", " 7755_306\n", "
\n", " +0.321\n", " \n", " 7755_37277\n", "
\n", " +0.243\n", " \n", " 7755_37277 7755_306\n", "
\n", " +0.225\n", " \n", " 7755_306 7755_37277\n", "
\n", " +0.224\n", " \n", " 7755_306 7755_306\n", "
\n", " +0.215\n", " \n", " 7755_32043\n", "
\n", " +0.189\n", " \n", " 7755_32043 7755_306\n", "
\n", " +0.150\n", " \n", " 7755_26527\n", "
\n", " +0.140\n", " \n", " 7755_306 7755_32043\n", "
\n", " +0.125\n", " \n", " 7755_306 7755_37277 7755_306\n", "
\n", " … 168 more positive …\n", "
\n", " … 49823 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.424\n", " \n", " 9739_24322\n", "
\n", " +0.377\n", " \n", " 9739_23809\n", "
\n", " +0.355\n", " \n", " 9739_24325\n", "
\n", " +0.320\n", " \n", " 9739_24342\n", "
\n", " +0.226\n", " \n", " 9739_24322 9739_24342\n", "
\n", " +0.219\n", " \n", " 9739_24342 9739_24322\n", "
\n", " +0.158\n", " \n", " 9739_24322 9739_24342 9739_24322\n", "
\n", " +0.148\n", " \n", " 9739_24325 9739_23809\n", "
\n", " +0.143\n", " \n", " 9739_23809 9739_24325\n", "
\n", " +0.133\n", " \n", " 9916_55809\n", "
\n", " … 814 more positive …\n", "
\n", " … 49177 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.383\n", " \n", " 9937_19717\n", "
\n", " +0.346\n", " \n", " 9937_19714\n", "
\n", " +0.346\n", " \n", " 9937_40194\n", "
\n", " +0.283\n", " \n", " 9716_19974\n", "
\n", " +0.243\n", " \n", " 9937_19734\n", "
\n", " +0.168\n", " \n", " 9937_40194 9937_19717\n", "
\n", " +0.168\n", " \n", " 9937_19717 9937_40194\n", "
\n", " +0.135\n", " \n", " 9736_55052\n", "
\n", " +0.133\n", " \n", " 9937_19717 9937_19714\n", "
\n", " +0.133\n", " \n", " 9716_19973\n", "
\n", " … 756 more positive …\n", "
\n", " … 49235 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.381\n", " \n", " 9916_2305\n", "
\n", " +0.374\n", " \n", " 9916_2316\n", "
\n", " +0.280\n", " \n", " 9716_7172\n", "
\n", " +0.262\n", " \n", " 9916_2305 9916_2316\n", "
\n", " +0.254\n", " \n", " 9916_2316 9916_2305\n", "
\n", " +0.196\n", " \n", " 9716_7173 9716_7172\n", "
\n", " +0.194\n", " \n", " 9916_2316 9916_2305 9916_2316\n", "
\n", " +0.194\n", " \n", " 9916_2305 9916_2316 9916_2305\n", "
\n", " +0.194\n", " \n", " 9716_7172 9716_7173\n", "
\n", " +0.168\n", " \n", " 9716_7172 9716_7173 9716_7172\n", "
\n", " … 900 more positive …\n", "
\n", " … 49091 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.419\n", " \n", " 9739_24324\n", "
\n", " +0.378\n", " \n", " 9739_41985\n", "
\n", " +0.234\n", " \n", " 9739_24332\n", "
\n", " +0.205\n", " \n", " 9916_20236\n", "
\n", " +0.198\n", " \n", " 9916_20225\n", "
\n", " +0.197\n", " \n", " 9739_41985 9739_24324\n", "
\n", " +0.178\n", " \n", " 9739_24321\n", "
\n", " +0.168\n", " \n", " 9739_24324 9739_41985\n", "
\n", " +0.165\n", " \n", " 9916_15875\n", "
\n", " +0.159\n", " \n", " 9916_65292\n", "
\n", " … 947 more positive …\n", "
\n", " … 49044 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.503\n", " \n", " 9734_61702\n", "
\n", " +0.351\n", " \n", " 9734_61699\n", "
\n", " +0.315\n", " \n", " 9734_61728\n", "
\n", " +0.300\n", " \n", " 9734_59905\n", "
\n", " +0.199\n", " \n", " 9734_59905 9734_61702\n", "
\n", " +0.188\n", " \n", " 9734_61702 9734_59905\n", "
\n", " +0.165\n", " \n", " 9734_61699 9734_61728\n", "
\n", " +0.131\n", " \n", " 9734_61702 9734_61699\n", "
\n", " +0.131\n", " \n", " 9734_61728 9734_61699\n", "
\n", " +0.120\n", " \n", " 9734_61702 9734_61728\n", "
\n", " … 573 more positive …\n", "
\n", " … 49418 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.336\n", " \n", " 9734_30486\n", "
\n", " +0.322\n", " \n", " 9734_30466 9734_30486\n", "
\n", " +0.312\n", " \n", " 9734_30486 9734_30466\n", "
\n", " +0.267\n", " \n", " 9734_30466\n", "
\n", " +0.260\n", " \n", " 9734_30486 9734_30466 9734_30486\n", "
\n", " +0.259\n", " \n", " 9734_30466 9734_30486 9734_30466\n", "
\n", " +0.245\n", " \n", " 7752_766\n", "
\n", " +0.215\n", " \n", " 9916_52227\n", "
\n", " +0.187\n", " \n", " 9916_52246\n", "
\n", " +0.183\n", " \n", " 9735_54533\n", "
\n", " … 430 more positive …\n", "
\n", " … 49561 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.537\n", " \n", " 9916_59680\n", "
\n", " +0.511\n", " \n", " 9916_59651\n", "
\n", " +0.320\n", " \n", " 9916_59680 9916_59651\n", "
\n", " +0.290\n", " \n", " 9916_59651 9916_59680\n", "
\n", " +0.200\n", " \n", " 9916_59680 9916_59651 9916_59680\n", "
\n", " +0.196\n", " \n", " 9916_59651 9916_59680 9916_59651\n", "
\n", " +0.108\n", " \n", " 9916_3350\n", "
\n", " +0.108\n", " \n", " 9916_3330\n", "
\n", " +0.102\n", " \n", " 9916_59680 9916_59680\n", "
\n", " +0.098\n", " \n", " 9916_32769\n", "
\n", " … 722 more positive …\n", "
\n", " … 49269 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.271\n", " \n", " 9935_63748\n", "
\n", " +0.264\n", " \n", " 9733_59396\n", "
\n", " +0.229\n", " \n", " 9043_53510\n", "
\n", " +0.229\n", " \n", " 5064_36357\n", "
\n", " +0.181\n", " \n", " 9735_25603\n", "
\n", " +0.165\n", " \n", " 5046_54149\n", "
\n", " +0.160\n", " \n", " 9935_14336\n", "
\n", " +0.157\n", " \n", " 9733_23971\n", "
\n", " +0.151\n", " \n", " 7752_61575\n", "
\n", " +0.150\n", " \n", " 9736_11782\n", "
\n", " … 776 more positive …\n", "
\n", " … 49215 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.334\n", " \n", " 9732_27142\n", "
\n", " +0.283\n", " \n", " 7755_872\n", "
\n", " +0.239\n", " \n", " 9734_14337\n", "
\n", " +0.192\n", " \n", " 9732_12289\n", "
\n", " +0.172\n", " \n", " 7755_873\n", "
\n", " +0.171\n", " \n", " 9734_34817\n", "
\n", " +0.167\n", " \n", " 9734_30465\n", "
\n", " +0.134\n", " \n", " 9734_30465 9734_61702 9734_30465\n", "
\n", " +0.133\n", " \n", " 9734_14340\n", "
\n", " +0.132\n", " \n", " 9734_61702 9734_30465\n", "
\n", " … 899 more positive …\n", "
\n", " … 49092 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.320\n", " \n", " 9739_29953\n", "
\n", " +0.319\n", " \n", " 9754_40450\n", "
\n", " +0.312\n", " \n", " 9916_46339\n", "
\n", " +0.291\n", " \n", " 9754_40470\n", "
\n", " +0.290\n", " \n", " 7755_38450\n", "
\n", " +0.254\n", " \n", " 9754_40452\n", "
\n", " +0.212\n", " \n", " 9916_20996\n", "
\n", " +0.171\n", " \n", " 9916_20996 9916_46339\n", "
\n", " +0.158\n", " \n", " 9916_46339 9916_20996\n", "
\n", " +0.151\n", " \n", " 5046_64340\n", "
\n", " … 608 more positive …\n", "
\n", " … 49383 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.604\n", " \n", " 5069_61443\n", "
\n", " +0.447\n", " \n", " 5015_51628\n", "
\n", " +0.314\n", " \n", " 5015_61397\n", "
\n", " +0.240\n", " \n", " 5015_51628 5069_61443\n", "
\n", " +0.236\n", " \n", " 5069_61443 5015_51628\n", "
\n", " +0.170\n", " \n", " 5069_61443 5015_61397\n", "
\n", " +0.165\n", " \n", " 5015_61397 5069_61443\n", "
\n", " +0.161\n", " \n", " 5069_61443 5069_61443\n", "
\n", " +0.128\n", " \n", " 5015_51628 5015_51628\n", "
\n", " +0.108\n", " \n", " 5069_61448\n", "
\n", " … 263 more positive …\n", "
\n", " … 49728 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.374\n", " \n", " 5047_8546\n", "
\n", " +0.321\n", " \n", " 7757_7040\n", "
\n", " +0.258\n", " \n", " 7755_9520\n", "
\n", " +0.239\n", " \n", " 7757_7033\n", "
\n", " +0.228\n", " \n", " 7755_44696\n", "
\n", " +0.205\n", " \n", " 7757_3276\n", "
\n", " +0.198\n", " \n", " 7755_35789\n", "
\n", " +0.196\n", " \n", " 9757_1050\n", "
\n", " +0.174\n", " \n", " 7755_57579\n", "
\n", " +0.150\n", " \n", " 9752_1936\n", "
\n", " … 115 more positive …\n", "
\n", " … 49876 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.563\n", " \n", " 7716_3161\n", "
\n", " +0.309\n", " \n", " 9716_3151\n", "
\n", " +0.283\n", " \n", " 9734_5382\n", "
\n", " +0.236\n", " \n", " 9916_42754\n", "
\n", " +0.221\n", " \n", " 9916_42774\n", "
\n", " +0.198\n", " \n", " 7716_3161 9716_3151\n", "
\n", " +0.195\n", " \n", " 9716_3151 7716_3161\n", "
\n", " +0.179\n", " \n", " 9716_4102\n", "
\n", " +0.156\n", " \n", " 9916_42774 9916_42754\n", "
\n", " +0.152\n", " \n", " 9916_42754 9916_42774\n", "
\n", " … 739 more positive …\n", "
\n", " … 49252 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.402\n", " \n", " 7716_55676\n", "
\n", " +0.355\n", " \n", " 7746_6551\n", "
\n", " +0.342\n", " \n", " 7716_39675\n", "
\n", " +0.304\n", " \n", " 7746_6552\n", "
\n", " +0.269\n", " \n", " 7746_6550\n", "
\n", " +0.170\n", " \n", " 7716_28931\n", "
\n", " +0.169\n", " \n", " 7716_31789\n", "
\n", " +0.157\n", " \n", " 7716_55676 7746_6551\n", "
\n", " +0.156\n", " \n", " 7746_6552 7716_39675\n", "
\n", " +0.143\n", " \n", " 7716_39675 7746_6552\n", "
\n", " … 507 more positive …\n", "
\n", " … 49484 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.618\n", " \n", " 9741_48901\n", "
\n", " +0.363\n", " \n", " 7741_5928\n", "
\n", " +0.270\n", " \n", " 7712_45270\n", "
\n", " +0.196\n", " \n", " 7746_14896\n", "
\n", " +0.194\n", " \n", " 9741_48901 7741_5928\n", "
\n", " +0.192\n", " \n", " 7741_5926\n", "
\n", " +0.188\n", " \n", " 7741_5928 9741_48901\n", "
\n", " +0.152\n", " \n", " 9741_48901 9741_48901\n", "
\n", " +0.151\n", " \n", " 7712_45270 9741_48901\n", "
\n", " +0.138\n", " \n", " 9741_48901 7712_45270\n", "
\n", " … 415 more positive …\n", "
\n", " … 49576 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.403\n", " \n", " 9716_1796\n", "
\n", " +0.323\n", " \n", " 9716_64513\n", "
\n", " +0.281\n", " \n", " 9716_64513 9716_64524 9716_64513\n", "
\n", " +0.253\n", " \n", " 9716_1793\n", "
\n", " +0.250\n", " \n", " 9716_64524 9716_64513\n", "
\n", " +0.237\n", " \n", " 9716_64513 9716_64524\n", "
\n", " +0.236\n", " \n", " 9716_64524 9716_64513 9716_64524\n", "
\n", " +0.233\n", " \n", " 9716_64524\n", "
\n", " +0.164\n", " \n", " 9716_64516\n", "
\n", " +0.157\n", " \n", " 9937_59393\n", "
\n", " … 386 more positive …\n", "
\n", " … 49605 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.340\n", " \n", " 9734_60694\n", "
\n", " +0.326\n", " \n", " 9916_63747\n", "
\n", " +0.322\n", " \n", " 9916_63776\n", "
\n", " +0.313\n", " \n", " 9734_60674\n", "
\n", " +0.272\n", " \n", " 9916_63776 9916_63747\n", "
\n", " +0.259\n", " \n", " 9916_63747 9916_63776\n", "
\n", " +0.230\n", " \n", " 9734_60694 9734_60674\n", "
\n", " +0.230\n", " \n", " 9734_60677\n", "
\n", " +0.218\n", " \n", " 9916_63776 9916_63747 9916_63776\n", "
\n", " +0.214\n", " \n", " 9916_63747 9916_63776 9916_63747\n", "
\n", " … 786 more positive …\n", "
\n", " … 49205 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.462\n", " \n", " 9790_38913\n", "
\n", " +0.408\n", " \n", " 9790_38924\n", "
\n", " +0.244\n", " \n", " 9790_38924 9790_38913\n", "
\n", " +0.238\n", " \n", " 7752_61571\n", "
\n", " +0.229\n", " \n", " 9790_38913 9790_38924\n", "
\n", " +0.209\n", " \n", " 9790_38916\n", "
\n", " +0.181\n", " \n", " 9754_18690\n", "
\n", " +0.180\n", " \n", " 9735_7169\n", "
\n", " +0.159\n", " \n", " 9935_63748\n", "
\n", " +0.135\n", " \n", " 9752_13216\n", "
\n", " … 678 more positive …\n", "
\n", " … 49313 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.643\n", " \n", " 9716_2260 9716_2260\n", "
\n", " +0.599\n", " \n", " 9716_2260 9716_2260 9716_2260\n", "
\n", " +0.463\n", " \n", " 9716_2260\n", "
\n", " … 1 more positive …\n", "
\n", " … 49990 more negative …\n", "
\n", " -0.006\n", " \n", " 9702_30576\n", "
\n", " -0.006\n", " \n", " 9700_8607\n", "
\n", " -0.006\n", " \n", " 9916_20226\n", "
\n", " -0.006\n", " \n", " 9734_61702\n", "
\n", " -0.007\n", " \n", " 9702_30571\n", "
\n", " -0.008\n", " \n", " 9752_14642\n", "
\n", " -0.009\n", " \n", " 9752_14633\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.717\n", " \n", " 7716_3158\n", "
\n", " +0.207\n", " \n", " 7716_3157\n", "
\n", " +0.199\n", " \n", " 7716_3158 7716_3157\n", "
\n", " +0.199\n", " \n", " 7716_3157 7716_3158\n", "
\n", " +0.177\n", " \n", " 9716_33107\n", "
\n", " +0.168\n", " \n", " 9716_3146\n", "
\n", " +0.146\n", " \n", " 7752_45995\n", "
\n", " +0.146\n", " \n", " 7716_3976\n", "
\n", " +0.134\n", " \n", " 7716_3158 9716_3146\n", "
\n", " +0.128\n", " \n", " 7716_6440\n", "
\n", " … 154 more positive …\n", "
\n", " … 49837 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.484\n", " \n", " 9739_34305\n", "
\n", " +0.341\n", " \n", " 9754_51203\n", "
\n", " +0.314\n", " \n", " 9754_51203 9739_34305\n", "
\n", " +0.271\n", " \n", " 9739_34305 9754_51203\n", "
\n", " +0.174\n", " \n", " 9760_27649\n", "
\n", " +0.170\n", " \n", " 9760_15110\n", "
\n", " +0.163\n", " \n", " 9739_34305 9754_51203 9739_34305\n", "
\n", " +0.155\n", " \n", " 9754_51232\n", "
\n", " +0.150\n", " \n", " 9934_22273\n", "
\n", " +0.149\n", " \n", " 9934_49665\n", "
\n", " … 470 more positive …\n", "
\n", " … 49521 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.513\n", " \n", " 9716_62011\n", "
\n", " +0.452\n", " \n", " 7716_31050\n", "
\n", " +0.335\n", " \n", " 9716_33828\n", "
\n", " +0.211\n", " \n", " 7752_7698\n", "
\n", " +0.201\n", " \n", " 7716_55654\n", "
\n", " +0.193\n", " \n", " 7752_7699\n", "
\n", " +0.193\n", " \n", " 7716_31050 9716_62011\n", "
\n", " +0.145\n", " \n", " 9716_62011 9716_33828\n", "
\n", " +0.138\n", " \n", " 7716_55654 9716_62011\n", "
\n", " +0.131\n", " \n", " 9716_33828 7716_31050\n", "
\n", " … 86 more positive …\n", "
\n", " … 49905 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.421\n", " \n", " 9734_16642\n", "
\n", " +0.356\n", " \n", " 9734_61700\n", "
\n", " +0.305\n", " \n", " 9734_16642 9734_61700\n", "
\n", " +0.251\n", " \n", " 9734_61700 9734_16642\n", "
\n", " +0.230\n", " \n", " 5007_770\n", "
\n", " +0.199\n", " \n", " 9734_16642 9734_61700 9734_16642\n", "
\n", " +0.167\n", " \n", " 5007_11521\n", "
\n", " +0.146\n", " \n", " 9734_61700 9734_16642 9734_61700\n", "
\n", " +0.143\n", " \n", " 5007_14594\n", "
\n", " +0.138\n", " \n", " 7716_63228\n", "
\n", " … 700 more positive …\n", "
\n", " … 49291 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.632\n", " \n", " 7716_3668\n", "
\n", " +0.382\n", " \n", " 7716_3669\n", "
\n", " +0.265\n", " \n", " 7716_3668 7716_3669\n", "
\n", " +0.199\n", " \n", " 7716_3669 7716_3668\n", "
\n", " +0.158\n", " \n", " 7752_759\n", "
\n", " +0.139\n", " \n", " 7716_20068\n", "
\n", " +0.139\n", " \n", " 9716_3664\n", "
\n", " +0.139\n", " \n", " 7716_3668 7716_3668\n", "
\n", " +0.123\n", " \n", " 9716_3664 7716_3668\n", "
\n", " +0.121\n", " \n", " 7716_3669 7716_20068\n", "
\n", " … 190 more positive …\n", "
\n", " … 49801 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.375\n", " \n", " 7755_55462\n", "
\n", " +0.329\n", " \n", " 5091_55862\n", "
\n", " +0.307\n", " \n", " 5091_57624\n", "
\n", " +0.270\n", " \n", " 7755_33264\n", "
\n", " +0.213\n", " \n", " 7755_55462 7755_33264\n", "
\n", " +0.190\n", " \n", " 7755_33264 7755_55462\n", "
\n", " +0.182\n", " \n", " 9091_55807\n", "
\n", " +0.136\n", " \n", " 9091_57627\n", "
\n", " +0.136\n", " \n", " 5091_55862 5091_55862\n", "
\n", " +0.132\n", " \n", " 7755_55462 7755_55462\n", "
\n", " … 452 more positive …\n", "
\n", " … 49539 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.380\n", " \n", " 9916_42764\n", "
\n", " +0.339\n", " \n", " 9916_42753\n", "
\n", " +0.333\n", " \n", " 9916_42764 9916_42753\n", "
\n", " +0.320\n", " \n", " 9916_42764 9916_42753 9916_42764\n", "
\n", " +0.317\n", " \n", " 9916_42753 9916_42764\n", "
\n", " +0.258\n", " \n", " 9916_42753 9916_42764 9916_42753\n", "
\n", " +0.164\n", " \n", " 9734_48406\n", "
\n", " +0.156\n", " \n", " 9716_33092\n", "
\n", " +0.150\n", " \n", " 9716_10497\n", "
\n", " +0.125\n", " \n", " 9759_22017\n", "
\n", " … 274 more positive …\n", "
\n", " … 49717 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.409\n", " \n", " 7755_2994\n", "
\n", " +0.323\n", " \n", " 7716_21029\n", "
\n", " +0.259\n", " \n", " 9735_21280\n", "
\n", " +0.241\n", " \n", " 9735_21251\n", "
\n", " +0.180\n", " \n", " 9735_41731\n", "
\n", " +0.177\n", " \n", " 7755_2994 7755_2994\n", "
\n", " +0.166\n", " \n", " 7755_2994 7716_21029\n", "
\n", " +0.166\n", " \n", " 7716_21029 7755_2994\n", "
\n", " +0.165\n", " \n", " 7755_2998\n", "
\n", " +0.158\n", " \n", " 9739_27907\n", "
\n", " … 574 more positive …\n", "
\n", " … 49417 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.447\n", " \n", " 9935_14597\n", "
\n", " +0.446\n", " \n", " 9935_14614\n", "
\n", " +0.384\n", " \n", " 9935_11523\n", "
\n", " +0.319\n", " \n", " 9935_14594\n", "
\n", " +0.187\n", " \n", " 9935_11523 9935_14597\n", "
\n", " +0.177\n", " \n", " 9935_14614 9935_11523\n", "
\n", " +0.166\n", " \n", " 9935_14597 9935_11523\n", "
\n", " +0.156\n", " \n", " 9935_14597 9935_14614\n", "
\n", " +0.137\n", " \n", " 9935_11523 9935_14614\n", "
\n", " +0.129\n", " \n", " 9935_11523 9935_14594\n", "
\n", " … 425 more positive …\n", "
\n", " … 49566 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.353\n", " \n", " 7716_11855\n", "
\n", " +0.343\n", " \n", " 7716_11870\n", "
\n", " +0.331\n", " \n", " 7716_11855 7716_11870\n", "
\n", " +0.311\n", " \n", " 7716_11870 7716_11855\n", "
\n", " +0.289\n", " \n", " 7757_12699\n", "
\n", " +0.270\n", " \n", " 7757_12693\n", "
\n", " +0.232\n", " \n", " 7716_11855 7716_11870 7716_11855\n", "
\n", " +0.232\n", " \n", " 7716_11870 7716_11855 7716_11870\n", "
\n", " +0.193\n", " \n", " 7757_12693 7757_12699\n", "
\n", " +0.165\n", " \n", " 7757_12699 7757_12693\n", "
\n", " … 116 more positive …\n", "
\n", " … 49875 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.537\n", " \n", " 7716_33418\n", "
\n", " +0.391\n", " \n", " 9716_31426\n", "
\n", " +0.254\n", " \n", " 7716_4759\n", "
\n", " +0.246\n", " \n", " 7716_62504\n", "
\n", " +0.232\n", " \n", " 9716_30646\n", "
\n", " +0.213\n", " \n", " 7716_33418 9716_31426\n", "
\n", " +0.210\n", " \n", " 9716_31426 7716_33418\n", "
\n", " +0.174\n", " \n", " 7716_61907\n", "
\n", " +0.122\n", " \n", " 7716_33418 7716_4759\n", "
\n", " +0.121\n", " \n", " 7716_6975\n", "
\n", " … 313 more positive …\n", "
\n", " … 49678 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.389\n", " \n", " 9934_20512\n", "
\n", " +0.328\n", " \n", " 9934_20483\n", "
\n", " +0.298\n", " \n", " 9736_48396\n", "
\n", " +0.262\n", " \n", " 9734_3078\n", "
\n", " +0.192\n", " \n", " 9934_20512 9736_48396\n", "
\n", " +0.185\n", " \n", " 9734_3075\n", "
\n", " +0.178\n", " \n", " 9736_48385\n", "
\n", " +0.175\n", " \n", " 9734_3104\n", "
\n", " +0.167\n", " \n", " 9736_48396 9934_20512\n", "
\n", " +0.160\n", " \n", " 9736_11781\n", "
\n", " … 395 more positive …\n", "
\n", " … 49596 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.434\n", " \n", " 7755_6982\n", "
\n", " +0.380\n", " \n", " 7755_15800\n", "
\n", " +0.273\n", " \n", " 7716_3668\n", "
\n", " +0.266\n", " \n", " 7755_6984\n", "
\n", " +0.265\n", " \n", " 7755_6592\n", "
\n", " +0.209\n", " \n", " 7755_6982 7755_15800\n", "
\n", " +0.199\n", " \n", " 7755_31332\n", "
\n", " +0.170\n", " \n", " 7716_3667\n", "
\n", " +0.167\n", " \n", " 7755_6983\n", "
\n", " +0.158\n", " \n", " 7755_15800 7755_6982\n", "
\n", " … 169 more positive …\n", "
\n", " … 49822 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.365\n", " \n", " 9716_30209\n", "
\n", " +0.343\n", " \n", " 9716_30220\n", "
\n", " +0.326\n", " \n", " 9716_30209 9716_30220\n", "
\n", " +0.319\n", " \n", " 9716_30220 9716_30209\n", "
\n", " +0.304\n", " \n", " 9716_30220 9716_30209 9716_30220\n", "
\n", " +0.297\n", " \n", " 9716_30209 9716_30220 9716_30209\n", "
\n", " +0.213\n", " \n", " 9916_20225\n", "
\n", " +0.201\n", " \n", " 9916_20236\n", "
\n", " +0.196\n", " \n", " 9916_65281\n", "
\n", " +0.148\n", " \n", " 9916_65292\n", "
\n", " … 761 more positive …\n", "
\n", " … 49230 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.510\n", " \n", " 9900_46850\n", "
\n", " +0.445\n", " \n", " 9900_46870\n", "
\n", " +0.322\n", " \n", " 9900_46870 9900_46850\n", "
\n", " +0.313\n", " \n", " 9900_46850 9900_46870\n", "
\n", " +0.214\n", " \n", " 9900_46850 9900_46870 9900_46850\n", "
\n", " +0.209\n", " \n", " 9900_46870 9900_46850 9900_46870\n", "
\n", " +0.169\n", " \n", " 5069_51213\n", "
\n", " +0.129\n", " \n", " 5069_51210\n", "
\n", " +0.114\n", " \n", " 9900_46853\n", "
\n", " +0.107\n", " \n", " 5069_51210 5069_51213\n", "
\n", " … 691 more positive …\n", "
\n", " … 49300 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.482\n", " \n", " 7700_1427\n", "
\n", " +0.402\n", " \n", " 7700_36930\n", "
\n", " +0.313\n", " \n", " 7700_49377\n", "
\n", " +0.234\n", " \n", " 7700_49377 7700_36930\n", "
\n", " +0.214\n", " \n", " 9700_14257\n", "
\n", " +0.208\n", " \n", " 9754_15275\n", "
\n", " +0.195\n", " \n", " 7700_36930 7700_49377\n", "
\n", " +0.194\n", " \n", " 9746_16330\n", "
\n", " +0.170\n", " \n", " 7700_1427 7700_1427\n", "
\n", " +0.156\n", " \n", " 7700_36930 7700_49377 7700_36930\n", "
\n", " … 145 more positive …\n", "
\n", " … 49846 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.342\n", " \n", " 9716_18178\n", "
\n", " +0.311\n", " \n", " 9716_48389\n", "
\n", " +0.282\n", " \n", " 9716_48406\n", "
\n", " +0.266\n", " \n", " 9716_48386\n", "
\n", " +0.243\n", " \n", " 9716_7190\n", "
\n", " +0.200\n", " \n", " 9716_7170\n", "
\n", " +0.191\n", " \n", " 9732_1541\n", "
\n", " +0.181\n", " \n", " 9732_1538\n", "
\n", " +0.155\n", " \n", " 9732_19458\n", "
\n", " +0.122\n", " \n", " 9716_18178 9716_48389\n", "
\n", " … 936 more positive …\n", "
\n", " … 49055 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.473\n", " \n", " 9762_28677\n", "
\n", " +0.348\n", " \n", " 9716_13825\n", "
\n", " +0.234\n", " \n", " 9716_64516\n", "
\n", " +0.191\n", " \n", " 9716_64516 9716_13825\n", "
\n", " +0.191\n", " \n", " 5042_57847\n", "
\n", " +0.187\n", " \n", " 5077_51032\n", "
\n", " +0.178\n", " \n", " 9716_13825 9716_64516\n", "
\n", " +0.150\n", " \n", " 5047_32518\n", "
\n", " +0.135\n", " \n", " 9716_58881\n", "
\n", " +0.125\n", " \n", " 9737_36868\n", "
\n", " … 723 more positive …\n", "
\n", " … 49268 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.533\n", " \n", " 9934_11009\n", "
\n", " +0.220\n", " \n", " 9716_4097\n", "
\n", " +0.202\n", " \n", " 9716_18433\n", "
\n", " +0.199\n", " \n", " 9716_18178\n", "
\n", " +0.195\n", " \n", " 9716_4108\n", "
\n", " +0.175\n", " \n", " 9716_48389\n", "
\n", " +0.157\n", " \n", " 9701_46339\n", "
\n", " +0.142\n", " \n", " 9934_56067\n", "
\n", " +0.141\n", " \n", " 5015_63902\n", "
\n", " +0.133\n", " \n", " 5000_25376\n", "
\n", " … 769 more positive …\n", "
\n", " … 49222 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.382\n", " \n", " 9734_59906\n", "
\n", " +0.289\n", " \n", " 9716_13827\n", "
\n", " +0.283\n", " \n", " 9734_8197\n", "
\n", " +0.277\n", " \n", " 9734_35078\n", "
\n", " +0.227\n", " \n", " 9734_8194\n", "
\n", " +0.197\n", " \n", " 7716_6166\n", "
\n", " +0.175\n", " \n", " 9734_8214\n", "
\n", " +0.155\n", " \n", " 9716_64516\n", "
\n", " +0.131\n", " \n", " 9908_50689\n", "
\n", " +0.129\n", " \n", " 9934_51714\n", "
\n", " … 822 more positive …\n", "
\n", " … 49169 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.478\n", " \n", " 9935_44290\n", "
\n", " +0.419\n", " \n", " 9935_44292\n", "
\n", " +0.387\n", " \n", " 9935_44310\n", "
\n", " +0.184\n", " \n", " 9935_8449\n", "
\n", " +0.174\n", " \n", " 9935_44290 9935_44292\n", "
\n", " +0.161\n", " \n", " 9935_48385\n", "
\n", " +0.144\n", " \n", " 9935_44292 9935_44290\n", "
\n", " +0.142\n", " \n", " 9935_44292 9935_44310\n", "
\n", " +0.124\n", " \n", " 9935_44310 9935_44290\n", "
\n", " +0.119\n", " \n", " 9935_44310 9935_44292\n", "
\n", " … 634 more positive …\n", "
\n", " … 49357 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.409\n", " \n", " 7716_6434\n", "
\n", " +0.378\n", " \n", " 5010_60780\n", "
\n", " +0.336\n", " \n", " 7752_1567\n", "
\n", " +0.275\n", " \n", " 7752_1569\n", "
\n", " +0.182\n", " \n", " 5010_7588\n", "
\n", " +0.162\n", " \n", " 9752_1556\n", "
\n", " +0.154\n", " \n", " 5010_7591\n", "
\n", " +0.140\n", " \n", " 9037_56936\n", "
\n", " +0.135\n", " \n", " 7752_2087\n", "
\n", " +0.126\n", " \n", " 7752_1569 7752_1567\n", "
\n", " … 291 more positive …\n", "
\n", " … 49700 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.499\n", " \n", " 9937_59395\n", "
\n", " +0.406\n", " \n", " 9937_59424\n", "
\n", " +0.319\n", " \n", " 9937_34819\n", "
\n", " +0.258\n", " \n", " 9937_59395 9937_59424\n", "
\n", " +0.255\n", " \n", " 9937_59424 9937_59395\n", "
\n", " +0.176\n", " \n", " 9758_23298\n", "
\n", " +0.165\n", " \n", " 9937_59395 9937_59424 9937_59395\n", "
\n", " +0.159\n", " \n", " 9937_59395 9937_34819\n", "
\n", " +0.146\n", " \n", " 9937_59424 9937_59395 9937_59424\n", "
\n", " +0.138\n", " \n", " 9937_34819 9937_59395\n", "
\n", " … 543 more positive …\n", "
\n", " … 49448 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.369\n", " \n", " 9937_59394\n", "
\n", " +0.364\n", " \n", " 9937_59414\n", "
\n", " +0.319\n", " \n", " 9937_59394 9937_59414\n", "
\n", " +0.299\n", " \n", " 9937_59414 9937_59394\n", "
\n", " +0.270\n", " \n", " 9937_59414 9937_59394 9937_59414\n", "
\n", " +0.250\n", " \n", " 9937_59394 9937_59414 9937_59394\n", "
\n", " +0.190\n", " \n", " 9739_21270\n", "
\n", " +0.158\n", " \n", " 9739_21250\n", "
\n", " +0.158\n", " \n", " 9716_2052\n", "
\n", " +0.147\n", " \n", " 5024_8480\n", "
\n", " … 516 more positive …\n", "
\n", " … 49475 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.456\n", " \n", " 7787_14015\n", "
\n", " +0.354\n", " \n", " 7710_7966\n", "
\n", " +0.267\n", " \n", " 7755_6982\n", "
\n", " +0.253\n", " \n", " 9787_13978\n", "
\n", " +0.253\n", " \n", " 5006_4711\n", "
\n", " +0.249\n", " \n", " 7755_30228\n", "
\n", " +0.202\n", " \n", " 9006_4831\n", "
\n", " +0.202\n", " \n", " 9787_13978 7787_14015\n", "
\n", " +0.190\n", " \n", " 7755_6594\n", "
\n", " +0.163\n", " \n", " 7755_6593\n", "
\n", " … 69 more positive …\n", "
\n", " … 49922 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.545\n", " \n", " 7755_15802\n", "
\n", " +0.310\n", " \n", " 7755_15807\n", "
\n", " +0.303\n", " \n", " 7755_15810\n", "
\n", " +0.206\n", " \n", " 9757_7021\n", "
\n", " +0.190\n", " \n", " 7755_15806\n", "
\n", " +0.164\n", " \n", " 7755_15818\n", "
\n", " +0.162\n", " \n", " 7755_15802 7755_15807\n", "
\n", " +0.160\n", " \n", " 7755_15810 7755_15802\n", "
\n", " +0.154\n", " \n", " 7755_15802 7755_15810\n", "
\n", " +0.146\n", " \n", " 9716_33842\n", "
\n", " … 228 more positive …\n", "
\n", " … 49763 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.533\n", " \n", " 7755_6592\n", "
\n", " +0.437\n", " \n", " 7755_6976\n", "
\n", " +0.304\n", " \n", " 7755_6976 7755_6592\n", "
\n", " +0.283\n", " \n", " 7755_6592 7755_6976\n", "
\n", " +0.231\n", " \n", " 7755_6592 7755_6592\n", "
\n", " +0.204\n", " \n", " 7755_6976 7755_6976\n", "
\n", " +0.185\n", " \n", " 7755_6977\n", "
\n", " +0.155\n", " \n", " 7755_6982\n", "
\n", " +0.136\n", " \n", " 7755_6976 7755_6592 7755_6976\n", "
\n", " +0.133\n", " \n", " 7755_6592 7755_6976 7755_6976\n", "
\n", " … 119 more positive …\n", "
\n", " … 49872 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.452\n", " \n", " 9716_3665\n", "
\n", " +0.282\n", " \n", " 9716_7033\n", "
\n", " +0.267\n", " \n", " 7755_31336\n", "
\n", " +0.223\n", " \n", " 9700_19413\n", "
\n", " +0.223\n", " \n", " 9716_7033 9716_3665\n", "
\n", " +0.223\n", " \n", " 9716_3665 7755_31336\n", "
\n", " +0.175\n", " \n", " 9716_3665 9716_3665\n", "
\n", " +0.156\n", " \n", " 7755_31336 9716_3665\n", "
\n", " +0.151\n", " \n", " 9716_31386\n", "
\n", " +0.146\n", " \n", " 9716_7033 9716_3665 9716_3665\n", "
\n", " … 149 more positive …\n", "
\n", " … 49842 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.492\n", " \n", " 9916_41475\n", "
\n", " +0.463\n", " \n", " 9916_41504\n", "
\n", " +0.332\n", " \n", " 9916_41504 9916_41475\n", "
\n", " +0.332\n", " \n", " 9916_41475 9916_41504\n", "
\n", " +0.230\n", " \n", " 9916_41475 9916_41504 9916_41475\n", "
\n", " +0.215\n", " \n", " 9916_41504 9916_41475 9916_41504\n", "
\n", " +0.130\n", " \n", " 9758_23297\n", "
\n", " +0.128\n", " \n", " 9758_23308\n", "
\n", " +0.126\n", " \n", " 9916_41475 9916_41475\n", "
\n", " +0.124\n", " \n", " 9734_14854\n", "
\n", " … 727 more positive …\n", "
\n", " … 49264 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.377\n", " \n", " 7716_742\n", "
\n", " +0.373\n", " \n", " 9716_31053\n", "
\n", " +0.371\n", " \n", " 7716_3160\n", "
\n", " +0.371\n", " \n", " 9716_3151\n", "
\n", " +0.242\n", " \n", " 7716_742 9716_31053\n", "
\n", " +0.224\n", " \n", " 9716_31053 7716_742\n", "
\n", " +0.186\n", " \n", " 9716_3151 7716_3160\n", "
\n", " +0.184\n", " \n", " 7716_3160 9716_3151\n", "
\n", " +0.156\n", " \n", " 9716_31053 9716_31053\n", "
\n", " +0.132\n", " \n", " 7716_3160 7716_3160\n", "
\n", " … 272 more positive …\n", "
\n", " … 49719 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.358\n", " \n", " 9937_59394\n", "
\n", " +0.349\n", " \n", " 9937_59414\n", "
\n", " +0.349\n", " \n", " 9739_34305\n", "
\n", " +0.285\n", " \n", " 9739_9729\n", "
\n", " +0.244\n", " \n", " 9739_44294\n", "
\n", " +0.234\n", " \n", " 9937_59414 9937_59394\n", "
\n", " +0.229\n", " \n", " 9937_59394 9937_59414\n", "
\n", " +0.191\n", " \n", " 9739_9729 9739_34305\n", "
\n", " +0.169\n", " \n", " 9739_34305 9739_9729\n", "
\n", " +0.158\n", " \n", " 9937_59394 9937_59414 9937_59394\n", "
\n", " … 860 more positive …\n", "
\n", " … 49131 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.347\n", " \n", " 9942_22276\n", "
\n", " +0.342\n", " \n", " 9976_63750\n", "
\n", " +0.301\n", " \n", " 9942_22273\n", "
\n", " +0.262\n", " \n", " 9716_48918\n", "
\n", " +0.260\n", " \n", " 9942_22284\n", "
\n", " +0.256\n", " \n", " 9976_63747\n", "
\n", " +0.208\n", " \n", " 9716_48898\n", "
\n", " +0.183\n", " \n", " 9716_48918 9716_48898\n", "
\n", " +0.183\n", " \n", " 9716_48898 9716_48918\n", "
\n", " +0.155\n", " \n", " 9716_48918 9716_48898 9716_48918\n", "
\n", " … 659 more positive …\n", "
\n", " … 49332 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.548\n", " \n", " 9934_45318\n", "
\n", " +0.473\n", " \n", " 9934_257\n", "
\n", " +0.302\n", " \n", " 9934_45315\n", "
\n", " +0.216\n", " \n", " 9934_45324\n", "
\n", " +0.195\n", " \n", " 9934_45344\n", "
\n", " +0.183\n", " \n", " 9934_45318 9934_257\n", "
\n", " +0.147\n", " \n", " 9934_257 9934_45318\n", "
\n", " +0.122\n", " \n", " 9934_45324 9934_257\n", "
\n", " +0.113\n", " \n", " 9934_45315 9934_45318\n", "
\n", " +0.112\n", " \n", " 9916_25089\n", "
\n", " … 515 more positive …\n", "
\n", " … 49476 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.674\n", " \n", " 5007_64499\n", "
\n", " +0.336\n", " \n", " 9007_54879\n", "
\n", " +0.323\n", " \n", " 9007_54874\n", "
\n", " +0.214\n", " \n", " 9007_54874 5007_64499\n", "
\n", " +0.209\n", " \n", " 5007_64499 9007_54879\n", "
\n", " +0.193\n", " \n", " 5007_64499 9007_54874\n", "
\n", " +0.182\n", " \n", " 9007_54879 5007_64499\n", "
\n", " +0.174\n", " \n", " 5007_64499 5007_64499\n", "
\n", " +0.130\n", " \n", " 5007_64499 9007_54874 5007_64499\n", "
\n", " +0.122\n", " \n", " 9046_21253\n", "
\n", " … 424 more positive …\n", "
\n", " … 49567 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.407\n", " \n", " 7752_880\n", "
\n", " +0.384\n", " \n", " 7752_894\n", "
\n", " +0.303\n", " \n", " 9746_16331\n", "
\n", " +0.273\n", " \n", " 7752_880 7752_894\n", "
\n", " +0.231\n", " \n", " 9752_866\n", "
\n", " +0.228\n", " \n", " 7752_894 7752_880\n", "
\n", " +0.198\n", " \n", " 7746_48369\n", "
\n", " +0.167\n", " \n", " 7752_880 7752_894 7752_880\n", "
\n", " +0.163\n", " \n", " 9752_867\n", "
\n", " +0.152\n", " \n", " 9746_34221\n", "
\n", " … 257 more positive …\n", "
\n", " … 49734 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.473\n", " \n", " 9937_43011\n", "
\n", " +0.461\n", " \n", " 9937_43040\n", "
\n", " +0.368\n", " \n", " 9937_43011 9937_43040\n", "
\n", " +0.341\n", " \n", " 9937_43040 9937_43011\n", "
\n", " +0.257\n", " \n", " 9937_43011 9937_43040 9937_43011\n", "
\n", " +0.254\n", " \n", " 9937_43040 9937_43011 9937_43040\n", "
\n", " +0.105\n", " \n", " 9937_30722\n", "
\n", " +0.095\n", " \n", " 9937_43040 9937_43040\n", "
\n", " +0.092\n", " \n", " 9937_34817\n", "
\n", " +0.089\n", " \n", " 9937_43011 9937_43011\n", "
\n", " … 848 more positive …\n", "
\n", " … 49143 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.504\n", " \n", " 9937_30722\n", "
\n", " +0.357\n", " \n", " 9937_43040\n", "
\n", " +0.251\n", " \n", " 7716_44974\n", "
\n", " +0.246\n", " \n", " 9937_43040 9937_30722\n", "
\n", " +0.246\n", " \n", " 9937_43011\n", "
\n", " +0.216\n", " \n", " 9937_30722 9937_43040\n", "
\n", " +0.203\n", " \n", " 9937_30721\n", "
\n", " +0.152\n", " \n", " 9937_30722 9937_30722\n", "
\n", " +0.151\n", " \n", " 9937_30722 9937_43040 9937_30722\n", "
\n", " +0.141\n", " \n", " 9937_43011 9937_30722\n", "
\n", " … 752 more positive …\n", "
\n", " … 49239 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.480\n", " \n", " 7716_3251\n", "
\n", " +0.404\n", " \n", " 9716_32507\n", "
\n", " +0.330\n", " \n", " 7716_60475\n", "
\n", " +0.269\n", " \n", " 9716_32507 7716_3251\n", "
\n", " +0.233\n", " \n", " 7716_3251 9716_32507\n", "
\n", " +0.208\n", " \n", " 7752_8399\n", "
\n", " +0.188\n", " \n", " 7716_32502\n", "
\n", " +0.179\n", " \n", " 7716_60475 9716_32507\n", "
\n", " +0.129\n", " \n", " 7716_3251 7716_60475\n", "
\n", " +0.125\n", " \n", " 9716_32507 7716_60475\n", "
\n", " … 425 more positive …\n", "
\n", " … 49566 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.540\n", " \n", " 9716_56834\n", "
\n", " +0.484\n", " \n", " 9716_25356\n", "
\n", " +0.299\n", " \n", " 9716_25356 9716_56834\n", "
\n", " +0.296\n", " \n", " 9716_56834 9716_25356\n", "
\n", " +0.178\n", " \n", " 9716_56834 9716_56834\n", "
\n", " +0.152\n", " \n", " 9900_10753\n", "
\n", " +0.136\n", " \n", " 9716_25345\n", "
\n", " +0.134\n", " \n", " 9716_56834 9716_25356 9716_56834\n", "
\n", " +0.129\n", " \n", " 9716_25356 9716_56834 9716_25356\n", "
\n", " +0.127\n", " \n", " 9716_25356 9716_25356\n", "
\n", " … 500 more positive …\n", "
\n", " … 49491 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.584\n", " \n", " 7764_2759\n", "
\n", " +0.541\n", " \n", " 9764_2755\n", "
\n", " +0.248\n", " \n", " 7764_2759 9764_2755\n", "
\n", " +0.243\n", " \n", " 9764_2755 7764_2759\n", "
\n", " +0.209\n", " \n", " 7764_2770\n", "
\n", " +0.156\n", " \n", " 9764_2763\n", "
\n", " +0.137\n", " \n", " 7764_2759 9764_2755 7764_2759\n", "
\n", " +0.128\n", " \n", " 9764_2755 9764_2755\n", "
\n", " +0.126\n", " \n", " 7764_2759 7764_2759\n", "
\n", " +0.107\n", " \n", " 9764_2755 7764_2759 9764_2755\n", "
\n", " … 326 more positive …\n", "
\n", " … 49665 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.562\n", " \n", " 5022_19797\n", "
\n", " +0.534\n", " \n", " 9041_55813\n", "
\n", " +0.248\n", " \n", " 9041_36101\n", "
\n", " +0.235\n", " \n", " 5022_61065\n", "
\n", " +0.177\n", " \n", " 5022_19797 5022_19797\n", "
\n", " +0.171\n", " \n", " 9041_36098\n", "
\n", " +0.171\n", " \n", " 5022_19793\n", "
\n", " +0.153\n", " \n", " 9700_62979\n", "
\n", " +0.153\n", " \n", " 9774_50693\n", "
\n", " +0.111\n", " \n", " 7716_3672\n", "
\n", " … 19 more positive …\n", "
\n", " … 49972 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.352\n", " \n", " 9734_12832 9734_12803 9734_12832\n", "
\n", " +0.317\n", " \n", " 9734_12832 9734_12803\n", "
\n", " +0.311\n", " \n", " 9734_12803 9734_12832\n", "
\n", " +0.309\n", " \n", " 9734_12803 9734_12832 9734_12803\n", "
\n", " +0.305\n", " \n", " 9937_59393\n", "
\n", " +0.305\n", " \n", " 9937_59404\n", "
\n", " +0.259\n", " \n", " 9734_12803\n", "
\n", " +0.259\n", " \n", " 9734_12832\n", "
\n", " +0.239\n", " \n", " 9937_59404 9937_59393\n", "
\n", " +0.233\n", " \n", " 9937_59393 9937_59404\n", "
\n", " … 575 more positive …\n", "
\n", " … 49416 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.582\n", " \n", " 7716_3251\n", "
\n", " +0.342\n", " \n", " 9716_32506\n", "
\n", " +0.339\n", " \n", " 9716_32507\n", "
\n", " +0.241\n", " \n", " 7716_3251 9716_32507\n", "
\n", " +0.225\n", " \n", " 7716_3251 7716_3251\n", "
\n", " +0.220\n", " \n", " 9716_32507 7716_3251\n", "
\n", " +0.182\n", " \n", " 9716_32506 7716_3251\n", "
\n", " +0.165\n", " \n", " 7716_3251 9716_32506\n", "
\n", " +0.127\n", " \n", " 9716_32506 9716_32506\n", "
\n", " +0.123\n", " \n", " 7716_3251 7716_3251 9716_32507\n", "
\n", " … 351 more positive …\n", "
\n", " … 49640 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.483\n", " \n", " 9916_9988\n", "
\n", " +0.451\n", " \n", " 9916_15873\n", "
\n", " +0.343\n", " \n", " 9916_9986\n", "
\n", " +0.293\n", " \n", " 9916_10006\n", "
\n", " +0.209\n", " \n", " 9916_15873 9916_9988\n", "
\n", " +0.203\n", " \n", " 9916_9988 9916_15873\n", "
\n", " +0.161\n", " \n", " 9916_9986 9916_15873\n", "
\n", " +0.124\n", " \n", " 9916_9988 9916_9986\n", "
\n", " +0.121\n", " \n", " 9916_9986 9916_9988\n", "
\n", " +0.121\n", " \n", " 9916_15873 9916_9986\n", "
\n", " … 584 more positive …\n", "
\n", " … 49407 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.465\n", " \n", " 9713_40962\n", "
\n", " +0.282\n", " \n", " 9713_18692\n", "
\n", " +0.268\n", " \n", " 9739_10508\n", "
\n", " +0.264\n", " \n", " 9739_10497\n", "
\n", " +0.251\n", " \n", " 9713_6406\n", "
\n", " +0.197\n", " \n", " 9935_48386\n", "
\n", " +0.183\n", " \n", " 9739_10497 9739_10508\n", "
\n", " +0.147\n", " \n", " 9916_52228\n", "
\n", " +0.140\n", " \n", " 9739_10508 9739_10497\n", "
\n", " +0.130\n", " \n", " 9739_61189\n", "
\n", " … 637 more positive …\n", "
\n", " … 49354 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.414\n", " \n", " 9716_13058\n", "
\n", " +0.296\n", " \n", " 5000_45569\n", "
\n", " +0.261\n", " \n", " 5000_45580\n", "
\n", " +0.259\n", " \n", " 5000_45569 5000_45580\n", "
\n", " +0.237\n", " \n", " 5000_45580 5000_45569\n", "
\n", " +0.236\n", " \n", " 9716_25346\n", "
\n", " +0.222\n", " \n", " 5000_45569 5000_45580 5000_45569\n", "
\n", " +0.178\n", " \n", " 5000_45580 5000_45569 5000_45580\n", "
\n", " +0.177\n", " \n", " 9716_25346 9716_13058\n", "
\n", " +0.167\n", " \n", " 9716_13058 9716_25346\n", "
\n", " … 104 more positive …\n", "
\n", " … 49887 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.513\n", " \n", " 7700_30030\n", "
\n", " +0.332\n", " \n", " 9758_43523\n", "
\n", " +0.296\n", " \n", " 9700_30038\n", "
\n", " +0.222\n", " \n", " 9934_29445\n", "
\n", " +0.211\n", " \n", " 7700_30030 9700_30038\n", "
\n", " +0.193\n", " \n", " 9758_43521\n", "
\n", " +0.193\n", " \n", " 9934_29445 7700_30030\n", "
\n", " +0.186\n", " \n", " 7700_30030 9934_29445\n", "
\n", " +0.168\n", " \n", " 9700_30038 7700_30030\n", "
\n", " +0.159\n", " \n", " 9758_43523 9758_43521\n", "
\n", " … 660 more positive …\n", "
\n", " … 49331 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.595\n", " \n", " 5078_8747\n", "
\n", " +0.327\n", " \n", " 9052_46594\n", "
\n", " +0.244\n", " \n", " 5060_40884\n", "
\n", " +0.208\n", " \n", " 9716_37142\n", "
\n", " +0.208\n", " \n", " 5060_41625\n", "
\n", " +0.186\n", " \n", " 9716_37122\n", "
\n", " +0.179\n", " \n", " 9716_37142 9716_37122\n", "
\n", " +0.171\n", " \n", " 9716_37122 9716_37142\n", "
\n", " +0.164\n", " \n", " 9716_37142 9716_37122 9716_37142\n", "
\n", " +0.149\n", " \n", " 9716_37122 9716_37142 9716_37122\n", "
\n", " … 304 more positive …\n", "
\n", " … 49687 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.384\n", " \n", " 9701_40470\n", "
\n", " +0.373\n", " \n", " 9701_40450\n", "
\n", " +0.261\n", " \n", " 9701_40450 9701_40470\n", "
\n", " +0.244\n", " \n", " 9701_40470 9701_40450\n", "
\n", " +0.227\n", " \n", " 9059_29185\n", "
\n", " +0.220\n", " \n", " 9730_6915\n", "
\n", " +0.208\n", " \n", " 9730_34818\n", "
\n", " +0.208\n", " \n", " 9059_29187\n", "
\n", " +0.163\n", " \n", " 9739_22530\n", "
\n", " +0.162\n", " \n", " 9701_40450 9701_40470 9701_40450\n", "
\n", " … 788 more positive …\n", "
\n", " … 49203 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.367\n", " \n", " 7752_1389\n", "
\n", " +0.300\n", " \n", " 7716_31988\n", "
\n", " +0.205\n", " \n", " 9716_39954\n", "
\n", " +0.204\n", " \n", " 7753_62669\n", "
\n", " +0.183\n", " \n", " 7752_1390\n", "
\n", " +0.176\n", " \n", " 7716_36160\n", "
\n", " +0.172\n", " \n", " 7753_6136\n", "
\n", " +0.172\n", " \n", " 7730_3805\n", "
\n", " +0.162\n", " \n", " 9716_31989\n", "
\n", " +0.158\n", " \n", " 7716_60325\n", "
\n", " … 241 more positive …\n", "
\n", " … 49750 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.428\n", " \n", " 7752_1942\n", "
\n", " +0.330\n", " \n", " 7752_1960\n", "
\n", " +0.261\n", " \n", " 7752_1942 7752_1960\n", "
\n", " +0.252\n", " \n", " 7716_940\n", "
\n", " +0.245\n", " \n", " 7752_1960 7752_1942\n", "
\n", " +0.208\n", " \n", " 7716_925\n", "
\n", " +0.196\n", " \n", " 7752_1942 7752_1960 7752_1942\n", "
\n", " +0.160\n", " \n", " 7745_55705\n", "
\n", " +0.152\n", " \n", " 7752_1960 7752_1942 7752_1960\n", "
\n", " +0.145\n", " \n", " 7745_14141\n", "
\n", " … 287 more positive …\n", "
\n", " … 49704 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.445\n", " \n", " 9916_42508\n", "
\n", " +0.411\n", " \n", " 9916_42497\n", "
\n", " +0.288\n", " \n", " 9916_42508 9916_42497\n", "
\n", " +0.277\n", " \n", " 9916_42497 9916_42508\n", "
\n", " +0.269\n", " \n", " 9732_39180\n", "
\n", " +0.187\n", " \n", " 9916_42508 9916_42497 9916_42508\n", "
\n", " +0.179\n", " \n", " 9916_42497 9916_42508 9916_42497\n", "
\n", " +0.171\n", " \n", " 9732_39169\n", "
\n", " +0.165\n", " \n", " 7752_1911\n", "
\n", " +0.160\n", " \n", " 9732_39169 9732_39180\n", "
\n", " … 509 more positive …\n", "
\n", " … 49482 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.405\n", " \n", " 9734_33286\n", "
\n", " +0.342\n", " \n", " 9734_33283\n", "
\n", " +0.308\n", " \n", " 7716_3253\n", "
\n", " +0.269\n", " \n", " 9734_33312\n", "
\n", " +0.198\n", " \n", " 9734_33286 9734_33283\n", "
\n", " +0.180\n", " \n", " 9916_35841\n", "
\n", " +0.179\n", " \n", " 9734_33283 9734_33286\n", "
\n", " +0.151\n", " \n", " 9734_33312 9734_33283\n", "
\n", " +0.148\n", " \n", " 5050_63489\n", "
\n", " +0.143\n", " \n", " 9916_35852\n", "
\n", " … 791 more positive …\n", "
\n", " … 49200 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.524\n", " \n", " 9716_33832\n", "
\n", " +0.359\n", " \n", " 7716_55674\n", "
\n", " +0.310\n", " \n", " 9716_1797\n", "
\n", " +0.264\n", " \n", " 7716_55674 9716_33832\n", "
\n", " +0.256\n", " \n", " 9716_33832 7716_55674\n", "
\n", " +0.210\n", " \n", " 9716_33837\n", "
\n", " +0.174\n", " \n", " 7716_55674 9716_33832 7716_55674\n", "
\n", " +0.165\n", " \n", " 9716_33832 9716_33832\n", "
\n", " +0.145\n", " \n", " 9716_33832 9716_1797\n", "
\n", " +0.132\n", " \n", " 9716_1797 9716_33832\n", "
\n", " … 305 more positive …\n", "
\n", " … 49686 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.443\n", " \n", " 9734_47110\n", "
\n", " +0.387\n", " \n", " 9716_2265\n", "
\n", " +0.311\n", " \n", " 9716_2265 9734_47110\n", "
\n", " +0.302\n", " \n", " 9734_47110 9716_2265\n", "
\n", " +0.199\n", " \n", " 9937_30722\n", "
\n", " +0.189\n", " \n", " 9734_47110 9716_2265 9734_47110\n", "
\n", " +0.162\n", " \n", " 9937_30722 9937_30722\n", "
\n", " +0.162\n", " \n", " 9937_30722 9937_30722 9937_30722\n", "
\n", " +0.155\n", " \n", " 9937_30721\n", "
\n", " +0.145\n", " \n", " 9716_34956\n", "
\n", " … 176 more positive …\n", "
\n", " … 49815 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.438\n", " \n", " 9916_19488\n", "
\n", " +0.362\n", " \n", " 9916_19459\n", "
\n", " +0.326\n", " \n", " 9916_19459 9916_19488\n", "
\n", " +0.307\n", " \n", " 9916_19488 9916_19459\n", "
\n", " +0.231\n", " \n", " 9916_19488 9916_19459 9916_19488\n", "
\n", " +0.217\n", " \n", " 9005_26113\n", "
\n", " +0.212\n", " \n", " 9916_19459 9916_19488 9916_19459\n", "
\n", " +0.193\n", " \n", " 9754_63776\n", "
\n", " +0.180\n", " \n", " 9754_63747\n", "
\n", " +0.146\n", " \n", " 9005_46593\n", "
\n", " … 565 more positive …\n", "
\n", " … 49426 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.342\n", " \n", " 9716_44960\n", "
\n", " +0.341\n", " \n", " 7746_6325\n", "
\n", " +0.330\n", " \n", " 7745_1270\n", "
\n", " +0.266\n", " \n", " 9746_6313\n", "
\n", " +0.256\n", " \n", " 7746_6314\n", "
\n", " +0.228\n", " \n", " 9746_16332\n", "
\n", " +0.186\n", " \n", " 7745_8223\n", "
\n", " +0.186\n", " \n", " 9746_6313 7746_6314\n", "
\n", " +0.151\n", " \n", " 9736_54785\n", "
\n", " +0.150\n", " \n", " 9716_33093\n", "
\n", " … 104 more positive …\n", "
\n", " … 49887 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.573\n", " \n", " 9754_51202\n", "
\n", " +0.370\n", " \n", " 9754_51222\n", "
\n", " +0.229\n", " \n", " 9754_51202 9754_51222\n", "
\n", " +0.192\n", " \n", " 9754_51222 9754_51202\n", "
\n", " +0.182\n", " \n", " 9739_29953\n", "
\n", " +0.173\n", " \n", " 9934_6659\n", "
\n", " +0.163\n", " \n", " 9739_10500\n", "
\n", " +0.159\n", " \n", " 9739_22529\n", "
\n", " +0.159\n", " \n", " 9739_29953 9754_51202\n", "
\n", " +0.153\n", " \n", " 9754_51202 9754_51222 9754_51202\n", "
\n", " … 793 more positive …\n", "
\n", " … 49198 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.709\n", " \n", " 9716_31788\n", "
\n", " +0.237\n", " \n", " 9716_31788 9746_16332\n", "
\n", " +0.229\n", " \n", " 9746_16332 9716_31788\n", "
\n", " +0.217\n", " \n", " 9746_16332\n", "
\n", " +0.214\n", " \n", " 9716_31788 9746_16331\n", "
\n", " +0.205\n", " \n", " 9746_16331\n", "
\n", " +0.199\n", " \n", " 9746_16331 9716_31788\n", "
\n", " +0.184\n", " \n", " 9716_31788 9746_16332 9716_31788\n", "
\n", " +0.161\n", " \n", " 9716_31788 9746_16331 9716_31788\n", "
\n", " +0.158\n", " \n", " 9716_31788 9716_31788\n", "
\n", " … 170 more positive …\n", "
\n", " … 49821 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.393\n", " \n", " 7716_1843\n", "
\n", " +0.349\n", " \n", " 7716_1840\n", "
\n", " +0.306\n", " \n", " 9716_1841\n", "
\n", " +0.282\n", " \n", " 7752_1941\n", "
\n", " +0.257\n", " \n", " 7716_1842\n", "
\n", " +0.249\n", " \n", " 7752_1959\n", "
\n", " +0.191\n", " \n", " 7752_1941 7752_1959\n", "
\n", " +0.170\n", " \n", " 7752_1959 7752_1941\n", "
\n", " +0.160\n", " \n", " 5022_19540\n", "
\n", " +0.153\n", " \n", " 5022_52187\n", "
\n", " … 151 more positive …\n", "
\n", " … 49840 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.409\n", " \n", " 9716_19971\n", "
\n", " +0.344\n", " \n", " 9937_43040\n", "
\n", " +0.278\n", " \n", " 9937_43011\n", "
\n", " +0.258\n", " \n", " 9716_20000\n", "
\n", " +0.234\n", " \n", " 9716_56835\n", "
\n", " +0.218\n", " \n", " 9937_43040 9937_43011\n", "
\n", " +0.206\n", " \n", " 9937_43011 9937_43040\n", "
\n", " +0.197\n", " \n", " 9716_20000 9716_19971\n", "
\n", " +0.184\n", " \n", " 9716_19971 9716_20000\n", "
\n", " +0.154\n", " \n", " 9716_19974\n", "
\n", " … 798 more positive …\n", "
\n", " … 49193 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.323\n", " \n", " 9716_39937\n", "
\n", " +0.305\n", " \n", " 9716_39948\n", "
\n", " +0.305\n", " \n", " 9739_22531\n", "
\n", " +0.262\n", " \n", " 9716_18178\n", "
\n", " +0.198\n", " \n", " 9916_20246\n", "
\n", " +0.197\n", " \n", " 9716_39940\n", "
\n", " +0.182\n", " \n", " 9916_20226\n", "
\n", " +0.174\n", " \n", " 9716_22529\n", "
\n", " +0.140\n", " \n", " 9735_19478\n", "
\n", " +0.133\n", " \n", " 9739_22531 9716_39948\n", "
\n", " … 887 more positive …\n", "
\n", " … 49104 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.380\n", " \n", " 9739_52738\n", "
\n", " +0.345\n", " \n", " 9739_52758\n", "
\n", " +0.320\n", " \n", " 9739_52741\n", "
\n", " +0.289\n", " \n", " 9934_51714\n", "
\n", " +0.265\n", " \n", " 9934_39426\n", "
\n", " +0.199\n", " \n", " 9739_52738 9739_52758\n", "
\n", " +0.184\n", " \n", " 9739_52741 9739_52738\n", "
\n", " +0.166\n", " \n", " 9739_52758 9739_52738\n", "
\n", " +0.120\n", " \n", " 9934_43523\n", "
\n", " +0.117\n", " \n", " 9739_52738 9739_52741\n", "
\n", " … 918 more positive …\n", "
\n", " … 49073 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.314\n", " \n", " 9734_12801\n", "
\n", " +0.311\n", " \n", " 9734_12812\n", "
\n", " +0.298\n", " \n", " 9916_20226\n", "
\n", " +0.275\n", " \n", " 9916_20246\n", "
\n", " +0.234\n", " \n", " 9734_33302\n", "
\n", " +0.172\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.172\n", " \n", " 9734_12812 9734_12801\n", "
\n", " +0.169\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.159\n", " \n", " 9734_33282\n", "
\n", " +0.139\n", " \n", " 9916_65292\n", "
\n", " … 944 more positive …\n", "
\n", " … 49047 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.351\n", " \n", " 9916_65292\n", "
\n", " +0.317\n", " \n", " 9916_65281\n", "
\n", " +0.279\n", " \n", " 9916_20226\n", "
\n", " +0.277\n", " \n", " 9916_20246\n", "
\n", " +0.211\n", " \n", " 9716_7173\n", "
\n", " +0.190\n", " \n", " 9735_47884\n", "
\n", " +0.189\n", " \n", " 9745_10037\n", "
\n", " +0.168\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.158\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.139\n", " \n", " 9916_65281 9916_65292\n", "
\n", " … 1053 more positive …\n", "
\n", " … 48938 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.283\n", " \n", " 9716_7200\n", "
\n", " +0.249\n", " \n", " 9716_48406\n", "
\n", " +0.246\n", " \n", " 9916_20236\n", "
\n", " +0.223\n", " \n", " 9716_7190\n", "
\n", " +0.211\n", " \n", " 9916_20225\n", "
\n", " +0.174\n", " \n", " 9716_48386\n", "
\n", " +0.168\n", " \n", " 9716_7171\n", "
\n", " +0.163\n", " \n", " 9903_50690\n", "
\n", " +0.148\n", " \n", " 9716_7171 9716_7200\n", "
\n", " +0.145\n", " \n", " 9716_7200 9716_7171\n", "
\n", " … 773 more positive …\n", "
\n", " … 49218 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.469\n", " \n", " 9716_3144\n", "
\n", " +0.430\n", " \n", " 7716_3155\n", "
\n", " +0.283\n", " \n", " 7716_6028\n", "
\n", " +0.262\n", " \n", " 9716_3145\n", "
\n", " +0.251\n", " \n", " 7716_37505\n", "
\n", " +0.213\n", " \n", " 9716_3144 7716_3155\n", "
\n", " +0.210\n", " \n", " 7716_3155 9716_3144\n", "
\n", " +0.154\n", " \n", " 7716_3154\n", "
\n", " +0.140\n", " \n", " 9716_3145 7716_3155\n", "
\n", " +0.138\n", " \n", " 9716_3144 9716_3144\n", "
\n", " … 470 more positive …\n", "
\n", " … 49521 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.742\n", " \n", " 7716_65294\n", "
\n", " +0.271\n", " \n", " 7716_65294 7716_65294\n", "
\n", " +0.237\n", " \n", " 9716_33099\n", "
\n", " +0.196\n", " \n", " 9716_33099 7716_65294\n", "
\n", " +0.190\n", " \n", " 7716_65294 9716_33099\n", "
\n", " +0.145\n", " \n", " 7716_65294 9716_33099 7716_65294\n", "
\n", " +0.111\n", " \n", " 9716_33096\n", "
\n", " +0.109\n", " \n", " 9716_65413\n", "
\n", " +0.104\n", " \n", " 9716_33099 7716_65294 9716_33099\n", "
\n", " +0.103\n", " \n", " 7716_65294 9716_33096\n", "
\n", " … 364 more positive …\n", "
\n", " … 49627 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.371\n", " \n", " 9916_20226\n", "
\n", " +0.346\n", " \n", " 9916_20246\n", "
\n", " +0.271\n", " \n", " 9734_61702\n", "
\n", " +0.200\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.196\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.192\n", " \n", " 9734_61728\n", "
\n", " +0.170\n", " \n", " 9734_61699\n", "
\n", " +0.169\n", " \n", " 9916_17409\n", "
\n", " +0.136\n", " \n", " 9916_17420\n", "
\n", " +0.125\n", " \n", " 9734_16642\n", "
\n", " … 988 more positive …\n", "
\n", " … 49003 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.399\n", " \n", " 9937_43011\n", "
\n", " +0.355\n", " \n", " 9937_43040\n", "
\n", " +0.302\n", " \n", " 9937_43040 9937_43011\n", "
\n", " +0.291\n", " \n", " 9937_43011 9937_43040\n", "
\n", " +0.231\n", " \n", " 9937_43011 9937_43040 9937_43011\n", "
\n", " +0.205\n", " \n", " 9937_43040 9937_43011 9937_43040\n", "
\n", " +0.173\n", " \n", " 9909_50700\n", "
\n", " +0.152\n", " \n", " 9937_34817\n", "
\n", " +0.134\n", " \n", " 9758_11788\n", "
\n", " +0.133\n", " \n", " 9909_50689\n", "
\n", " … 962 more positive …\n", "
\n", " … 49029 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.344\n", " \n", " 9916_20225\n", "
\n", " +0.339\n", " \n", " 9916_20236\n", "
\n", " +0.288\n", " \n", " 9916_20236 9916_20225\n", "
\n", " +0.286\n", " \n", " 9716_4098\n", "
\n", " +0.274\n", " \n", " 9916_20225 9916_20236\n", "
\n", " +0.246\n", " \n", " 9716_4118\n", "
\n", " +0.225\n", " \n", " 9916_20236 9916_20225 9916_20236\n", "
\n", " +0.206\n", " \n", " 9916_20225 9916_20236 9916_20225\n", "
\n", " +0.200\n", " \n", " 9716_54038\n", "
\n", " +0.181\n", " \n", " 9043_40198\n", "
\n", " … 775 more positive …\n", "
\n", " … 49216 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.494\n", " \n", " 7752_40574\n", "
\n", " +0.337\n", " \n", " 7752_40452\n", "
\n", " +0.329\n", " \n", " 7716_55662\n", "
\n", " +0.249\n", " \n", " 7752_40454\n", "
\n", " +0.185\n", " \n", " 9716_61253\n", "
\n", " +0.168\n", " \n", " 7752_40574 7752_40454\n", "
\n", " +0.168\n", " \n", " 7752_40452 7752_40574\n", "
\n", " +0.158\n", " \n", " 7716_55662 9716_61253\n", "
\n", " +0.156\n", " \n", " 9752_40793\n", "
\n", " +0.138\n", " \n", " 7716_32952\n", "
\n", " … 261 more positive …\n", "
\n", " … 49730 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.600\n", " \n", " 9716_62011\n", "
\n", " +0.372\n", " \n", " 7716_55654\n", "
\n", " +0.273\n", " \n", " 7716_55654 9716_62011\n", "
\n", " +0.245\n", " \n", " 9716_62011 7716_55654\n", "
\n", " +0.176\n", " \n", " 9716_62011 9716_62011\n", "
\n", " +0.152\n", " \n", " 7700_33799\n", "
\n", " +0.145\n", " \n", " 9716_62011 7716_55654 9716_62011\n", "
\n", " +0.131\n", " \n", " 7716_49282\n", "
\n", " +0.128\n", " \n", " 7700_1152\n", "
\n", " +0.125\n", " \n", " 9716_62011 7716_49282\n", "
\n", " … 557 more positive …\n", "
\n", " … 49434 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.403\n", " \n", " 9701_49153\n", "
\n", " +0.268\n", " \n", " 9934_35842\n", "
\n", " +0.255\n", " \n", " 9701_49153 9934_35842\n", "
\n", " +0.254\n", " \n", " 9701_49156\n", "
\n", " +0.246\n", " \n", " 9934_35842 9701_49153\n", "
\n", " +0.200\n", " \n", " 9934_35862\n", "
\n", " +0.195\n", " \n", " 9701_49153 9934_35842 9701_49153\n", "
\n", " +0.165\n", " \n", " 9735_27660\n", "
\n", " +0.154\n", " \n", " 9701_49156 9934_35862\n", "
\n", " +0.152\n", " \n", " 9934_35842 9701_49153 9934_35842\n", "
\n", " … 780 more positive …\n", "
\n", " … 49211 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.579\n", " \n", " 7798_15404\n", "
\n", " +0.328\n", " \n", " 7798_62672\n", "
\n", " +0.218\n", " \n", " 7798_62672 7798_15404\n", "
\n", " +0.214\n", " \n", " 7755_55452\n", "
\n", " +0.197\n", " \n", " 7798_15404 7798_62672\n", "
\n", " +0.164\n", " \n", " 7798_59973\n", "
\n", " +0.159\n", " \n", " 7752_32983\n", "
\n", " +0.153\n", " \n", " 7798_34295\n", "
\n", " +0.144\n", " \n", " 7755_44696\n", "
\n", " +0.142\n", " \n", " 7798_15404 7798_15404\n", "
\n", " … 313 more positive …\n", "
\n", " … 49678 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.435\n", " \n", " 9716_30209\n", "
\n", " +0.367\n", " \n", " 9716_30220\n", "
\n", " +0.295\n", " \n", " 9716_30209 9716_30220\n", "
\n", " +0.241\n", " \n", " 9716_30220 9716_30209\n", "
\n", " +0.177\n", " \n", " 9716_30209 9716_30220 9716_30209\n", "
\n", " +0.166\n", " \n", " 9716_3841\n", "
\n", " +0.157\n", " \n", " 9716_30220 9716_30209 9716_30220\n", "
\n", " +0.120\n", " \n", " 9916_65292\n", "
\n", " +0.118\n", " \n", " 9916_65281\n", "
\n", " +0.094\n", " \n", " 9916_33025\n", "
\n", " … 1011 more positive …\n", "
\n", " … 48980 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.357\n", " \n", " 9739_29953\n", "
\n", " +0.332\n", " \n", " 9916_42753\n", "
\n", " +0.328\n", " \n", " 9916_42764\n", "
\n", " +0.268\n", " \n", " 9739_22529\n", "
\n", " +0.263\n", " \n", " 9916_42753 9916_42764\n", "
\n", " +0.240\n", " \n", " 9916_42764 9916_42753\n", "
\n", " +0.217\n", " \n", " 9754_51202\n", "
\n", " +0.209\n", " \n", " 9739_29953 9739_22529\n", "
\n", " +0.188\n", " \n", " 9916_42764 9916_42753 9916_42764\n", "
\n", " +0.186\n", " \n", " 9916_42753 9916_42764 9916_42753\n", "
\n", " … 723 more positive …\n", "
\n", " … 49268 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.343\n", " \n", " 9701_64771\n", "
\n", " +0.340\n", " \n", " 9701_64800\n", "
\n", " +0.277\n", " \n", " 9716_18433\n", "
\n", " +0.243\n", " \n", " 9701_64771 9701_64800\n", "
\n", " +0.242\n", " \n", " 9701_64800 9701_64771\n", "
\n", " +0.237\n", " \n", " 9716_4108\n", "
\n", " +0.211\n", " \n", " 9716_39942\n", "
\n", " +0.204\n", " \n", " 9716_4097\n", "
\n", " +0.201\n", " \n", " 9701_64771 9701_64800 9701_64771\n", "
\n", " +0.171\n", " \n", " 9701_64800 9701_64771 9701_64800\n", "
\n", " … 800 more positive …\n", "
\n", " … 49191 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.562\n", " \n", " 7716_902\n", "
\n", " +0.530\n", " \n", " 9734_64260\n", "
\n", " +0.279\n", " \n", " 7716_902 9734_64260\n", "
\n", " +0.270\n", " \n", " 9734_64260 7716_902\n", "
\n", " +0.218\n", " \n", " 9734_64260 9734_64260\n", "
\n", " +0.171\n", " \n", " 7716_902 7716_902\n", "
\n", " +0.137\n", " \n", " 7716_902 9734_64260 7716_902\n", "
\n", " +0.133\n", " \n", " 7716_902 9734_64260 9734_64260\n", "
\n", " +0.124\n", " \n", " 9734_64260 7716_902 9734_64260\n", "
\n", " +0.112\n", " \n", " 7716_902 7716_902 9734_64260\n", "
\n", " … 667 more positive …\n", "
\n", " … 49324 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.376\n", " \n", " 9937_38156\n", "
\n", " +0.351\n", " \n", " 9937_38145\n", "
\n", " +0.262\n", " \n", " 9937_38156 9937_38145\n", "
\n", " +0.258\n", " \n", " 9741_48901\n", "
\n", " +0.254\n", " \n", " 9937_38145 9937_38156\n", "
\n", " +0.236\n", " \n", " 7741_5928\n", "
\n", " +0.184\n", " \n", " 9014_60422\n", "
\n", " +0.180\n", " \n", " 9937_38156 9937_38145 9937_38156\n", "
\n", " +0.178\n", " \n", " 9758_34561 9758_34572\n", "
\n", " +0.177\n", " \n", " 9758_34561\n", "
\n", " … 621 more positive …\n", "
\n", " … 49370 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.476\n", " \n", " 9934_59137\n", "
\n", " +0.357\n", " \n", " 7752_59117\n", "
\n", " +0.312\n", " \n", " 9734_61702\n", "
\n", " +0.280\n", " \n", " 9734_16642\n", "
\n", " +0.277\n", " \n", " 9934_59137 7752_59117\n", "
\n", " +0.267\n", " \n", " 7752_59117 9934_59137\n", "
\n", " +0.183\n", " \n", " 9934_59137 7752_59117 9934_59137\n", "
\n", " +0.179\n", " \n", " 9734_16642 9734_61702\n", "
\n", " +0.176\n", " \n", " 9734_61702 9734_16642\n", "
\n", " +0.147\n", " \n", " 7752_59117 9934_59137 7752_59117\n", "
\n", " … 753 more positive …\n", "
\n", " … 49238 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.519\n", " \n", " 9934_56067\n", "
\n", " +0.381\n", " \n", " 9934_56076\n", "
\n", " +0.350\n", " \n", " 9934_56065\n", "
\n", " +0.197\n", " \n", " 9934_29188\n", "
\n", " +0.170\n", " \n", " 9062_51718\n", "
\n", " +0.160\n", " \n", " 9934_56076 9934_56065\n", "
\n", " +0.149\n", " \n", " 9934_56065 9934_56076\n", "
\n", " +0.146\n", " \n", " 9934_56067 9934_56076\n", "
\n", " +0.142\n", " \n", " 9934_56065 9934_56067\n", "
\n", " +0.125\n", " \n", " 9934_56067 9934_56065\n", "
\n", " … 592 more positive …\n", "
\n", " … 49399 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.440\n", " \n", " 9739_22530\n", "
\n", " +0.358\n", " \n", " 9716_2052\n", "
\n", " +0.284\n", " \n", " 9716_2052 9739_22530\n", "
\n", " +0.259\n", " \n", " 9739_22530 9716_2052\n", "
\n", " +0.251\n", " \n", " 9736_27137\n", "
\n", " +0.181\n", " \n", " 9739_22530 9716_2052 9739_22530\n", "
\n", " +0.142\n", " \n", " 9773_51468\n", "
\n", " +0.135\n", " \n", " 9739_22530 9739_22530\n", "
\n", " +0.135\n", " \n", " 9736_56070\n", "
\n", " +0.126\n", " \n", " 9773_55820\n", "
\n", " … 780 more positive …\n", "
\n", " … 49211 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.423\n", " \n", " 7755_15803\n", "
\n", " +0.409\n", " \n", " 9716_3665\n", "
\n", " +0.298\n", " \n", " 7716_3672\n", "
\n", " +0.281\n", " \n", " 7755_15811\n", "
\n", " +0.245\n", " \n", " 7755_15803 9716_3665\n", "
\n", " +0.193\n", " \n", " 9716_3665 7755_15803\n", "
\n", " +0.177\n", " \n", " 7716_3672 7755_15811\n", "
\n", " +0.172\n", " \n", " 9752_2971\n", "
\n", " +0.147\n", " \n", " 9716_33846\n", "
\n", " +0.139\n", " \n", " 7755_15811 7716_3672\n", "
\n", " … 598 more positive …\n", "
\n", " … 49393 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.439\n", " \n", " 9916_35852\n", "
\n", " +0.392\n", " \n", " 9916_35841\n", "
\n", " +0.315\n", " \n", " 9916_35841 9916_35852\n", "
\n", " +0.304\n", " \n", " 9916_35852 9916_35841\n", "
\n", " +0.299\n", " \n", " 5060_45028\n", "
\n", " +0.231\n", " \n", " 5045_45029\n", "
\n", " +0.211\n", " \n", " 5045_5896\n", "
\n", " +0.200\n", " \n", " 9916_35852 9916_35841 9916_35852\n", "
\n", " +0.200\n", " \n", " 9916_35841 9916_35852 9916_35841\n", "
\n", " +0.116\n", " \n", " 5060_45028 5045_5896\n", "
\n", " … 234 more positive …\n", "
\n", " … 49757 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.373\n", " \n", " 9916_35852\n", "
\n", " +0.309\n", " \n", " 9916_35841\n", "
\n", " +0.271\n", " \n", " 9916_35841 9916_35852\n", "
\n", " +0.265\n", " \n", " 9916_35852 9916_35841\n", "
\n", " +0.258\n", " \n", " 9754_18690\n", "
\n", " +0.214\n", " \n", " 9754_63747\n", "
\n", " +0.210\n", " \n", " 9916_35852 9916_35841 9916_35852\n", "
\n", " +0.204\n", " \n", " 9916_35841 9916_35852 9916_35841\n", "
\n", " +0.163\n", " \n", " 9754_63776\n", "
\n", " +0.149\n", " \n", " 7755_30228\n", "
\n", " … 707 more positive …\n", "
\n", " … 49284 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.562\n", " \n", " 9732_19457\n", "
\n", " +0.313\n", " \n", " 9732_39172\n", "
\n", " +0.221\n", " \n", " 9916_35841\n", "
\n", " +0.203\n", " \n", " 9732_64516\n", "
\n", " +0.200\n", " \n", " 9916_35852\n", "
\n", " +0.161\n", " \n", " 9732_1541\n", "
\n", " +0.148\n", " \n", " 9732_39172 9732_19457\n", "
\n", " +0.135\n", " \n", " 9739_34050\n", "
\n", " +0.131\n", " \n", " 9916_35841 9916_35852\n", "
\n", " +0.124\n", " \n", " 9716_43778\n", "
\n", " … 803 more positive …\n", "
\n", " … 49188 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.432\n", " \n", " 9916_35852\n", "
\n", " +0.383\n", " \n", " 9916_35841\n", "
\n", " +0.368\n", " \n", " 9916_35852 9916_35841\n", "
\n", " +0.352\n", " \n", " 9916_35841 9916_35852\n", "
\n", " +0.301\n", " \n", " 9916_35841 9916_35852 9916_35841\n", "
\n", " +0.297\n", " \n", " 9916_35852 9916_35841 9916_35852\n", "
\n", " +0.141\n", " \n", " 9716_7190\n", "
\n", " +0.125\n", " \n", " 9716_7170\n", "
\n", " +0.098\n", " \n", " 9909_49153\n", "
\n", " +0.089\n", " \n", " 9901_50945\n", "
\n", " … 926 more positive …\n", "
\n", " … 49065 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.523\n", " \n", " 9937_59393\n", "
\n", " +0.413\n", " \n", " 9937_30723\n", "
\n", " +0.349\n", " \n", " 9937_59404\n", "
\n", " +0.261\n", " \n", " 7757_7012\n", "
\n", " +0.220\n", " \n", " 9937_59393 9937_59404\n", "
\n", " +0.191\n", " \n", " 9937_30723 9937_59393\n", "
\n", " +0.177\n", " \n", " 9937_59404 9937_59393\n", "
\n", " +0.155\n", " \n", " 7757_7012 9937_30723\n", "
\n", " +0.123\n", " \n", " 9937_59393 9937_59404 9937_59393\n", "
\n", " +0.116\n", " \n", " 9937_59393 7757_7012\n", "
\n", " … 520 more positive …\n", "
\n", " … 49471 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.582\n", " \n", " 9741_24453\n", "
\n", " +0.308\n", " \n", " 7741_17689\n", "
\n", " +0.302\n", " \n", " 7741_837\n", "
\n", " +0.205\n", " \n", " 7755_872\n", "
\n", " +0.183\n", " \n", " 7752_1564\n", "
\n", " +0.171\n", " \n", " 9741_24453 7741_837\n", "
\n", " +0.168\n", " \n", " 7741_837 9741_24453\n", "
\n", " +0.168\n", " \n", " 9741_24453 9741_24453\n", "
\n", " +0.167\n", " \n", " 9741_655\n", "
\n", " +0.153\n", " \n", " 7752_1565\n", "
\n", " … 423 more positive …\n", "
\n", " … 49568 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.540\n", " \n", " 7755_7128\n", "
\n", " +0.364\n", " \n", " 7755_35929\n", "
\n", " +0.361\n", " \n", " 7755_23103\n", "
\n", " +0.338\n", " \n", " 7755_38893\n", "
\n", " +0.250\n", " \n", " 7755_38817\n", "
\n", " +0.198\n", " \n", " 7755_35948\n", "
\n", " +0.125\n", " \n", " 7755_38893 7755_7128\n", "
\n", " +0.119\n", " \n", " 7752_516\n", "
\n", " +0.111\n", " \n", " 7755_30064\n", "
\n", " +0.111\n", " \n", " 7755_7128 7755_38893\n", "
\n", " … 221 more positive …\n", "
\n", " … 49770 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.579\n", " \n", " 7716_36161\n", "
\n", " +0.371\n", " \n", " 9716_31987\n", "
\n", " +0.311\n", " \n", " 9716_31987 7716_36161\n", "
\n", " +0.298\n", " \n", " 7716_36161 7716_36161\n", "
\n", " +0.254\n", " \n", " 7716_36161 7716_36161 7716_36161\n", "
\n", " +0.246\n", " \n", " 7716_7043\n", "
\n", " +0.135\n", " \n", " 7716_7042\n", "
\n", " +0.115\n", " \n", " 7716_7043 7716_7043\n", "
\n", " +0.095\n", " \n", " 7700_36754\n", "
\n", " +0.089\n", " \n", " 7716_7043 7700_34895\n", "
\n", " … 74 more positive …\n", "
\n", " … 49917 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.486\n", " \n", " 9934_46594\n", "
\n", " +0.446\n", " \n", " 9934_46614\n", "
\n", " +0.385\n", " \n", " 9934_46614 9934_46594\n", "
\n", " +0.385\n", " \n", " 9934_46594 9934_46614\n", "
\n", " +0.331\n", " \n", " 9934_46594 9934_46614 9934_46594\n", "
\n", " +0.308\n", " \n", " 9934_46614 9934_46594 9934_46614\n", "
\n", " +0.065\n", " \n", " 9934_46594 9934_46594\n", "
\n", " +0.062\n", " \n", " 9732_40192\n", "
\n", " +0.059\n", " \n", " 9784_14614\n", "
\n", " +0.058\n", " \n", " 9934_46594 9934_46594 9934_46614\n", "
\n", " … 602 more positive …\n", "
\n", " … 49389 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.591\n", " \n", " 9752_15475\n", "
\n", " +0.316\n", " \n", " 7755_61036\n", "
\n", " +0.265\n", " \n", " 9752_15475 9752_15475\n", "
\n", " +0.228\n", " \n", " 7755_30237\n", "
\n", " +0.221\n", " \n", " 9752_15475 9752_15475 9752_15475\n", "
\n", " +0.204\n", " \n", " 7755_33346\n", "
\n", " +0.138\n", " \n", " 7755_38846\n", "
\n", " +0.128\n", " \n", " 7755_61031\n", "
\n", " +0.124\n", " \n", " 7755_33346 9700_63215 9752_14633\n", "
\n", " +0.124\n", " \n", " 9752_14633 9752_15475\n", "
\n", " … 108 more positive …\n", "
\n", " … 49883 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.623\n", " \n", " 9739_27909\n", "
\n", " +0.286\n", " \n", " 9716_1797\n", "
\n", " +0.263\n", " \n", " 9739_27909 9716_1797\n", "
\n", " +0.258\n", " \n", " 9716_1797 9739_27909\n", "
\n", " +0.231\n", " \n", " 9739_27909 9739_27909\n", "
\n", " +0.213\n", " \n", " 9716_1814\n", "
\n", " +0.184\n", " \n", " 9739_27909 9716_1814\n", "
\n", " +0.181\n", " \n", " 9716_1814 9739_27909\n", "
\n", " +0.164\n", " \n", " 9739_27909 9716_1797 9739_27909\n", "
\n", " +0.132\n", " \n", " 9716_1797 9739_27909 9716_1797\n", "
\n", " … 585 more positive …\n", "
\n", " … 49406 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.342\n", " \n", " 9934_32513\n", "
\n", " +0.241\n", " \n", " 9739_52741\n", "
\n", " +0.232\n", " \n", " 7716_3387\n", "
\n", " +0.232\n", " \n", " 9739_22530\n", "
\n", " +0.229\n", " \n", " 7716_3386\n", "
\n", " +0.215\n", " \n", " 9787_42757\n", "
\n", " +0.209\n", " \n", " 9787_42774\n", "
\n", " +0.209\n", " \n", " 9934_12037\n", "
\n", " +0.205\n", " \n", " 7755_33264\n", "
\n", " +0.188\n", " \n", " 9787_42754\n", "
\n", " … 591 more positive …\n", "
\n", " … 49400 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.645\n", " \n", " 9739_34305\n", "
\n", " +0.296\n", " \n", " 7755_6589\n", "
\n", " +0.274\n", " \n", " 9739_34305 9739_34305\n", "
\n", " +0.193\n", " \n", " 9739_34305 7755_6589\n", "
\n", " +0.193\n", " \n", " 9908_53762\n", "
\n", " +0.190\n", " \n", " 9739_61188\n", "
\n", " +0.181\n", " \n", " 9908_18947\n", "
\n", " +0.154\n", " \n", " 9739_34305 7755_6589 9739_34305\n", "
\n", " +0.145\n", " \n", " 7755_6589 9739_34305\n", "
\n", " +0.125\n", " \n", " 9739_61188 9739_61188\n", "
\n", " … 78 more positive …\n", "
\n", " … 49913 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.506\n", " \n", " 7752_3290\n", "
\n", " +0.321\n", " \n", " 7752_19475\n", "
\n", " +0.273\n", " \n", " 7752_19470\n", "
\n", " +0.246\n", " \n", " 9752_19471\n", "
\n", " +0.240\n", " \n", " 9752_1553\n", "
\n", " +0.211\n", " \n", " 7752_1564\n", "
\n", " +0.207\n", " \n", " 7745_10345\n", "
\n", " +0.199\n", " \n", " 9752_10501\n", "
\n", " +0.150\n", " \n", " 7752_55304\n", "
\n", " +0.136\n", " \n", " 7752_3290 7752_3290\n", "
\n", " … 435 more positive …\n", "
\n", " … 49556 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.455\n", " \n", " 9739_3333\n", "
\n", " +0.322\n", " \n", " 9935_53505\n", "
\n", " +0.292\n", " \n", " 9935_53516\n", "
\n", " +0.238\n", " \n", " 9935_53516 9935_53505\n", "
\n", " +0.217\n", " \n", " 9935_53505 9935_53516\n", "
\n", " +0.206\n", " \n", " 9739_3333 9716_7169\n", "
\n", " +0.187\n", " \n", " 9935_53516 9935_53505 9935_53516\n", "
\n", " +0.181\n", " \n", " 9716_7169\n", "
\n", " +0.178\n", " \n", " 9716_7169 9739_3333\n", "
\n", " +0.166\n", " \n", " 9935_53505 9935_53516 9935_53505\n", "
\n", " … 717 more positive …\n", "
\n", " … 49274 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.374\n", " \n", " 7716_3497\n", "
\n", " +0.345\n", " \n", " 9752_34072\n", "
\n", " +0.306\n", " \n", " 9716_34958\n", "
\n", " +0.301\n", " \n", " 7752_8584\n", "
\n", " +0.234\n", " \n", " 9716_34958 7716_3497\n", "
\n", " +0.201\n", " \n", " 7716_3497 9716_34958\n", "
\n", " +0.187\n", " \n", " 9752_34072 7752_8584\n", "
\n", " +0.140\n", " \n", " 7765_65407\n", "
\n", " +0.140\n", " \n", " 7758_3316\n", "
\n", " +0.140\n", " \n", " 7752_354\n", "
\n", " … 288 more positive …\n", "
\n", " … 49703 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.324\n", " \n", " 9953_37016\n", "
\n", " +0.304\n", " \n", " 9752_12949\n", "
\n", " +0.282\n", " \n", " 9716_33229\n", "
\n", " +0.236\n", " \n", " 9709_7021\n", "
\n", " +0.235\n", " \n", " 9953_37016 9716_33229\n", "
\n", " +0.189\n", " \n", " 9953_34366\n", "
\n", " +0.182\n", " \n", " 9716_34606\n", "
\n", " +0.182\n", " \n", " 9716_33229 9953_37016\n", "
\n", " +0.181\n", " \n", " 9716_34606 7730_3431\n", "
\n", " +0.164\n", " \n", " 7730_3431\n", "
\n", " … 207 more positive …\n", "
\n", " … 49784 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.499\n", " \n", " 9934_39427\n", "
\n", " +0.337\n", " \n", " 9732_63233\n", "
\n", " +0.234\n", " \n", " 9733_53254\n", "
\n", " +0.213\n", " \n", " 9934_39427 9934_45313\n", "
\n", " +0.212\n", " \n", " 9732_63233 9733_53254\n", "
\n", " +0.201\n", " \n", " 9934_45313\n", "
\n", " +0.194\n", " \n", " 9934_45313 9934_39427\n", "
\n", " +0.163\n", " \n", " 9934_39427 9934_39427\n", "
\n", " +0.145\n", " \n", " 9934_45324\n", "
\n", " +0.145\n", " \n", " 9934_45324 9934_39427\n", "
\n", " … 861 more positive …\n", "
\n", " … 49130 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.542\n", " \n", " 9754_14283\n", "
\n", " +0.477\n", " \n", " 7754_14282\n", "
\n", " +0.255\n", " \n", " 7746_16336\n", "
\n", " +0.248\n", " \n", " 9754_14283 7754_14282\n", "
\n", " +0.230\n", " \n", " 7754_14282 9754_14283\n", "
\n", " +0.177\n", " \n", " 7754_37034\n", "
\n", " +0.173\n", " \n", " 9754_14283 9754_14283\n", "
\n", " +0.168\n", " \n", " 7716_39675\n", "
\n", " +0.141\n", " \n", " 7754_14282 7754_14282\n", "
\n", " +0.131\n", " \n", " 7746_16336 7716_39675\n", "
\n", " … 319 more positive …\n", "
\n", " … 49672 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.436\n", " \n", " 9782_41740\n", "
\n", " +0.415\n", " \n", " 9782_41729\n", "
\n", " +0.332\n", " \n", " 5032_60676\n", "
\n", " +0.207\n", " \n", " 9782_41729 9782_41740\n", "
\n", " +0.199\n", " \n", " 9782_41730\n", "
\n", " +0.199\n", " \n", " 9782_41750\n", "
\n", " +0.194\n", " \n", " 9782_41740 9782_41729\n", "
\n", " +0.136\n", " \n", " 9739_29957\n", "
\n", " +0.133\n", " \n", " 9934_45313\n", "
\n", " +0.133\n", " \n", " 9782_41740 9782_41729 9782_41740\n", "
\n", " … 772 more positive …\n", "
\n", " … 49219 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.330\n", " \n", " 9734_12832\n", "
\n", " +0.286\n", " \n", " 9734_12803\n", "
\n", " +0.276\n", " \n", " 9916_62467\n", "
\n", " +0.268\n", " \n", " 9916_62496\n", "
\n", " +0.262\n", " \n", " 9916_62467 9916_62496\n", "
\n", " +0.253\n", " \n", " 9734_12832 9734_12803\n", "
\n", " +0.252\n", " \n", " 9916_62496 9916_62467\n", "
\n", " +0.249\n", " \n", " 9734_12803 9734_12832\n", "
\n", " +0.237\n", " \n", " 9734_12832 9734_12803 9734_12832\n", "
\n", " +0.222\n", " \n", " 9758_5900\n", "
\n", " … 435 more positive …\n", "
\n", " … 49556 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.474\n", " \n", " 9746_38506\n", "
\n", " +0.327\n", " \n", " 9953_6545\n", "
\n", " +0.262\n", " \n", " 9746_38506 9953_6545\n", "
\n", " +0.232\n", " \n", " 9746_38506 9746_38506\n", "
\n", " +0.221\n", " \n", " 9953_6545 9746_38506\n", "
\n", " +0.196\n", " \n", " 9709_3657\n", "
\n", " +0.190\n", " \n", " 9746_38506 9746_38506 9953_6545\n", "
\n", " +0.169\n", " \n", " 9746_38506 9953_6545 9716_33229\n", "
\n", " +0.168\n", " \n", " 9953_6545 9716_33229 7730_3431\n", "
\n", " +0.156\n", " \n", " 9953_6545 9716_33229\n", "
\n", " … 180 more positive …\n", "
\n", " … 49811 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.589\n", " \n", " 9716_33025\n", "
\n", " +0.303\n", " \n", " 9716_30211\n", "
\n", " +0.220\n", " \n", " 9716_61956\n", "
\n", " +0.216\n", " \n", " 9716_31062\n", "
\n", " +0.197\n", " \n", " 9716_16897\n", "
\n", " +0.186\n", " \n", " 7716_28965\n", "
\n", " +0.160\n", " \n", " 7716_28965 9716_33025\n", "
\n", " +0.143\n", " \n", " 9716_33025 7716_28965\n", "
\n", " +0.137\n", " \n", " 9716_33025 9716_33025\n", "
\n", " +0.125\n", " \n", " 9935_14338\n", "
\n", " … 667 more positive …\n", "
\n", " … 49324 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.504\n", " \n", " 9716_1841\n", "
\n", " +0.449\n", " \n", " 7716_1843\n", "
\n", " +0.311\n", " \n", " 7716_1840\n", "
\n", " +0.298\n", " \n", " 7716_1843 9716_1841\n", "
\n", " +0.279\n", " \n", " 9716_1841 7716_1843\n", "
\n", " +0.189\n", " \n", " 9716_1841 7716_1840\n", "
\n", " +0.175\n", " \n", " 7716_1843 9716_1841 7716_1843\n", "
\n", " +0.134\n", " \n", " 7716_1840 9716_1841\n", "
\n", " +0.129\n", " \n", " 9716_1841 7716_1843 9716_1841\n", "
\n", " +0.103\n", " \n", " 7716_1843 7716_1843\n", "
\n", " … 180 more positive …\n", "
\n", " … 49811 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.405\n", " \n", " 9700_730\n", "
\n", " +0.390\n", " \n", " 9754_3559\n", "
\n", " +0.333\n", " \n", " 9716_33837\n", "
\n", " +0.322\n", " \n", " 9754_44237\n", "
\n", " +0.208\n", " \n", " 9745_10308\n", "
\n", " +0.160\n", " \n", " 9745_47196\n", "
\n", " +0.146\n", " \n", " 9700_10537\n", "
\n", " +0.142\n", " \n", " 9754_3559 9700_730\n", "
\n", " +0.139\n", " \n", " 9754_44237 9700_10537\n", "
\n", " +0.137\n", " \n", " 9716_7033\n", "
\n", " … 211 more positive …\n", "
\n", " … 49780 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.369\n", " \n", " 7755_41965\n", "
\n", " +0.272\n", " \n", " 7755_41961\n", "
\n", " +0.263\n", " \n", " 9752_14633 9752_19184\n", "
\n", " +0.263\n", " \n", " 9752_19184\n", "
\n", " +0.213\n", " \n", " 9953_34466\n", "
\n", " +0.211\n", " \n", " 9752_19184 9700_8607\n", "
\n", " +0.211\n", " \n", " 9700_32785 9752_14633 9752_19184\n", "
\n", " +0.211\n", " \n", " 9752_14633 9752_19184 9700_8607\n", "
\n", " +0.197\n", " \n", " 7762_32289\n", "
\n", " +0.184\n", " \n", " 9752_19184 9700_8607 7755_32379\n", "
\n", " … 89 more positive …\n", "
\n", " … 49902 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.426\n", " \n", " 9716_61259\n", "
\n", " +0.400\n", " \n", " 9716_7033\n", "
\n", " +0.310\n", " \n", " 9716_7033 9716_61259\n", "
\n", " +0.271\n", " \n", " 9716_7033 9716_7033 9716_61259\n", "
\n", " +0.237\n", " \n", " 9716_7033 9716_7033\n", "
\n", " +0.232\n", " \n", " 9752_34077\n", "
\n", " +0.232\n", " \n", " 9716_61259 9700_32789\n", "
\n", " +0.159\n", " \n", " 9700_8607 9716_7033\n", "
\n", " +0.155\n", " \n", " 7717_39608\n", "
\n", " +0.133\n", " \n", " 9700_8607\n", "
\n", " … 124 more positive …\n", "
\n", " … 49867 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.657\n", " \n", " 9716_36734\n", "
\n", " +0.318\n", " \n", " 9716_36732 9716_36734\n", "
\n", " +0.298\n", " \n", " 9716_36734 9716_36732\n", "
\n", " +0.297\n", " \n", " 9716_36732\n", "
\n", " +0.258\n", " \n", " 9716_36734 9716_36732 9716_36734\n", "
\n", " +0.231\n", " \n", " 9716_36734 9716_36734\n", "
\n", " +0.179\n", " \n", " 9716_36732 9716_36734 9716_36732\n", "
\n", " +0.119\n", " \n", " 9716_7033 9716_36734\n", "
\n", " +0.116\n", " \n", " 9752_13277\n", "
\n", " +0.112\n", " \n", " 9752_13510 9752_13277\n", "
\n", " … 79 more positive …\n", "
\n", " … 49912 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.420\n", " \n", " 7755_31336\n", "
\n", " +0.271\n", " \n", " 7755_31336 7755_31336\n", "
\n", " +0.241\n", " \n", " 9700_14123 9716_7033\n", "
\n", " +0.225\n", " \n", " 9700_14123 9716_7033 7755_31336\n", "
\n", " +0.198\n", " \n", " 9797_12439\n", "
\n", " +0.197\n", " \n", " 9716_7033 7755_31336\n", "
\n", " +0.197\n", " \n", " 9754_10667 9700_14123 9716_7033\n", "
\n", " +0.184\n", " \n", " 9700_14123\n", "
\n", " +0.183\n", " \n", " 9716_6428\n", "
\n", " +0.183\n", " \n", " 9797_12439 9754_10667 9700_14123\n", "
\n", " … 65 more positive …\n", "
\n", " … 49926 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.296\n", " \n", " 9746_31436\n", "
\n", " +0.248\n", " \n", " 9716_12396\n", "
\n", " +0.226\n", " \n", " 9752_3089\n", "
\n", " +0.222\n", " \n", " 9716_44955 9746_31436\n", "
\n", " +0.221\n", " \n", " 9716_44955\n", "
\n", " +0.216\n", " \n", " 9700_29750 9752_30046\n", "
\n", " +0.201\n", " \n", " 9752_30046 9752_3089\n", "
\n", " +0.201\n", " \n", " 9716_34958 9700_29750 9752_30046\n", "
\n", " +0.201\n", " \n", " 9716_34958 9700_29750\n", "
\n", " +0.198\n", " \n", " 9746_31436 9716_34958\n", "
\n", " … 123 more positive …\n", "
\n", " … 49868 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.382\n", " \n", " 7755_32046\n", "
\n", " +0.304\n", " \n", " 9745_10306\n", "
\n", " +0.284\n", " \n", " 7755_32046 7755_32046\n", "
\n", " +0.282\n", " \n", " 9047_46629\n", "
\n", " +0.282\n", " \n", " 7761_30007\n", "
\n", " +0.265\n", " \n", " 9745_10306 9745_10306\n", "
\n", " +0.265\n", " \n", " 9745_36247\n", "
\n", " +0.212\n", " \n", " 9745_10306 9745_36247\n", "
\n", " +0.212\n", " \n", " 9745_10306 9745_10306 9745_10306\n", "
\n", " +0.131\n", " \n", " 9745_12668\n", "
\n", " … 52 more positive …\n", "
\n", " … 49939 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.394\n", " \n", " 9716_33836\n", "
\n", " +0.380\n", " \n", " 9752_10379\n", "
\n", " +0.221\n", " \n", " 9752_10371 9752_10379\n", "
\n", " +0.201\n", " \n", " 9716_33838\n", "
\n", " +0.199\n", " \n", " 9716_7033 9716_33836\n", "
\n", " +0.177\n", " \n", " 9700_8607 9716_7033 9716_33836\n", "
\n", " +0.177\n", " \n", " 9752_10379 9752_10371 9752_10379\n", "
\n", " +0.166\n", " \n", " 9752_10379 9752_10371\n", "
\n", " +0.155\n", " \n", " 9716_7033 9716_33836 9716_33836\n", "
\n", " +0.155\n", " \n", " 9752_10379 9742_25596\n", "
\n", " … 170 more positive …\n", "
\n", " … 49821 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.517\n", " \n", " 9716_32507\n", "
\n", " +0.248\n", " \n", " 9716_32507 9716_32507\n", "
\n", " +0.197\n", " \n", " 9700_33819 9752_14633\n", "
\n", " +0.172\n", " \n", " 9716_35306 9716_32507 9716_32507\n", "
\n", " +0.172\n", " \n", " 9716_35306 9716_32507\n", "
\n", " +0.168\n", " \n", " 9752_46818\n", "
\n", " +0.162\n", " \n", " 9700_33819 9752_14633 9752_46818\n", "
\n", " +0.158\n", " \n", " 9752_14633 9752_46818\n", "
\n", " +0.154\n", " \n", " 5018_53966\n", "
\n", " +0.139\n", " \n", " 9700_33819\n", "
\n", " … 195 more positive …\n", "
\n", " … 49796 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.369\n", " \n", " 9716_37508\n", "
\n", " +0.317\n", " \n", " 5069_61001\n", "
\n", " +0.286\n", " \n", " 5069_60963\n", "
\n", " +0.268\n", " \n", " 5022_58668\n", "
\n", " +0.239\n", " \n", " 5069_53248\n", "
\n", " +0.205\n", " \n", " 5022_55587\n", "
\n", " +0.205\n", " \n", " 5022_52826\n", "
\n", " +0.183\n", " \n", " 7755_38926\n", "
\n", " +0.179\n", " \n", " 5018_59584 5022_52826\n", "
\n", " +0.158\n", " \n", " 5018_57337\n", "
\n", " … 56 more positive …\n", "
\n", " … 49935 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.595\n", " \n", " 9716_31786\n", "
\n", " +0.265\n", " \n", " 9005_45062\n", "
\n", " +0.239\n", " \n", " 9716_44950\n", "
\n", " +0.233\n", " \n", " 9716_44950 9716_31786\n", "
\n", " +0.219\n", " \n", " 9716_31786 9716_31786\n", "
\n", " +0.206\n", " \n", " 9700_15158\n", "
\n", " +0.204\n", " \n", " 9716_31786 9716_44950\n", "
\n", " +0.187\n", " \n", " 9716_31786 9716_44950 9716_31786\n", "
\n", " +0.171\n", " \n", " 9005_40997\n", "
\n", " +0.171\n", " \n", " 9005_44359\n", "
\n", " … 157 more positive …\n", "
\n", " … 49834 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.523\n", " \n", " 9716_33096\n", "
\n", " +0.276\n", " \n", " 9716_31386 9716_31386\n", "
\n", " +0.268\n", " \n", " 9716_31386 9716_31386 9716_31386\n", "
\n", " +0.219\n", " \n", " 9716_31386\n", "
\n", " +0.216\n", " \n", " 9716_900\n", "
\n", " +0.190\n", " \n", " 9716_34958\n", "
\n", " +0.151\n", " \n", " 9716_900 9716_33096\n", "
\n", " +0.144\n", " \n", " 9752_46818 9700_1655\n", "
\n", " +0.144\n", " \n", " 9716_33096 9747_34926\n", "
\n", " +0.144\n", " \n", " 9716_33096 9747_34926 9702_15768\n", "
\n", " … 83 more positive …\n", "
\n", " … 49908 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.528\n", " \n", " 9716_35038\n", "
\n", " +0.306\n", " \n", " 9752_1375\n", "
\n", " +0.254\n", " \n", " 9716_35306\n", "
\n", " +0.196\n", " \n", " 9716_35038 9700_33819\n", "
\n", " +0.196\n", " \n", " 9716_35306 9716_35038\n", "
\n", " +0.196\n", " \n", " 9752_14477 9752_1375\n", "
\n", " +0.196\n", " \n", " 9716_31386 9716_35038\n", "
\n", " +0.171\n", " \n", " 9716_31386\n", "
\n", " +0.168\n", " \n", " 9700_33818\n", "
\n", " +0.164\n", " \n", " 9716_35038 9700_33818\n", "
\n", " … 65 more positive …\n", "
\n", " … 49926 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.394\n", " \n", " 9752_31489 9702_30578\n", "
\n", " +0.391\n", " \n", " 9702_30578\n", "
\n", " +0.365\n", " \n", " 9702_30578 9752_31489\n", "
\n", " +0.359\n", " \n", " 9702_30578 9752_31489 9702_30578\n", "
\n", " +0.307\n", " \n", " 9752_31489\n", "
\n", " +0.294\n", " \n", " 9752_31489 9702_30578 9752_31489\n", "
\n", " +0.168\n", " \n", " 9746_16333\n", "
\n", " +0.139\n", " \n", " 9716_33398\n", "
\n", " +0.131\n", " \n", " 9747_15282 9716_33398\n", "
\n", " +0.120\n", " \n", " 9747_15282\n", "
\n", " … 61 more positive …\n", "
\n", " … 49930 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.794\n", " \n", " 9752_36583\n", "
\n", " +0.340\n", " \n", " 9752_36586\n", "
\n", " +0.263\n", " \n", " 9716_32508\n", "
\n", " +0.172\n", " \n", " 9716_33092\n", "
\n", " +0.148\n", " \n", " 9716_44963\n", "
\n", " +0.130\n", " \n", " 9752_43900\n", "
\n", " +0.097\n", " \n", " 9700_63226\n", "
\n", " +0.092\n", " \n", " 9752_15548 9752_11327\n", "
\n", " +0.085\n", " \n", " 9716_44963 9716_44963\n", "
\n", " +0.085\n", " \n", " 9702_36257\n", "
\n", " … 17 more positive …\n", "
\n", " … 49974 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.471\n", " \n", " 7755_37278\n", "
\n", " +0.403\n", " \n", " 9716_3664 7755_37278\n", "
\n", " +0.391\n", " \n", " 9716_3664\n", "
\n", " +0.386\n", " \n", " 7755_37278 9716_3664\n", "
\n", " +0.273\n", " \n", " 7755_37278 9716_3664 7755_37278\n", "
\n", " +0.240\n", " \n", " 9716_3664 7755_37278 9716_3664\n", "
\n", " +0.173\n", " \n", " 7755_37278 7755_37278\n", "
\n", " +0.159\n", " \n", " 7755_37278 7755_37278 9716_3664\n", "
\n", " +0.157\n", " \n", " 9716_3664 7755_37278 7755_37278\n", "
\n", " +0.139\n", " \n", " 9716_3664 9716_3664\n", "
\n", " … 74 more positive …\n", "
\n", " … 49917 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.625\n", " \n", " 9716_33376\n", "
\n", " +0.287\n", " \n", " 9716_33376 9716_33376\n", "
\n", " +0.239\n", " \n", " 9752_30046\n", "
\n", " +0.223\n", " \n", " 9716_31386\n", "
\n", " +0.140\n", " \n", " 9700_33818\n", "
\n", " +0.132\n", " \n", " 9013_9170\n", "
\n", " +0.131\n", " \n", " 9028_65017\n", "
\n", " +0.131\n", " \n", " 9700_33818 9752_30046\n", "
\n", " +0.108\n", " \n", " 9028_41996 9013_9170\n", "
\n", " +0.108\n", " \n", " 9752_30046 9700_1655\n", "
\n", " … 99 more positive …\n", "
\n", " … 49892 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.377\n", " \n", " 9746_34226\n", "
\n", " +0.346\n", " \n", " 9746_14891\n", "
\n", " +0.318\n", " \n", " 9746_14876\n", "
\n", " +0.256\n", " \n", " 9746_34226 9716_34958\n", "
\n", " +0.240\n", " \n", " 9752_28036\n", "
\n", " +0.220\n", " \n", " 9746_14876 9746_34226\n", "
\n", " +0.219\n", " \n", " 9746_14891 9746_14891\n", "
\n", " +0.216\n", " \n", " 9716_34958\n", "
\n", " +0.183\n", " \n", " 9746_14891 9746_34226\n", "
\n", " +0.146\n", " \n", " 9746_14891 9746_14891 9746_34226\n", "
\n", " … 105 more positive …\n", "
\n", " … 49886 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.336\n", " \n", " 9716_3664\n", "
\n", " +0.265\n", " \n", " 9752_836\n", "
\n", " +0.247\n", " \n", " 9752_46818\n", "
\n", " +0.241\n", " \n", " 9716_3665\n", "
\n", " +0.207\n", " \n", " 9752_46818 9752_836\n", "
\n", " +0.204\n", " \n", " 7755_31336\n", "
\n", " +0.196\n", " \n", " 7755_31336 9716_3664\n", "
\n", " +0.190\n", " \n", " 9752_836 9752_46818\n", "
\n", " +0.161\n", " \n", " 9752_46818 9752_836 9752_46818\n", "
\n", " +0.161\n", " \n", " 9752_836 9752_46818 9752_836\n", "
\n", " … 238 more positive …\n", "
\n", " … 49753 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.493\n", " \n", " 9716_33846\n", "
\n", " +0.351\n", " \n", " 9716_3665\n", "
\n", " +0.280\n", " \n", " 9716_3665 9716_33846\n", "
\n", " +0.279\n", " \n", " 9716_61257\n", "
\n", " +0.245\n", " \n", " 9716_33846 9716_3665\n", "
\n", " +0.197\n", " \n", " 9752_2902\n", "
\n", " +0.191\n", " \n", " 9752_2902 9752_2904\n", "
\n", " +0.191\n", " \n", " 9752_2904 9752_2902\n", "
\n", " +0.179\n", " \n", " 9752_2904 9752_2902 9752_2904\n", "
\n", " +0.165\n", " \n", " 9752_2904\n", "
\n", " … 86 more positive …\n", "
\n", " … 49905 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.485\n", " \n", " 7753_62669\n", "
\n", " +0.442\n", " \n", " 7753_6136\n", "
\n", " +0.311\n", " \n", " 7716_26290\n", "
\n", " +0.260\n", " \n", " 7716_28801\n", "
\n", " +0.247\n", " \n", " 7716_26292\n", "
\n", " +0.160\n", " \n", " 7716_36160\n", "
\n", " +0.148\n", " \n", " 7716_31984\n", "
\n", " +0.146\n", " \n", " 9716_26295\n", "
\n", " +0.107\n", " \n", " 7753_62669 7753_62669\n", "
\n", " +0.102\n", " \n", " 7753_62669 7716_26292\n", "
\n", " … 570 more positive …\n", "
\n", " … 49421 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.488\n", " \n", " 9716_33099\n", "
\n", " +0.404\n", " \n", " 9716_65414\n", "
\n", " +0.403\n", " \n", " 9752_19186\n", "
\n", " +0.322\n", " \n", " 5086_54588\n", "
\n", " +0.319\n", " \n", " 9716_34958\n", "
\n", " +0.215\n", " \n", " 9716_33099 9752_19186\n", "
\n", " +0.192\n", " \n", " 9716_65414 9716_33099\n", "
\n", " +0.191\n", " \n", " 9716_34958 9716_34958\n", "
\n", " +0.178\n", " \n", " 9716_65413\n", "
\n", " +0.130\n", " \n", " 9716_33093\n", "
\n", " … 14 more positive …\n", "
\n", " … 49977 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.525\n", " \n", " 9701_2817\n", "
\n", " +0.446\n", " \n", " 9701_40450\n", "
\n", " +0.354\n", " \n", " 9701_40470\n", "
\n", " +0.263\n", " \n", " 9701_40450 9701_2817\n", "
\n", " +0.251\n", " \n", " 9701_2817 9701_40450\n", "
\n", " +0.186\n", " \n", " 9701_2817 9701_40470\n", "
\n", " +0.170\n", " \n", " 9701_40470 9701_2817\n", "
\n", " +0.160\n", " \n", " 9701_2817 9701_2817\n", "
\n", " +0.124\n", " \n", " 9701_2817 9701_40450 9701_2817\n", "
\n", " +0.104\n", " \n", " 9701_40450 9701_40450\n", "
\n", " … 428 more positive …\n", "
\n", " … 49563 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.618\n", " \n", " 9757_9091\n", "
\n", " +0.488\n", " \n", " 9953_6545\n", "
\n", " +0.269\n", " \n", " 7743_9090\n", "
\n", " +0.228\n", " \n", " 9757_9090\n", "
\n", " +0.205\n", " \n", " 9700_15158\n", "
\n", " +0.170\n", " \n", " 9953_6544\n", "
\n", " +0.159\n", " \n", " 9953_6545 9953_6545\n", "
\n", " +0.146\n", " \n", " 9953_6544 9953_6544\n", "
\n", " +0.136\n", " \n", " 9700_34898\n", "
\n", " +0.123\n", " \n", " 9716_44950\n", "
\n", " … 16 more positive …\n", "
\n", " … 49975 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.394\n", " \n", " 9746_38746\n", "
\n", " +0.323\n", " \n", " 9746_38746 9746_38746\n", "
\n", " +0.263\n", " \n", " 9716_44955\n", "
\n", " +0.227\n", " \n", " 9746_14892 9716_44955\n", "
\n", " +0.222\n", " \n", " 9746_14892\n", "
\n", " +0.195\n", " \n", " 9716_2260 9746_38746\n", "
\n", " +0.189\n", " \n", " 9746_14891\n", "
\n", " +0.180\n", " \n", " 9716_44955 9700_33819\n", "
\n", " +0.161\n", " \n", " 9746_38746 9746_38746 9746_38746\n", "
\n", " +0.161\n", " \n", " 9746_14892 9716_44955 9700_33819\n", "
\n", " … 114 more positive …\n", "
\n", " … 49877 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.409\n", " \n", " 7752_1567\n", "
\n", " +0.377\n", " \n", " 9752_1556\n", "
\n", " +0.298\n", " \n", " 9935_48641\n", "
\n", " +0.247\n", " \n", " 9935_22533\n", "
\n", " +0.223\n", " \n", " 7752_1567 7752_1567\n", "
\n", " +0.211\n", " \n", " 9752_1556 7752_1567\n", "
\n", " +0.199\n", " \n", " 7752_1567 9752_1556\n", "
\n", " +0.195\n", " \n", " 9752_1556 9752_1556\n", "
\n", " +0.158\n", " \n", " 9716_25376\n", "
\n", " +0.153\n", " \n", " 9941_9220\n", "
\n", " … 425 more positive …\n", "
\n", " … 49566 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.404\n", " \n", " 9752_13277\n", "
\n", " +0.384\n", " \n", " 9752_2446\n", "
\n", " +0.364\n", " \n", " 9752_13277 9752_2446\n", "
\n", " +0.298\n", " \n", " 9752_13277 9752_13277\n", "
\n", " +0.298\n", " \n", " 9752_2446 9752_13277\n", "
\n", " +0.273\n", " \n", " 9752_13277 9752_13277 9752_2446\n", "
\n", " +0.273\n", " \n", " 9752_13277 9752_2446 9752_13277\n", "
\n", " +0.227\n", " \n", " 9752_2446 9752_13277 9752_13277\n", "
\n", " +0.221\n", " \n", " 9716_37501\n", "
\n", " +0.209\n", " \n", " 9716_36733\n", "
\n", " … 26 more positive …\n", "
\n", " … 49965 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.422\n", " \n", " 9734_30476\n", "
\n", " +0.378\n", " \n", " 9734_30465\n", "
\n", " +0.285\n", " \n", " 9734_30465 9734_30476\n", "
\n", " +0.266\n", " \n", " 9734_30476 9734_30465\n", "
\n", " +0.240\n", " \n", " 9734_30476 9734_30465 9734_30476\n", "
\n", " +0.236\n", " \n", " 9734_30465 9734_30476 9734_30465\n", "
\n", " +0.229\n", " \n", " 9734_30467\n", "
\n", " +0.181\n", " \n", " 9916_20246\n", "
\n", " +0.180\n", " \n", " 9916_20226\n", "
\n", " +0.126\n", " \n", " 9916_20226 9916_20246\n", "
\n", " … 627 more positive …\n", "
\n", " … 49364 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.527\n", " \n", " 9701_34049\n", "
\n", " +0.340\n", " \n", " 9701_64774\n", "
\n", " +0.239\n", " \n", " 9701_46337\n", "
\n", " +0.231\n", " \n", " 9734_1538\n", "
\n", " +0.207\n", " \n", " 9701_34049 9701_64774\n", "
\n", " +0.205\n", " \n", " 9701_21506\n", "
\n", " +0.162\n", " \n", " 9701_64771\n", "
\n", " +0.148\n", " \n", " 9701_64800\n", "
\n", " +0.145\n", " \n", " 9734_2821\n", "
\n", " +0.127\n", " \n", " 9701_64774 9701_34049\n", "
\n", " … 331 more positive …\n", "
\n", " … 49660 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.492\n", " \n", " 9754_18690\n", "
\n", " +0.367\n", " \n", " 9937_40193\n", "
\n", " +0.282\n", " \n", " 9937_28162\n", "
\n", " +0.212\n", " \n", " 9937_28161\n", "
\n", " +0.187\n", " \n", " 9754_63747\n", "
\n", " +0.186\n", " \n", " 9754_63776\n", "
\n", " +0.170\n", " \n", " 9754_63750\n", "
\n", " +0.161\n", " \n", " 9754_51202\n", "
\n", " +0.140\n", " \n", " 9754_51202 9754_18690\n", "
\n", " +0.116\n", " \n", " 9754_51222\n", "
\n", " … 741 more positive …\n", "
\n", " … 49250 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.539\n", " \n", " 9716_31428\n", "
\n", " +0.358\n", " \n", " 9716_33096\n", "
\n", " +0.190\n", " \n", " 9746_38746\n", "
\n", " +0.167\n", " \n", " 9716_31428 9716_31428\n", "
\n", " +0.125\n", " \n", " 9746_38746 9747_39227\n", "
\n", " +0.119\n", " \n", " 9716_33097\n", "
\n", " +0.118\n", " \n", " 9716_31428 9716_2264\n", "
\n", " +0.118\n", " \n", " 9764_20059 9743_23276 9757_930\n", "
\n", " +0.112\n", " \n", " 9743_23276 9757_930\n", "
\n", " +0.109\n", " \n", " 9716_2264\n", "
\n", " … 147 more positive …\n", "
\n", " … 49844 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.358\n", " \n", " 7755_32046\n", "
\n", " +0.333\n", " \n", " 9752_19188\n", "
\n", " +0.318\n", " \n", " 7755_32379\n", "
\n", " +0.298\n", " \n", " 9752_14633 9752_19188\n", "
\n", " +0.188\n", " \n", " 9700_8607 7755_32379\n", "
\n", " +0.186\n", " \n", " 9700_30157 9752_14633 9752_19188\n", "
\n", " +0.170\n", " \n", " 9700_30157 9752_14633\n", "
\n", " +0.169\n", " \n", " 9752_14633\n", "
\n", " +0.149\n", " \n", " 7755_32046 7755_32046\n", "
\n", " +0.149\n", " \n", " 9752_19188 9700_8607\n", "
\n", " … 123 more positive …\n", "
\n", " … 49868 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.362\n", " \n", " 9716_33026\n", "
\n", " +0.354\n", " \n", " 9716_1797\n", "
\n", " +0.267\n", " \n", " 9716_30212\n", "
\n", " +0.180\n", " \n", " 9716_20649\n", "
\n", " +0.146\n", " \n", " 9734_30468\n", "
\n", " +0.144\n", " \n", " 9716_1797 9716_30212\n", "
\n", " +0.139\n", " \n", " 9716_1798\n", "
\n", " +0.136\n", " \n", " 9716_56834\n", "
\n", " +0.131\n", " \n", " 9763_12037\n", "
\n", " +0.128\n", " \n", " 9734_5636\n", "
\n", " … 793 more positive …\n", "
\n", " … 49198 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.429\n", " \n", " 7755_46910\n", "
\n", " +0.372\n", " \n", " 7755_46890\n", "
\n", " +0.312\n", " \n", " 7755_63261\n", "
\n", " +0.208\n", " \n", " 7757_3563\n", "
\n", " +0.208\n", " \n", " 9733_14809\n", "
\n", " +0.202\n", " \n", " 9757_3551\n", "
\n", " +0.197\n", " \n", " 7752_515\n", "
\n", " +0.163\n", " \n", " 7752_516\n", "
\n", " +0.156\n", " \n", " 7755_63261 7755_46910\n", "
\n", " +0.125\n", " \n", " 7733_14813\n", "
\n", " … 277 more positive …\n", "
\n", " … 49714 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.292\n", " \n", " 9734_59905\n", "
\n", " +0.269\n", " \n", " 9916_42753\n", "
\n", " +0.240\n", " \n", " 9916_42764\n", "
\n", " +0.239\n", " \n", " 9734_5644\n", "
\n", " +0.189\n", " \n", " 9734_30466\n", "
\n", " +0.185\n", " \n", " 9734_5644 9734_5644\n", "
\n", " +0.163\n", " \n", " 7746_14897\n", "
\n", " +0.162\n", " \n", " 9734_59905 9734_59905\n", "
\n", " +0.156\n", " \n", " 5061_1721\n", "
\n", " +0.154\n", " \n", " 9734_47105\n", "
\n", " … 291 more positive …\n", "
\n", " … 49700 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.438\n", " \n", " 7725_30574\n", "
\n", " +0.309\n", " \n", " 9716_2265\n", "
\n", " +0.308\n", " \n", " 7716_2278\n", "
\n", " +0.300\n", " \n", " 7716_2269\n", "
\n", " +0.215\n", " \n", " 7716_2284\n", "
\n", " +0.208\n", " \n", " 9700_30038\n", "
\n", " +0.192\n", " \n", " 7716_2284 7716_2278\n", "
\n", " +0.187\n", " \n", " 9716_34956\n", "
\n", " +0.186\n", " \n", " 7716_2278 7716_2284\n", "
\n", " +0.158\n", " \n", " 7725_30574 9700_30038\n", "
\n", " … 361 more positive …\n", "
\n", " … 49630 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.447\n", " \n", " 7755_31336\n", "
\n", " +0.314\n", " \n", " 9716_3664\n", "
\n", " +0.285\n", " \n", " 7755_31336 9716_3664\n", "
\n", " +0.250\n", " \n", " 9716_3666\n", "
\n", " +0.204\n", " \n", " 7755_2984\n", "
\n", " +0.192\n", " \n", " 7755_2985 9716_3666\n", "
\n", " +0.175\n", " \n", " 7755_31336 7755_31336\n", "
\n", " +0.160\n", " \n", " 7755_2985 9716_3666 7755_31336\n", "
\n", " +0.160\n", " \n", " 9752_14641 9700_8607 9716_7033\n", "
\n", " +0.150\n", " \n", " 9752_31488 9752_14641\n", "
\n", " … 116 more positive …\n", "
\n", " … 49875 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.320\n", " \n", " 7755_32767\n", "
\n", " +0.261\n", " \n", " 9716_7033 7755_33266\n", "
\n", " +0.261\n", " \n", " 9716_6428 9700_32789\n", "
\n", " +0.261\n", " \n", " 9716_6428 9700_32789 9752_14633\n", "
\n", " +0.224\n", " \n", " 7755_32269\n", "
\n", " +0.221\n", " \n", " 9716_7033\n", "
\n", " +0.210\n", " \n", " 7755_32767 9716_6428\n", "
\n", " +0.198\n", " \n", " 9716_6428\n", "
\n", " +0.186\n", " \n", " 7755_32768\n", "
\n", " +0.179\n", " \n", " 7755_33266\n", "
\n", " … 97 more positive …\n", "
\n", " … 49894 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.623\n", " \n", " 7701_5213\n", "
\n", " +0.487\n", " \n", " 9701_40453\n", "
\n", " +0.278\n", " \n", " 9701_40453 7701_5213\n", "
\n", " +0.244\n", " \n", " 7701_5213 9701_40453\n", "
\n", " +0.170\n", " \n", " 7701_5213 7701_5213\n", "
\n", " +0.164\n", " \n", " 7710_38912\n", "
\n", " +0.142\n", " \n", " 7701_5213 9701_40453 7701_5213\n", "
\n", " +0.140\n", " \n", " 7716_49282\n", "
\n", " +0.136\n", " \n", " 9701_40453 7701_5213 9701_40453\n", "
\n", " +0.112\n", " \n", " 9710_4101\n", "
\n", " … 268 more positive …\n", "
\n", " … 49723 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.402\n", " \n", " 9710_32513\n", "
\n", " +0.360\n", " \n", " 9710_13569\n", "
\n", " +0.339\n", " \n", " 9710_32524\n", "
\n", " +0.239\n", " \n", " 9710_58636\n", "
\n", " +0.230\n", " \n", " 9710_58625\n", "
\n", " +0.209\n", " \n", " 5064_38401\n", "
\n", " +0.180\n", " \n", " 5064_38412\n", "
\n", " +0.173\n", " \n", " 9734_14852\n", "
\n", " +0.155\n", " \n", " 9723_33538\n", "
\n", " +0.133\n", " \n", " 7740_2590\n", "
\n", " … 463 more positive …\n", "
\n", " … 49528 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.600\n", " \n", " 7752_6312\n", "
\n", " +0.323\n", " \n", " 7752_6312 7752_6312\n", "
\n", " +0.211\n", " \n", " 9758_43523\n", "
\n", " +0.211\n", " \n", " 7700_30030\n", "
\n", " +0.179\n", " \n", " 7752_6312 9752_14642\n", "
\n", " +0.162\n", " \n", " 9752_14642 7752_6312\n", "
\n", " +0.153\n", " \n", " 7725_30574\n", "
\n", " +0.150\n", " \n", " 7752_6312 7752_6312 7752_6312\n", "
\n", " +0.143\n", " \n", " 9752_14642\n", "
\n", " +0.137\n", " \n", " 7700_8608\n", "
\n", " … 613 more positive …\n", "
\n", " … 49378 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.358\n", " \n", " 9716_33026\n", "
\n", " +0.342\n", " \n", " 9716_43779\n", "
\n", " +0.339\n", " \n", " 9916_20226\n", "
\n", " +0.294\n", " \n", " 9916_20246\n", "
\n", " +0.203\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.199\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.158\n", " \n", " 9916_20225\n", "
\n", " +0.156\n", " \n", " 9916_20236\n", "
\n", " +0.155\n", " \n", " 9916_20226 9916_20246 9916_20226\n", "
\n", " +0.150\n", " \n", " 9946_25345\n", "
\n", " … 787 more positive …\n", "
\n", " … 49204 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.482\n", " \n", " 9916_41484\n", "
\n", " +0.479\n", " \n", " 9916_41473\n", "
\n", " +0.357\n", " \n", " 9916_41484 9916_41473\n", "
\n", " +0.333\n", " \n", " 9916_41473 9916_41484\n", "
\n", " +0.256\n", " \n", " 9916_41484 9916_41473 9916_41484\n", "
\n", " +0.252\n", " \n", " 9916_41473 9916_41484 9916_41473\n", "
\n", " +0.132\n", " \n", " 9739_34070\n", "
\n", " +0.125\n", " \n", " 9739_34050\n", "
\n", " +0.115\n", " \n", " 9739_34050 9739_34070 9739_34050\n", "
\n", " +0.106\n", " \n", " 9739_34070 9739_34050\n", "
\n", " … 706 more positive …\n", "
\n", " … 49285 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.433\n", " \n", " 9734_47136\n", "
\n", " +0.399\n", " \n", " 9734_47107 9734_47136\n", "
\n", " +0.397\n", " \n", " 9734_47136 9734_47107\n", "
\n", " +0.394\n", " \n", " 9734_47107\n", "
\n", " +0.294\n", " \n", " 9734_47136 9734_47107 9734_47136\n", "
\n", " +0.290\n", " \n", " 9734_47107 9734_47136 9734_47107\n", "
\n", " +0.148\n", " \n", " 9734_47136 9734_47107 9734_47107\n", "
\n", " +0.140\n", " \n", " 9734_47136 9734_47136\n", "
\n", " +0.139\n", " \n", " 9734_47107 9734_47136 9734_47136\n", "
\n", " +0.138\n", " \n", " 9734_47107 9734_47107\n", "
\n", " … 218 more positive …\n", "
\n", " … 49773 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.528\n", " \n", " 7716_2284\n", "
\n", " +0.417\n", " \n", " 9716_34957\n", "
\n", " +0.286\n", " \n", " 9716_2265\n", "
\n", " +0.249\n", " \n", " 7716_2278\n", "
\n", " +0.245\n", " \n", " 9716_34957 7716_2284\n", "
\n", " +0.168\n", " \n", " 7716_2284 9716_34957\n", "
\n", " +0.147\n", " \n", " 7716_2269\n", "
\n", " +0.145\n", " \n", " 7716_2283\n", "
\n", " +0.120\n", " \n", " 7716_2284 7716_2278\n", "
\n", " +0.103\n", " \n", " 9716_2265 7716_2284\n", "
\n", " … 270 more positive …\n", "
\n", " … 49721 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.558\n", " \n", " 7746_16339\n", "
\n", " +0.312\n", " \n", " 7746_16345\n", "
\n", " +0.230\n", " \n", " 7716_55676\n", "
\n", " +0.168\n", " \n", " 7716_31789\n", "
\n", " +0.155\n", " \n", " 7742_46754\n", "
\n", " +0.135\n", " \n", " 7716_31789 7746_16345\n", "
\n", " +0.124\n", " \n", " 7716_55676 7746_16339\n", "
\n", " +0.119\n", " \n", " 7746_16353\n", "
\n", " +0.116\n", " \n", " 7746_16339 7716_55676\n", "
\n", " +0.116\n", " \n", " 9701_43536\n", "
\n", " … 434 more positive …\n", "
\n", " … 49557 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.504\n", " \n", " 9916_51458\n", "
\n", " +0.343\n", " \n", " 9916_35841\n", "
\n", " +0.319\n", " \n", " 9790_55809\n", "
\n", " +0.242\n", " \n", " 9734_35329\n", "
\n", " +0.191\n", " \n", " 9735_13060\n", "
\n", " +0.155\n", " \n", " 9916_15366\n", "
\n", " +0.151\n", " \n", " 9794_28417\n", "
\n", " +0.140\n", " \n", " 9916_51458 9916_35841\n", "
\n", " +0.132\n", " \n", " 9935_53250\n", "
\n", " +0.132\n", " \n", " 9916_32770\n", "
\n", " … 626 more positive …\n", "
\n", " … 49365 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.483\n", " \n", " 9935_59936\n", "
\n", " +0.463\n", " \n", " 9935_59907\n", "
\n", " +0.342\n", " \n", " 9935_59936 9935_59907\n", "
\n", " +0.300\n", " \n", " 9935_59907 9935_59936\n", "
\n", " +0.225\n", " \n", " 9935_59907 9935_59936 9935_59907\n", "
\n", " +0.210\n", " \n", " 9935_59936 9935_59907 9935_59936\n", "
\n", " +0.191\n", " \n", " 9934_40963\n", "
\n", " +0.128\n", " \n", " 9734_14860\n", "
\n", " +0.117\n", " \n", " 9935_59936 9935_59936\n", "
\n", " +0.110\n", " \n", " 9935_59907 9935_59907\n", "
\n", " … 661 more positive …\n", "
\n", " … 49330 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.555\n", " \n", " 9916_65026\n", "
\n", " +0.467\n", " \n", " 9916_65046\n", "
\n", " +0.341\n", " \n", " 9916_65028\n", "
\n", " +0.248\n", " \n", " 9916_65026 9916_65046\n", "
\n", " +0.222\n", " \n", " 9916_65046 9916_65026\n", "
\n", " +0.155\n", " \n", " 9916_65046 9916_65028\n", "
\n", " +0.149\n", " \n", " 9916_65028 9916_65026\n", "
\n", " +0.124\n", " \n", " 9916_65028 9916_65046\n", "
\n", " +0.120\n", " \n", " 9916_65026 9916_65028\n", "
\n", " +0.113\n", " \n", " 9916_65026 9916_65026\n", "
\n", " … 689 more positive …\n", "
\n", " … 49302 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.469\n", " \n", " 9916_19457\n", "
\n", " +0.456\n", " \n", " 9916_19468\n", "
\n", " +0.267\n", " \n", " 9716_1794\n", "
\n", " +0.261\n", " \n", " 9916_19457 9916_19468\n", "
\n", " +0.241\n", " \n", " 9916_19468 9916_19457\n", "
\n", " +0.234\n", " \n", " 9716_1814\n", "
\n", " +0.187\n", " \n", " 7752_32993\n", "
\n", " +0.173\n", " \n", " 9716_1794 9716_1814\n", "
\n", " +0.149\n", " \n", " 9916_19457 9916_19468 9916_19457\n", "
\n", " +0.146\n", " \n", " 9716_1814 9716_1794\n", "
\n", " … 727 more positive …\n", "
\n", " … 49264 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.402\n", " \n", " 9702_30576\n", "
\n", " +0.390\n", " \n", " 9702_30576 9752_14642\n", "
\n", " +0.326\n", " \n", " 9752_14642 9702_30576\n", "
\n", " +0.315\n", " \n", " 9752_14642\n", "
\n", " +0.276\n", " \n", " 9752_14642 9702_30576 9752_14642\n", "
\n", " +0.258\n", " \n", " 9702_30576 9752_14642 9702_30576\n", "
\n", " +0.192\n", " \n", " 9716_32507\n", "
\n", " +0.168\n", " \n", " 9716_20259\n", "
\n", " +0.162\n", " \n", " 9702_30571\n", "
\n", " +0.152\n", " \n", " 9716_20259 9716_32507\n", "
\n", " … 224 more positive …\n", "
\n", " … 49767 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.302\n", " \n", " 9770_10158\n", "
\n", " +0.283\n", " \n", " 7798_19230\n", "
\n", " +0.204\n", " \n", " 9716_31063\n", "
\n", " +0.203\n", " \n", " 7762_30257\n", "
\n", " +0.172\n", " \n", " 9767_14249\n", "
\n", " +0.166\n", " \n", " 9767_14244\n", "
\n", " +0.157\n", " \n", " 7765_30668\n", "
\n", " +0.156\n", " \n", " 7762_32129\n", "
\n", " +0.155\n", " \n", " 9702_30571\n", "
\n", " +0.151\n", " \n", " 9752_11327\n", "
\n", " … 220 more positive …\n", "
\n", " … 49771 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.447\n", " \n", " 9716_18433\n", "
\n", " +0.409\n", " \n", " 9716_39968\n", "
\n", " +0.380\n", " \n", " 9716_39942\n", "
\n", " +0.376\n", " \n", " 9716_39939\n", "
\n", " +0.177\n", " \n", " 9716_18433 9716_39942\n", "
\n", " +0.155\n", " \n", " 9716_39942 9716_18433\n", "
\n", " +0.134\n", " \n", " 9716_39968 9716_18433\n", "
\n", " +0.132\n", " \n", " 9716_18433 9716_39939\n", "
\n", " +0.122\n", " \n", " 9716_48386\n", "
\n", " +0.118\n", " \n", " 9716_39939 9716_18433\n", "
\n", " … 709 more positive …\n", "
\n", " … 49282 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.394\n", " \n", " 9934_39426\n", "
\n", " +0.266\n", " \n", " 9739_24326\n", "
\n", " +0.240\n", " \n", " 9976_3872\n", "
\n", " +0.206\n", " \n", " 9934_51714\n", "
\n", " +0.199\n", " \n", " 9976_24322\n", "
\n", " +0.195\n", " \n", " 9976_3843\n", "
\n", " +0.183\n", " \n", " 9716_7180\n", "
\n", " +0.166\n", " \n", " 9976_3846\n", "
\n", " +0.163\n", " \n", " 9716_7169\n", "
\n", " +0.158\n", " \n", " 9909_16133\n", "
\n", " … 905 more positive …\n", "
\n", " … 49086 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.558\n", " \n", " 9953_37016\n", "
\n", " +0.380\n", " \n", " 9716_33102\n", "
\n", " +0.311\n", " \n", " 9953_37016 9716_33102\n", "
\n", " +0.304\n", " \n", " 9716_33102 9953_37016\n", "
\n", " +0.213\n", " \n", " 7716_26290\n", "
\n", " +0.199\n", " \n", " 9716_26295\n", "
\n", " +0.178\n", " \n", " 9953_37016 9716_33102 9953_37016\n", "
\n", " +0.147\n", " \n", " 9716_33102 9953_37016 9716_33102\n", "
\n", " +0.136\n", " \n", " 9953_37016 9716_26295\n", "
\n", " +0.129\n", " \n", " 9953_37016 9953_37016\n", "
\n", " … 279 more positive …\n", "
\n", " … 49712 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.487\n", " \n", " 7752_4063\n", "
\n", " +0.409\n", " \n", " 9702_11009\n", "
\n", " +0.238\n", " \n", " 9702_11009 7752_4063\n", "
\n", " +0.238\n", " \n", " 7752_4063 9702_11009\n", "
\n", " +0.191\n", " \n", " 7702_36002\n", "
\n", " +0.159\n", " \n", " 7752_4063 7752_4063\n", "
\n", " +0.158\n", " \n", " 7702_42622\n", "
\n", " +0.157\n", " \n", " 7755_6590\n", "
\n", " +0.148\n", " \n", " 7755_6591\n", "
\n", " +0.143\n", " \n", " 9702_11009 9702_11009\n", "
\n", " … 223 more positive …\n", "
\n", " … 49768 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.417\n", " \n", " 7700_5872\n", "
\n", " +0.347\n", " \n", " 7752_6312\n", "
\n", " +0.345\n", " \n", " 7700_30030\n", "
\n", " +0.276\n", " \n", " 9934_29445\n", "
\n", " +0.209\n", " \n", " 9700_30038\n", "
\n", " +0.166\n", " \n", " 9934_29445 7700_30030\n", "
\n", " +0.149\n", " \n", " 7752_6312 7700_30030\n", "
\n", " +0.138\n", " \n", " 7700_59709\n", "
\n", " +0.136\n", " \n", " 7700_30030 7752_6312\n", "
\n", " +0.135\n", " \n", " 7752_6312 7752_6312\n", "
\n", " … 284 more positive …\n", "
\n", " … 49707 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.539\n", " \n", " 7716_3323\n", "
\n", " +0.345\n", " \n", " 9716_33102\n", "
\n", " +0.334\n", " \n", " 9716_33102 7716_3323\n", "
\n", " +0.322\n", " \n", " 7716_3323 9716_33102\n", "
\n", " +0.256\n", " \n", " 7716_3323 7716_3323\n", "
\n", " +0.209\n", " \n", " 7716_3323 9716_33102 7716_3323\n", "
\n", " +0.188\n", " \n", " 9716_33229 7716_3323\n", "
\n", " +0.170\n", " \n", " 9716_33229\n", "
\n", " +0.166\n", " \n", " 9716_33102 7716_3323 9716_33102\n", "
\n", " +0.144\n", " \n", " 7716_3323 9716_33229\n", "
\n", " … 275 more positive …\n", "
\n", " … 49716 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.423\n", " \n", " 9701_47361\n", "
\n", " +0.399\n", " \n", " 9701_47372\n", "
\n", " +0.280\n", " \n", " 9739_10501\n", "
\n", " +0.271\n", " \n", " 9701_47361 9701_47372\n", "
\n", " +0.267\n", " \n", " 9701_47372 9701_47361\n", "
\n", " +0.249\n", " \n", " 9701_25601\n", "
\n", " +0.189\n", " \n", " 9701_47361 9701_47372 9701_47361\n", "
\n", " +0.175\n", " \n", " 9739_56580\n", "
\n", " +0.156\n", " \n", " 9701_47372 9701_47361 9701_47372\n", "
\n", " +0.145\n", " \n", " 9701_25612\n", "
\n", " … 479 more positive …\n", "
\n", " … 49512 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.333\n", " \n", " 7755_37276\n", "
\n", " +0.283\n", " \n", " 7755_3729\n", "
\n", " +0.265\n", " \n", " 7754_37010\n", "
\n", " +0.246\n", " \n", " 7755_306\n", "
\n", " +0.234\n", " \n", " 7752_3243\n", "
\n", " +0.223\n", " \n", " 7755_55452\n", "
\n", " +0.210\n", " \n", " 7754_5721\n", "
\n", " +0.177\n", " \n", " 7754_37010 7754_5721\n", "
\n", " +0.177\n", " \n", " 7754_5721 7754_37010\n", "
\n", " +0.140\n", " \n", " 9752_31486\n", "
\n", " … 140 more positive …\n", "
\n", " … 49851 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.438\n", " \n", " 9934_56067\n", "
\n", " +0.361\n", " \n", " 9934_56065\n", "
\n", " +0.349\n", " \n", " 9934_56076\n", "
\n", " +0.310\n", " \n", " 9934_11009\n", "
\n", " +0.216\n", " \n", " 9716_15874\n", "
\n", " +0.203\n", " \n", " 9716_15894\n", "
\n", " +0.195\n", " \n", " 9716_54048\n", "
\n", " +0.155\n", " \n", " 9934_56076 9934_56065\n", "
\n", " +0.138\n", " \n", " 9934_56065 9934_56076\n", "
\n", " +0.135\n", " \n", " 9934_56067 9934_11009\n", "
\n", " … 697 more positive …\n", "
\n", " … 49294 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.451\n", " \n", " 9716_48396\n", "
\n", " +0.373\n", " \n", " 9716_18177\n", "
\n", " +0.271\n", " \n", " 9716_48388\n", "
\n", " +0.265\n", " \n", " 9716_48385\n", "
\n", " +0.216\n", " \n", " 9716_48396 9716_48385\n", "
\n", " +0.190\n", " \n", " 9716_48385 9716_48396\n", "
\n", " +0.177\n", " \n", " 9716_18177 9716_48396\n", "
\n", " +0.150\n", " \n", " 9716_48388 9716_18177\n", "
\n", " +0.134\n", " \n", " 9716_48396 9716_48388\n", "
\n", " +0.132\n", " \n", " 9716_48396 9716_48396\n", "
\n", " … 783 more positive …\n", "
\n", " … 49208 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.323\n", " \n", " 9734_39948\n", "
\n", " +0.292\n", " \n", " 9734_39937\n", "
\n", " +0.254\n", " \n", " 9937_33804\n", "
\n", " +0.250\n", " \n", " 9934_56076\n", "
\n", " +0.235\n", " \n", " 9937_33793\n", "
\n", " +0.226\n", " \n", " 9734_64262\n", "
\n", " +0.211\n", " \n", " 9934_11009\n", "
\n", " +0.184\n", " \n", " 9934_56067\n", "
\n", " +0.169\n", " \n", " 9734_48387\n", "
\n", " +0.167\n", " \n", " 9782_22550\n", "
\n", " … 611 more positive …\n", "
\n", " … 49380 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.420\n", " \n", " 9735_13068\n", "
\n", " +0.295\n", " \n", " 9735_13057\n", "
\n", " +0.269\n", " \n", " 9735_13060\n", "
\n", " +0.228\n", " \n", " 7746_6552\n", "
\n", " +0.215\n", " \n", " 9758_55564\n", "
\n", " +0.209\n", " \n", " 9953_6544\n", "
\n", " +0.189\n", " \n", " 9937_33794\n", "
\n", " +0.182\n", " \n", " 9937_33814\n", "
\n", " +0.154\n", " \n", " 9937_1538\n", "
\n", " +0.150\n", " \n", " 9735_13068 9735_13057\n", "
\n", " … 863 more positive …\n", "
\n", " … 49128 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.451\n", " \n", " 9734_10006\n", "
\n", " +0.435\n", " \n", " 9734_9986\n", "
\n", " +0.361\n", " \n", " 9734_10006 9734_9986\n", "
\n", " +0.355\n", " \n", " 9734_9986 9734_10006\n", "
\n", " +0.277\n", " \n", " 9734_10006 9734_9986 9734_10006\n", "
\n", " +0.269\n", " \n", " 9734_9986 9734_10006 9734_9986\n", "
\n", " +0.140\n", " \n", " 9734_9985\n", "
\n", " +0.129\n", " \n", " 9734_10006 9734_10006\n", "
\n", " +0.114\n", " \n", " 9734_9986 9734_9986\n", "
\n", " +0.103\n", " \n", " 9734_9986 9734_9986 9734_10006\n", "
\n", " … 340 more positive …\n", "
\n", " … 49651 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.372\n", " \n", " 7700_30030\n", "
\n", " +0.274\n", " \n", " 7700_5871\n", "
\n", " +0.253\n", " \n", " 7755_6988\n", "
\n", " +0.229\n", " \n", " 7752_6312\n", "
\n", " +0.223\n", " \n", " 7700_5872\n", "
\n", " +0.192\n", " \n", " 7755_55462\n", "
\n", " +0.176\n", " \n", " 7700_59709\n", "
\n", " +0.162\n", " \n", " 7752_6312 7700_30030\n", "
\n", " +0.160\n", " \n", " 7700_30030 7752_6312\n", "
\n", " +0.150\n", " \n", " 5091_64480\n", "
\n", " … 454 more positive …\n", "
\n", " … 49537 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.494\n", " \n", " 9790_55809\n", "
\n", " +0.345\n", " \n", " 9916_51458\n", "
\n", " +0.338\n", " \n", " 7752_8398\n", "
\n", " +0.290\n", " \n", " 9785_52993\n", "
\n", " +0.228\n", " \n", " 9794_28417\n", "
\n", " +0.177\n", " \n", " 9935_53250\n", "
\n", " +0.176\n", " \n", " 9716_39425\n", "
\n", " +0.168\n", " \n", " 9716_39425 9785_52993\n", "
\n", " +0.153\n", " \n", " 9916_32770\n", "
\n", " +0.145\n", " \n", " 9785_52993 9716_39425\n", "
\n", " … 504 more positive …\n", "
\n", " … 49487 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.470\n", " \n", " 9935_55052\n", "
\n", " +0.392\n", " \n", " 9935_55041\n", "
\n", " +0.293\n", " \n", " 9935_55041 9935_55052\n", "
\n", " +0.281\n", " \n", " 9935_55052 9935_55041\n", "
\n", " +0.251\n", " \n", " 9935_64260\n", "
\n", " +0.233\n", " \n", " 9935_55041 9935_55052 9935_55041\n", "
\n", " +0.228\n", " \n", " 9935_55052 9935_55041 9935_55052\n", "
\n", " +0.181\n", " \n", " 9935_55044\n", "
\n", " +0.138\n", " \n", " 9754_63747\n", "
\n", " +0.129\n", " \n", " 7716_3669\n", "
\n", " … 552 more positive …\n", "
\n", " … 49439 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.461\n", " \n", " 9937_63500\n", "
\n", " +0.414\n", " \n", " 9937_63489\n", "
\n", " +0.338\n", " \n", " 9937_63500 9937_63489\n", "
\n", " +0.305\n", " \n", " 9937_63489 9937_63500\n", "
\n", " +0.228\n", " \n", " 9937_63500 9937_63489 9937_63500\n", "
\n", " +0.220\n", " \n", " 9937_63489 9937_63500 9937_63489\n", "
\n", " +0.193\n", " \n", " 9739_27906\n", "
\n", " +0.165\n", " \n", " 9739_27926\n", "
\n", " +0.139\n", " \n", " 9739_27906 9739_27926\n", "
\n", " +0.139\n", " \n", " 9739_27926 9739_27906\n", "
\n", " … 692 more positive …\n", "
\n", " … 49299 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.467\n", " \n", " 9701_40460\n", "
\n", " +0.321\n", " \n", " 9716_55556\n", "
\n", " +0.285\n", " \n", " 9716_55558\n", "
\n", " +0.285\n", " \n", " 9701_40449\n", "
\n", " +0.217\n", " \n", " 9716_10497\n", "
\n", " +0.170\n", " \n", " 9700_813\n", "
\n", " +0.166\n", " \n", " 9701_40449 9701_40460\n", "
\n", " +0.161\n", " \n", " 9701_40460 9701_40449\n", "
\n", " +0.153\n", " \n", " 9716_55556 9716_55558\n", "
\n", " +0.141\n", " \n", " 9701_40451\n", "
\n", " … 771 more positive …\n", "
\n", " … 49220 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.641\n", " \n", " 9746_16333\n", "
\n", " +0.277\n", " \n", " 9716_31787\n", "
\n", " +0.243\n", " \n", " 9746_16333 9746_16333\n", "
\n", " +0.229\n", " \n", " 9716_31787 9746_16333\n", "
\n", " +0.197\n", " \n", " 9746_16333 9716_31787\n", "
\n", " +0.171\n", " \n", " 9752_15568\n", "
\n", " +0.169\n", " \n", " 9752_15916\n", "
\n", " +0.162\n", " \n", " 9716_31788\n", "
\n", " +0.139\n", " \n", " 9752_15568 9752_15916\n", "
\n", " +0.139\n", " \n", " 9716_31788 9746_16333\n", "
\n", " … 100 more positive …\n", "
\n", " … 49891 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.333\n", " \n", " 9734_47107\n", "
\n", " +0.306\n", " \n", " 9734_47136\n", "
\n", " +0.277\n", " \n", " 9736_43788\n", "
\n", " +0.275\n", " \n", " 9736_43777\n", "
\n", " +0.255\n", " \n", " 9734_47136 9734_47107\n", "
\n", " +0.231\n", " \n", " 9734_47107 9734_47136\n", "
\n", " +0.210\n", " \n", " 9734_47110\n", "
\n", " +0.200\n", " \n", " 9734_47107 9734_47136 9734_47107\n", "
\n", " +0.178\n", " \n", " 9734_47136 9734_47107 9734_47136\n", "
\n", " +0.178\n", " \n", " 9736_43788 9736_43777\n", "
\n", " … 618 more positive …\n", "
\n", " … 49373 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.451\n", " \n", " 7755_6589\n", "
\n", " +0.286\n", " \n", " 7755_6590\n", "
\n", " +0.273\n", " \n", " 7755_6590 7755_6589\n", "
\n", " +0.254\n", " \n", " 7757_46774\n", "
\n", " +0.250\n", " \n", " 7755_6589 7755_6590\n", "
\n", " +0.244\n", " \n", " 7755_6589 7755_6590 7755_6589\n", "
\n", " +0.198\n", " \n", " 7767_10391\n", "
\n", " +0.184\n", " \n", " 7755_6591\n", "
\n", " +0.157\n", " \n", " 7755_6589 7755_6591\n", "
\n", " +0.142\n", " \n", " 7755_6590 7755_6589 7755_6590\n", "
\n", " … 472 more positive …\n", "
\n", " … 49519 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.454\n", " \n", " 9004_56331\n", "
\n", " +0.341\n", " \n", " 9004_54141\n", "
\n", " +0.249\n", " \n", " 7752_7749\n", "
\n", " +0.234\n", " \n", " 5046_54144\n", "
\n", " +0.204\n", " \n", " 7716_35363\n", "
\n", " +0.195\n", " \n", " 9004_54141 9004_56331\n", "
\n", " +0.182\n", " \n", " 9004_56331 9004_54141\n", "
\n", " +0.171\n", " \n", " 9716_20251\n", "
\n", " +0.168\n", " \n", " 7716_35365\n", "
\n", " +0.160\n", " \n", " 9752_11191\n", "
\n", " … 352 more positive …\n", "
\n", " … 49639 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.563\n", " \n", " 9934_22274\n", "
\n", " +0.320\n", " \n", " 9934_29185\n", "
\n", " +0.302\n", " \n", " 9739_10500\n", "
\n", " +0.215\n", " \n", " 9934_22274 9934_29185\n", "
\n", " +0.210\n", " \n", " 9934_30467\n", "
\n", " +0.194\n", " \n", " 7752_8214\n", "
\n", " +0.191\n", " \n", " 9934_29185 9934_22274\n", "
\n", " +0.168\n", " \n", " 9934_22274 9934_22274\n", "
\n", " +0.128\n", " \n", " 9934_22274 7752_8214\n", "
\n", " +0.128\n", " \n", " 7752_8214 9934_22274\n", "
\n", " … 682 more positive …\n", "
\n", " … 49309 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.500\n", " \n", " 9916_15366\n", "
\n", " +0.345\n", " \n", " 7752_10367\n", "
\n", " +0.341\n", " \n", " 7752_8398\n", "
\n", " +0.212\n", " \n", " 9916_3333\n", "
\n", " +0.188\n", " \n", " 9752_11327\n", "
\n", " +0.187\n", " \n", " 7752_10367 9916_15366\n", "
\n", " +0.176\n", " \n", " 9916_15366 7752_10367\n", "
\n", " +0.162\n", " \n", " 7752_15672\n", "
\n", " +0.125\n", " \n", " 9916_15366 9916_15366\n", "
\n", " +0.114\n", " \n", " 9916_3333 9916_15366\n", "
\n", " … 650 more positive …\n", "
\n", " … 49341 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.429\n", " \n", " 9935_64278\n", "
\n", " +0.413\n", " \n", " 9935_64258\n", "
\n", " +0.322\n", " \n", " 9935_64278 9935_64258\n", "
\n", " +0.302\n", " \n", " 9935_64258 9935_64278\n", "
\n", " +0.224\n", " \n", " 9935_55062\n", "
\n", " +0.216\n", " \n", " 9935_64258 9935_64278 9935_64258\n", "
\n", " +0.180\n", " \n", " 9935_55042\n", "
\n", " +0.177\n", " \n", " 9935_64278 9935_64258 9935_64278\n", "
\n", " +0.175\n", " \n", " 9935_64278 9935_55062\n", "
\n", " +0.153\n", " \n", " 9935_55062 9935_64278\n", "
\n", " … 793 more positive …\n", "
\n", " … 49198 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.407\n", " \n", " 7752_7732\n", "
\n", " +0.400\n", " \n", " 7745_3088\n", "
\n", " +0.297\n", " \n", " 7745_3088 7752_7732\n", "
\n", " +0.294\n", " \n", " 7752_7732 7745_3088\n", "
\n", " +0.218\n", " \n", " 7752_10505\n", "
\n", " +0.200\n", " \n", " 7752_7732 7752_7732\n", "
\n", " +0.192\n", " \n", " 7745_3089\n", "
\n", " +0.191\n", " \n", " 7745_3088 7745_3088\n", "
\n", " +0.179\n", " \n", " 7752_10505 7745_3089\n", "
\n", " +0.176\n", " \n", " 7752_7732 7745_3088 7752_7732\n", "
\n", " … 252 more positive …\n", "
\n", " … 49739 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.554\n", " \n", " 7745_46879\n", "
\n", " +0.390\n", " \n", " 7745_46876\n", "
\n", " +0.272\n", " \n", " 7752_181\n", "
\n", " +0.269\n", " \n", " 7752_182\n", "
\n", " +0.256\n", " \n", " 7752_183\n", "
\n", " +0.216\n", " \n", " 7752_180\n", "
\n", " +0.140\n", " \n", " 7745_46879 7752_183\n", "
\n", " +0.135\n", " \n", " 7745_40256\n", "
\n", " +0.131\n", " \n", " 7752_182 7745_46876\n", "
\n", " +0.119\n", " \n", " 7752_183 7745_46879\n", "
\n", " … 424 more positive …\n", "
\n", " … 49567 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.423\n", " \n", " 9916_1793\n", "
\n", " +0.332\n", " \n", " 9916_1804\n", "
\n", " +0.262\n", " \n", " 9935_44803\n", "
\n", " +0.256\n", " \n", " 9716_39425\n", "
\n", " +0.236\n", " \n", " 7752_13090\n", "
\n", " +0.234\n", " \n", " 9935_44801\n", "
\n", " +0.216\n", " \n", " 9916_1804 9916_1793\n", "
\n", " +0.209\n", " \n", " 9916_1793 9916_1804\n", "
\n", " +0.184\n", " \n", " 7752_9957\n", "
\n", " +0.184\n", " \n", " 9935_44812\n", "
\n", " … 594 more positive …\n", "
\n", " … 49397 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.609\n", " \n", " 9953_6547\n", "
\n", " +0.307\n", " \n", " 9953_6547 9716_33229\n", "
\n", " +0.288\n", " \n", " 9716_33229\n", "
\n", " +0.247\n", " \n", " 9953_6547 9953_6547\n", "
\n", " +0.227\n", " \n", " 9953_6547 9953_6547 9716_33229\n", "
\n", " +0.151\n", " \n", " 9953_45296\n", "
\n", " +0.146\n", " \n", " 9953_39591\n", "
\n", " +0.121\n", " \n", " 9953_32906\n", "
\n", " +0.110\n", " \n", " 9702_30578\n", "
\n", " +0.109\n", " \n", " 9752_31489\n", "
\n", " … 119 more positive …\n", "
\n", " … 49872 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.570\n", " \n", " 9790_29186\n", "
\n", " +0.450\n", " \n", " 9790_5890\n", "
\n", " +0.293\n", " \n", " 9790_5890 9790_29186\n", "
\n", " +0.291\n", " \n", " 9790_29186 9790_5890\n", "
\n", " +0.195\n", " \n", " 9790_5910\n", "
\n", " +0.183\n", " \n", " 9790_29186 9790_29186\n", "
\n", " +0.127\n", " \n", " 9790_29186 9790_5890 9790_29186\n", "
\n", " +0.121\n", " \n", " 9790_5890 9790_5890\n", "
\n", " +0.117\n", " \n", " 7742_473\n", "
\n", " +0.115\n", " \n", " 9790_5890 9790_29186 9790_5890\n", "
\n", " … 467 more positive …\n", "
\n", " … 49524 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.400\n", " \n", " 9025_58026\n", "
\n", " +0.357\n", " \n", " 7700_55154\n", "
\n", " +0.292\n", " \n", " 9074_51603\n", "
\n", " +0.231\n", " \n", " 5056_18948\n", "
\n", " +0.217\n", " \n", " 7700_5871\n", "
\n", " +0.212\n", " \n", " 9934_29445\n", "
\n", " +0.169\n", " \n", " 5056_16385\n", "
\n", " +0.161\n", " \n", " 9705_46338\n", "
\n", " +0.136\n", " \n", " 9701_49154\n", "
\n", " +0.131\n", " \n", " 5074_64850\n", "
\n", " … 787 more positive …\n", "
\n", " … 49204 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.439\n", " \n", " 9716_33846\n", "
\n", " +0.335\n", " \n", " 9716_33841\n", "
\n", " +0.285\n", " \n", " 9757_7016\n", "
\n", " +0.277\n", " \n", " 5069_59237\n", "
\n", " +0.248\n", " \n", " 9752_1936\n", "
\n", " +0.189\n", " \n", " 9757_9090\n", "
\n", " +0.185\n", " \n", " 5069_60912\n", "
\n", " +0.173\n", " \n", " 9716_33846 9716_33841\n", "
\n", " +0.159\n", " \n", " 9716_33846 9716_33846\n", "
\n", " +0.154\n", " \n", " 5069_60917\n", "
\n", " … 74 more positive …\n", "
\n", " … 49917 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.480\n", " \n", " 9937_16385\n", "
\n", " +0.428\n", " \n", " 9937_16396\n", "
\n", " +0.380\n", " \n", " 9937_16396 9937_16385\n", "
\n", " +0.365\n", " \n", " 9937_16385 9937_16396\n", "
\n", " +0.301\n", " \n", " 9937_16396 9937_16385 9937_16396\n", "
\n", " +0.295\n", " \n", " 9937_16385 9937_16396 9937_16385\n", "
\n", " +0.138\n", " \n", " 9937_46614\n", "
\n", " +0.101\n", " \n", " 9937_46594\n", "
\n", " +0.076\n", " \n", " 9937_16385 9937_16385\n", "
\n", " +0.074\n", " \n", " 9716_62468\n", "
\n", " … 460 more positive …\n", "
\n", " … 49531 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.343\n", " \n", " 9934_34305\n", "
\n", " +0.342\n", " \n", " 9716_19972\n", "
\n", " +0.266\n", " \n", " 9052_49924\n", "
\n", " +0.219\n", " \n", " 9934_58115\n", "
\n", " +0.211\n", " \n", " 9934_62977\n", "
\n", " +0.187\n", " \n", " 5078_26557\n", "
\n", " +0.182\n", " \n", " 9716_4098\n", "
\n", " +0.180\n", " \n", " 9716_19969\n", "
\n", " +0.172\n", " \n", " 9716_4118\n", "
\n", " +0.169\n", " \n", " 9716_19980\n", "
\n", " … 384 more positive …\n", "
\n", " … 49607 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.501\n", " \n", " 9916_25100\n", "
\n", " +0.382\n", " \n", " 9916_25089 9916_25100\n", "
\n", " +0.377\n", " \n", " 9916_25089\n", "
\n", " +0.370\n", " \n", " 9916_25100 9916_25089\n", "
\n", " +0.267\n", " \n", " 9916_25089 9916_25100 9916_25089\n", "
\n", " +0.243\n", " \n", " 9916_25100 9916_25089 9916_25100\n", "
\n", " +0.110\n", " \n", " 9916_25100 9916_25100\n", "
\n", " +0.108\n", " \n", " 9916_25100 9916_25089 9916_25089\n", "
\n", " +0.100\n", " \n", " 9916_25089 9916_25089 9916_25100\n", "
\n", " +0.097\n", " \n", " 9916_25089 9916_25089\n", "
\n", " … 754 more positive …\n", "
\n", " … 49237 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.434\n", " \n", " 7755_853\n", "
\n", " +0.395\n", " \n", " 9752_15475\n", "
\n", " +0.250\n", " \n", " 9091_55767\n", "
\n", " +0.233\n", " \n", " 7755_38846\n", "
\n", " +0.178\n", " \n", " 9710_42229\n", "
\n", " +0.178\n", " \n", " 7755_18823\n", "
\n", " +0.152\n", " \n", " 7755_30238\n", "
\n", " +0.150\n", " \n", " 9752_14633\n", "
\n", " +0.137\n", " \n", " 5061_966\n", "
\n", " +0.125\n", " \n", " 9091_55762\n", "
\n", " … 143 more positive …\n", "
\n", " … 49848 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.434\n", " \n", " 9701_64774\n", "
\n", " +0.285\n", " \n", " 7700_6193\n", "
\n", " +0.283\n", " \n", " 9701_64800\n", "
\n", " +0.265\n", " \n", " 9701_64771\n", "
\n", " +0.242\n", " \n", " 9739_24836\n", "
\n", " +0.217\n", " \n", " 7716_3672\n", "
\n", " +0.174\n", " \n", " 7700_6193 9701_64774\n", "
\n", " +0.161\n", " \n", " 9701_64774 7700_6193\n", "
\n", " +0.145\n", " \n", " 9701_14085\n", "
\n", " +0.145\n", " \n", " 7700_6192\n", "
\n", " … 448 more positive …\n", "
\n", " … 49543 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.575\n", " \n", " 9739_21270\n", "
\n", " +0.288\n", " \n", " 9739_21250 9739_21270\n", "
\n", " +0.278\n", " \n", " 9739_21250\n", "
\n", " +0.266\n", " \n", " 9739_21270 9739_21250\n", "
\n", " +0.237\n", " \n", " 9739_21270 9739_21250 9739_21270\n", "
\n", " +0.221\n", " \n", " 9739_21250 9739_21270 9739_21250\n", "
\n", " +0.200\n", " \n", " 7755_15810\n", "
\n", " +0.183\n", " \n", " 9739_21270 7755_15810\n", "
\n", " +0.183\n", " \n", " 9739_21270 9739_21270\n", "
\n", " +0.179\n", " \n", " 7755_15810 9739_21270\n", "
\n", " … 776 more positive …\n", "
\n", " … 49215 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.406\n", " \n", " 9716_61953\n", "
\n", " +0.317\n", " \n", " 9716_16897\n", "
\n", " +0.304\n", " \n", " 9916_42755\n", "
\n", " +0.291\n", " \n", " 9716_61964\n", "
\n", " +0.261\n", " \n", " 9716_61956\n", "
\n", " +0.229\n", " \n", " 7716_62856\n", "
\n", " +0.189\n", " \n", " 9716_33025\n", "
\n", " +0.166\n", " \n", " 7716_28965\n", "
\n", " +0.141\n", " \n", " 9716_1824\n", "
\n", " +0.127\n", " \n", " 9716_61953 9716_16897\n", "
\n", " … 485 more positive …\n", "
\n", " … 49506 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.315\n", " \n", " 9947_534\n", "
\n", " +0.277\n", " \n", " 9947_514\n", "
\n", " +0.266\n", " \n", " 9741_9987\n", "
\n", " +0.242\n", " \n", " 9741_10016\n", "
\n", " +0.224\n", " \n", " 9708_29186\n", "
\n", " +0.218\n", " \n", " 9708_29206\n", "
\n", " +0.214\n", " \n", " 9741_9986\n", "
\n", " +0.197\n", " \n", " 9741_10006\n", "
\n", " +0.177\n", " \n", " 9741_10016 9741_9987\n", "
\n", " +0.164\n", " \n", " 9708_29206 9708_29186\n", "
\n", " … 655 more positive …\n", "
\n", " … 49336 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.397\n", " \n", " 9758_43523\n", "
\n", " +0.257\n", " \n", " 9053_45315\n", "
\n", " +0.225\n", " \n", " 9916_65282\n", "
\n", " +0.215\n", " \n", " 9758_55574\n", "
\n", " +0.207\n", " \n", " 9916_65302\n", "
\n", " +0.175\n", " \n", " 9716_39425\n", "
\n", " +0.168\n", " \n", " 9053_57632\n", "
\n", " +0.157\n", " \n", " 9735_13068\n", "
\n", " +0.157\n", " \n", " 7752_1337\n", "
\n", " +0.139\n", " \n", " 7752_1336\n", "
\n", " … 716 more positive …\n", "
\n", " … 49275 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.549\n", " \n", " 9935_44310\n", "
\n", " +0.459\n", " \n", " 9935_44290\n", "
\n", " +0.285\n", " \n", " 9935_44310 9935_44290\n", "
\n", " +0.277\n", " \n", " 9935_44290 9935_44310\n", "
\n", " +0.273\n", " \n", " 9935_44292\n", "
\n", " +0.200\n", " \n", " 9935_44290 9935_44310 9935_44290\n", "
\n", " +0.197\n", " \n", " 9935_44310 9935_44290 9935_44310\n", "
\n", " +0.100\n", " \n", " 9935_44310 9935_44292\n", "
\n", " +0.095\n", " \n", " 9935_8449\n", "
\n", " +0.091\n", " \n", " 9935_44310 9935_44310\n", "
\n", " … 740 more positive …\n", "
\n", " … 49251 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.294\n", " \n", " 9937_29185\n", "
\n", " +0.276\n", " \n", " 9732_50437\n", "
\n", " +0.223\n", " \n", " 9937_29196\n", "
\n", " +0.222\n", " \n", " 9716_27424\n", "
\n", " +0.212\n", " \n", " 9716_19974\n", "
\n", " +0.209\n", " \n", " 9716_27395\n", "
\n", " +0.209\n", " \n", " 9732_5378\n", "
\n", " +0.198\n", " \n", " 9705_2049\n", "
\n", " +0.186\n", " \n", " 9716_19971\n", "
\n", " +0.178\n", " \n", " 9937_28161\n", "
\n", " … 823 more positive …\n", "
\n", " … 49168 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.468\n", " \n", " 7716_3579\n", "
\n", " +0.397\n", " \n", " 9716_34606\n", "
\n", " +0.263\n", " \n", " 7716_3579 9716_34606\n", "
\n", " +0.253\n", " \n", " 9716_34606 7716_3579\n", "
\n", " +0.204\n", " \n", " 9745_10307\n", "
\n", " +0.149\n", " \n", " 9745_10314\n", "
\n", " +0.137\n", " \n", " 9716_9218\n", "
\n", " +0.137\n", " \n", " 9754_12964\n", "
\n", " +0.131\n", " \n", " 7716_3579 9716_34606 7716_3579\n", "
\n", " +0.126\n", " \n", " 9716_34609\n", "
\n", " … 137 more positive …\n", "
\n", " … 49854 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.371\n", " \n", " 9732_27168\n", "
\n", " +0.371\n", " \n", " 9732_27139\n", "
\n", " +0.335\n", " \n", " 9732_27168 9732_27139\n", "
\n", " +0.286\n", " \n", " 9732_27139 9732_27168\n", "
\n", " +0.250\n", " \n", " 9934_16130\n", "
\n", " +0.215\n", " \n", " 9732_27168 9732_27139 9732_27168\n", "
\n", " +0.215\n", " \n", " 9934_16150\n", "
\n", " +0.213\n", " \n", " 9732_27139 9732_27168 9732_27139\n", "
\n", " +0.194\n", " \n", " 9934_36609\n", "
\n", " +0.184\n", " \n", " 9934_16150 9934_16130\n", "
\n", " … 270 more positive …\n", "
\n", " … 49721 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.626\n", " \n", " 7755_6981\n", "
\n", " +0.501\n", " \n", " 7755_6981 7755_6981\n", "
\n", " +0.340\n", " \n", " 7755_6981 7755_6981 7755_6981\n", "
\n", " +0.243\n", " \n", " 9745_10316\n", "
\n", " +0.202\n", " \n", " 7755_62987\n", "
\n", " +0.146\n", " \n", " 9745_10303 9745_10316\n", "
\n", " +0.125\n", " \n", " 7749_25397\n", "
\n", " +0.121\n", " \n", " 9754_44238\n", "
\n", " +0.109\n", " \n", " 9745_10303\n", "
\n", " +0.091\n", " \n", " 9745_10308 9754_44238\n", "
\n", " … 23 more positive …\n", "
\n", " … 49968 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.507\n", " \n", " 7757_21260\n", "
\n", " +0.487\n", " \n", " 7743_21261\n", "
\n", " +0.330\n", " \n", " 7743_21261 7757_21260\n", "
\n", " +0.324\n", " \n", " 7757_21260 7743_21261\n", "
\n", " +0.228\n", " \n", " 7757_21260 7757_21260\n", "
\n", " +0.183\n", " \n", " 7757_21260 7743_21261 7757_21260\n", "
\n", " +0.183\n", " \n", " 7743_21261 7757_21260 7743_21261\n", "
\n", " +0.177\n", " \n", " 7743_21261 7743_21261\n", "
\n", " +0.146\n", " \n", " 9757_21261\n", "
\n", " +0.138\n", " \n", " 7743_21261 7757_21260 7757_21260\n", "
\n", " … 54 more positive …\n", "
\n", " … 49937 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.546\n", " \n", " 9735_26627\n", "
\n", " +0.380\n", " \n", " 9937_1537\n", "
\n", " +0.283\n", " \n", " 9736_11780\n", "
\n", " +0.264\n", " \n", " 9736_11782\n", "
\n", " +0.219\n", " \n", " 9735_19462\n", "
\n", " +0.204\n", " \n", " 9716_55558\n", "
\n", " +0.152\n", " \n", " 9735_6150\n", "
\n", " +0.149\n", " \n", " 7752_61571\n", "
\n", " +0.145\n", " \n", " 9935_47873\n", "
\n", " +0.141\n", " \n", " 9736_33025\n", "
\n", " … 496 more positive …\n", "
\n", " … 49495 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.490\n", " \n", " 7755_32046\n", "
\n", " +0.376\n", " \n", " 7755_35296\n", "
\n", " +0.275\n", " \n", " 9752_15575\n", "
\n", " +0.237\n", " \n", " 7755_32046 7755_35296\n", "
\n", " +0.227\n", " \n", " 9767_11599\n", "
\n", " +0.226\n", " \n", " 7755_30238\n", "
\n", " +0.160\n", " \n", " 7755_38846\n", "
\n", " +0.157\n", " \n", " 7755_35296 7755_32046\n", "
\n", " +0.151\n", " \n", " 7755_35299\n", "
\n", " +0.137\n", " \n", " 7755_38846 7755_32046\n", "
\n", " … 161 more positive …\n", "
\n", " … 49830 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.447\n", " \n", " 7755_26527\n", "
\n", " +0.275\n", " \n", " 9752_14267\n", "
\n", " +0.249\n", " \n", " 7755_26527 9700_32785\n", "
\n", " +0.249\n", " \n", " 7755_26527 9700_32785 9752_14633\n", "
\n", " +0.240\n", " \n", " 9700_32785 9752_14633\n", "
\n", " +0.192\n", " \n", " 7755_31336\n", "
\n", " +0.190\n", " \n", " 9700_32785\n", "
\n", " +0.171\n", " \n", " 9716_7033\n", "
\n", " +0.167\n", " \n", " 7755_26527 7755_26527\n", "
\n", " +0.161\n", " \n", " 9752_14633\n", "
\n", " … 173 more positive …\n", "
\n", " … 49818 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.472\n", " \n", " 9916_21516\n", "
\n", " +0.428\n", " \n", " 9916_21505\n", "
\n", " +0.297\n", " \n", " 9916_21505 9916_21516\n", "
\n", " +0.286\n", " \n", " 9916_21516 9916_21505\n", "
\n", " +0.240\n", " \n", " 9734_48387\n", "
\n", " +0.180\n", " \n", " 9916_21516 9916_21505 9916_21516\n", "
\n", " +0.175\n", " \n", " 9916_21505 9916_21516 9916_21505\n", "
\n", " +0.122\n", " \n", " 9734_48385\n", "
\n", " +0.105\n", " \n", " 9916_21536\n", "
\n", " +0.095\n", " \n", " 9774_54788\n", "
\n", " … 846 more positive …\n", "
\n", " … 49145 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.471\n", " \n", " 9934_56066\n", "
\n", " +0.372\n", " \n", " 9934_35329\n", "
\n", " +0.328\n", " \n", " 9934_56086\n", "
\n", " +0.242\n", " \n", " 9934_35340\n", "
\n", " +0.207\n", " \n", " 9934_56068\n", "
\n", " +0.206\n", " \n", " 7752_3098\n", "
\n", " +0.194\n", " \n", " 9934_56066 9934_35329\n", "
\n", " +0.188\n", " \n", " 9934_35329 9934_56066\n", "
\n", " +0.183\n", " \n", " 7752_52368\n", "
\n", " +0.150\n", " \n", " 9934_35332\n", "
\n", " … 461 more positive …\n", "
\n", " … 49530 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.366\n", " \n", " 9934_24834\n", "
\n", " +0.364\n", " \n", " 9934_24854\n", "
\n", " +0.305\n", " \n", " 5043_5890\n", "
\n", " +0.263\n", " \n", " 5043_50966\n", "
\n", " +0.260\n", " \n", " 9934_24834 9934_24854\n", "
\n", " +0.260\n", " \n", " 9934_24854 9934_24834\n", "
\n", " +0.229\n", " \n", " 9934_24833\n", "
\n", " +0.191\n", " \n", " 5043_5890 5043_50966\n", "
\n", " +0.187\n", " \n", " 5043_50966 5043_5890\n", "
\n", " +0.157\n", " \n", " 9934_24854 9934_24834 9934_24854\n", "
\n", " … 665 more positive …\n", "
\n", " … 49326 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.246\n", " \n", " 9788_34562\n", "
\n", " +0.231\n", " \n", " 9734_14337\n", "
\n", " +0.220\n", " \n", " 9934_6657\n", "
\n", " +0.210\n", " \n", " 9717_12802\n", "
\n", " +0.207\n", " \n", " 9717_12805\n", "
\n", " +0.182\n", " \n", " 9734_14341\n", "
\n", " +0.179\n", " \n", " 9711_4353\n", "
\n", " +0.150\n", " \n", " 9717_4613\n", "
\n", " +0.146\n", " \n", " 9934_51714\n", "
\n", " +0.143\n", " \n", " 9717_60673\n", "
\n", " … 899 more positive …\n", "
\n", " … 49092 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.411\n", " \n", " 9916_20226\n", "
\n", " +0.394\n", " \n", " 9916_20246\n", "
\n", " +0.327\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.321\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.250\n", " \n", " 9916_20226 9916_20246 9916_20226\n", "
\n", " +0.250\n", " \n", " 9916_20246 9916_20226 9916_20246\n", "
\n", " +0.215\n", " \n", " 9739_29953\n", "
\n", " +0.209\n", " \n", " 9739_10502\n", "
\n", " +0.203\n", " \n", " 9739_10502 9739_29953\n", "
\n", " +0.197\n", " \n", " 9739_29953 9739_10502\n", "
\n", " … 593 more positive …\n", "
\n", " … 49398 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.356\n", " \n", " 9716_2049\n", "
\n", " +0.347\n", " \n", " 9716_2052\n", "
\n", " +0.344\n", " \n", " 9716_2060\n", "
\n", " +0.212\n", " \n", " 5005_65285\n", "
\n", " +0.203\n", " \n", " 9935_32534\n", "
\n", " +0.191\n", " \n", " 9716_2060 9716_2049\n", "
\n", " +0.184\n", " \n", " 9716_2049 9716_2060\n", "
\n", " +0.180\n", " \n", " 9935_11523\n", "
\n", " +0.177\n", " \n", " 5005_8736\n", "
\n", " +0.152\n", " \n", " 9716_2052 9716_2049\n", "
\n", " … 567 more positive …\n", "
\n", " … 49424 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.511\n", " \n", " 7716_2147\n", "
\n", " +0.490\n", " \n", " 7716_38835\n", "
\n", " +0.211\n", " \n", " 7716_2866\n", "
\n", " +0.202\n", " \n", " 7716_65523\n", "
\n", " +0.195\n", " \n", " 7716_62858\n", "
\n", " +0.185\n", " \n", " 7716_36730\n", "
\n", " +0.185\n", " \n", " 7716_6026\n", "
\n", " +0.166\n", " \n", " 7716_38835 7716_38835\n", "
\n", " +0.141\n", " \n", " 9716_36734\n", "
\n", " +0.133\n", " \n", " 9716_33838\n", "
\n", " … 99 more positive …\n", "
\n", " … 49892 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.463\n", " \n", " 9758_57092\n", "
\n", " +0.328\n", " \n", " 7747_3968\n", "
\n", " +0.323\n", " \n", " 9734_12803\n", "
\n", " +0.282\n", " \n", " 9734_12832\n", "
\n", " +0.168\n", " \n", " 9935_32514\n", "
\n", " +0.165\n", " \n", " 9734_12803 9758_57092\n", "
\n", " +0.158\n", " \n", " 7702_4341\n", "
\n", " +0.145\n", " \n", " 9758_57092 9734_12803\n", "
\n", " +0.140\n", " \n", " 7746_3617\n", "
\n", " +0.136\n", " \n", " 9758_57092 9734_12832\n", "
\n", " … 706 more positive …\n", "
\n", " … 49285 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.463\n", " \n", " 7755_33266\n", "
\n", " +0.418\n", " \n", " 7755_55462\n", "
\n", " +0.229\n", " \n", " 7755_33266 7755_55462\n", "
\n", " +0.206\n", " \n", " 7755_6988\n", "
\n", " +0.178\n", " \n", " 7755_55462 7755_33266\n", "
\n", " +0.149\n", " \n", " 7700_13970\n", "
\n", " +0.140\n", " \n", " 7752_6193\n", "
\n", " +0.131\n", " \n", " 7754_35304\n", "
\n", " +0.119\n", " \n", " 7700_37286\n", "
\n", " +0.111\n", " \n", " 7700_803 7700_13970\n", "
\n", " … 284 more positive …\n", "
\n", " … 49707 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.472\n", " \n", " 9935_62467\n", "
\n", " +0.372\n", " \n", " 9935_62496\n", "
\n", " +0.341\n", " \n", " 9935_62466\n", "
\n", " +0.332\n", " \n", " 9935_62486\n", "
\n", " +0.211\n", " \n", " 9935_62467 9935_62466\n", "
\n", " +0.193\n", " \n", " 9935_62466 9935_62467\n", "
\n", " +0.174\n", " \n", " 9935_62486 9935_62467\n", "
\n", " +0.166\n", " \n", " 9935_62466 9935_62486\n", "
\n", " +0.165\n", " \n", " 9935_62496 9935_62486\n", "
\n", " +0.155\n", " \n", " 9935_62486 9935_62496\n", "
\n", " … 602 more positive …\n", "
\n", " … 49389 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.375\n", " \n", " 7700_6192\n", "
\n", " +0.367\n", " \n", " 7716_3497 7716_3497\n", "
\n", " +0.366\n", " \n", " 7716_3497 7716_3497 7716_3497\n", "
\n", " +0.312\n", " \n", " 7716_18164\n", "
\n", " +0.312\n", " \n", " 7716_3497\n", "
\n", " +0.296\n", " \n", " 9700_14516\n", "
\n", " +0.226\n", " \n", " 9700_8631\n", "
\n", " +0.213\n", " \n", " 7716_18165\n", "
\n", " +0.183\n", " \n", " 7700_6192 9700_14516\n", "
\n", " +0.176\n", " \n", " 7716_18164 7716_18164\n", "
\n", " … 16 more positive …\n", "
\n", " … 49975 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.463\n", " \n", " 9916_23809\n", "
\n", " +0.340\n", " \n", " 9935_53516\n", "
\n", " +0.274\n", " \n", " 9916_3333\n", "
\n", " +0.235\n", " \n", " 9734_12812 9734_12801\n", "
\n", " +0.234\n", " \n", " 9916_3340\n", "
\n", " +0.223\n", " \n", " 9734_12801 9734_12812\n", "
\n", " +0.219\n", " \n", " 9734_12801 9734_12812 9734_12801\n", "
\n", " +0.213\n", " \n", " 9734_12812\n", "
\n", " +0.211\n", " \n", " 9734_12801\n", "
\n", " +0.203\n", " \n", " 9734_12812 9734_12801 9734_12812\n", "
\n", " … 540 more positive …\n", "
\n", " … 49451 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.333\n", " \n", " 9916_42764\n", "
\n", " +0.310\n", " \n", " 7755_15800\n", "
\n", " +0.295\n", " \n", " 7755_6982\n", "
\n", " +0.285\n", " \n", " 9916_42753\n", "
\n", " +0.235\n", " \n", " 9754_51222\n", "
\n", " +0.234\n", " \n", " 9754_51202\n", "
\n", " +0.196\n", " \n", " 7755_15801\n", "
\n", " +0.190\n", " \n", " 7752_1959\n", "
\n", " +0.150\n", " \n", " 9754_43526\n", "
\n", " +0.139\n", " \n", " 7752_1941\n", "
\n", " … 747 more positive …\n", "
\n", " … 49244 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.419\n", " \n", " 9716_62466\n", "
\n", " +0.360\n", " \n", " 9716_62486\n", "
\n", " +0.333\n", " \n", " 9716_62466 9716_62486\n", "
\n", " +0.330\n", " \n", " 9716_62486 9716_62466\n", "
\n", " +0.271\n", " \n", " 9716_62466 9716_62486 9716_62466\n", "
\n", " +0.257\n", " \n", " 9716_62469\n", "
\n", " +0.247\n", " \n", " 9716_62486 9716_62466 9716_62486\n", "
\n", " +0.158\n", " \n", " 9716_62469 9716_62466\n", "
\n", " +0.155\n", " \n", " 9716_62466 9716_62469\n", "
\n", " +0.140\n", " \n", " 7797_40544\n", "
\n", " … 657 more positive …\n", "
\n", " … 49334 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.444\n", " \n", " 7752_3103\n", "
\n", " +0.246\n", " \n", " 9752_33921\n", "
\n", " +0.246\n", " \n", " 9734_33312 9734_33283\n", "
\n", " +0.234\n", " \n", " 9734_33312\n", "
\n", " +0.232\n", " \n", " 9734_33283 9734_33312\n", "
\n", " +0.229\n", " \n", " 9734_33312 9734_33283 9734_33312\n", "
\n", " +0.221\n", " \n", " 9734_33283\n", "
\n", " +0.215\n", " \n", " 9734_33283 9734_33312 9734_33283\n", "
\n", " +0.205\n", " \n", " 9934_49921\n", "
\n", " +0.182\n", " \n", " 9752_3090\n", "
\n", " … 650 more positive …\n", "
\n", " … 49341 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.341\n", " \n", " 9934_46624\n", "
\n", " +0.324\n", " \n", " 9739_27905 9739_27905\n", "
\n", " +0.303\n", " \n", " 9934_46595\n", "
\n", " +0.303\n", " \n", " 9740_8972\n", "
\n", " +0.284\n", " \n", " 9739_27905 9739_27905 9739_27905\n", "
\n", " +0.273\n", " \n", " 9739_27905\n", "
\n", " +0.216\n", " \n", " 9916_62476 9916_62465 9916_62476\n", "
\n", " +0.194\n", " \n", " 9916_62476\n", "
\n", " +0.190\n", " \n", " 9916_62476 9916_62465\n", "
\n", " +0.178\n", " \n", " 9916_62465 9916_62476\n", "
\n", " … 38 more positive …\n", "
\n", " … 49953 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.505\n", " \n", " 9937_42241\n", "
\n", " +0.422\n", " \n", " 9937_35585\n", "
\n", " +0.367\n", " \n", " 9937_42252\n", "
\n", " +0.347\n", " \n", " 9937_35596\n", "
\n", " +0.203\n", " \n", " 9937_35585 9937_42241\n", "
\n", " +0.177\n", " \n", " 9937_42241 9937_35585\n", "
\n", " +0.169\n", " \n", " 9937_35596 9937_42252\n", "
\n", " +0.146\n", " \n", " 9937_42252 9937_35596\n", "
\n", " +0.138\n", " \n", " 9937_42244\n", "
\n", " +0.136\n", " \n", " 7757_8040\n", "
\n", " … 478 more positive …\n", "
\n", " … 49513 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.448\n", " \n", " 7716_35363\n", "
\n", " +0.275\n", " \n", " 7716_25270\n", "
\n", " +0.250\n", " \n", " 7716_3976\n", "
\n", " +0.236\n", " \n", " 7716_35365\n", "
\n", " +0.222\n", " \n", " 9716_20252\n", "
\n", " +0.216\n", " \n", " 9716_20251\n", "
\n", " +0.211\n", " \n", " 7716_35364\n", "
\n", " +0.193\n", " \n", " 7752_7903\n", "
\n", " +0.179\n", " \n", " 7752_7749\n", "
\n", " +0.178\n", " \n", " 9716_33844\n", "
\n", " … 178 more positive …\n", "
\n", " … 49813 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.375\n", " \n", " 7746_6555\n", "
\n", " +0.364\n", " \n", " 7752_59117\n", "
\n", " +0.287\n", " \n", " 7752_59118\n", "
\n", " +0.248\n", " \n", " 9953_32901\n", "
\n", " +0.243\n", " \n", " 7716_25354\n", "
\n", " +0.241\n", " \n", " 7752_59117 7752_59118\n", "
\n", " +0.234\n", " \n", " 7752_59118 7752_59117\n", "
\n", " +0.194\n", " \n", " 7752_59117 7752_59118 7752_59117\n", "
\n", " +0.174\n", " \n", " 9953_32901 7746_6555\n", "
\n", " +0.168\n", " \n", " 7716_35360\n", "
\n", " … 419 more positive …\n", "
\n", " … 49572 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.548\n", " \n", " 7752_4705\n", "
\n", " +0.301\n", " \n", " 7752_56488\n", "
\n", " +0.285\n", " \n", " 5069_57369\n", "
\n", " +0.222\n", " \n", " 5015_57368\n", "
\n", " +0.190\n", " \n", " 7752_45995\n", "
\n", " +0.190\n", " \n", " 5069_57364\n", "
\n", " +0.187\n", " \n", " 7752_36321\n", "
\n", " +0.148\n", " \n", " 7755_36135\n", "
\n", " +0.143\n", " \n", " 7752_4705 7752_56488\n", "
\n", " +0.143\n", " \n", " 7755_62891\n", "
\n", " … 244 more positive …\n", "
\n", " … 49747 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.385\n", " \n", " 9734_30486\n", "
\n", " +0.378\n", " \n", " 9734_47107\n", "
\n", " +0.351\n", " \n", " 9734_47136\n", "
\n", " +0.325\n", " \n", " 9734_30466\n", "
\n", " +0.202\n", " \n", " 9734_30466 9734_47107\n", "
\n", " +0.179\n", " \n", " 9734_47107 9734_30466\n", "
\n", " +0.166\n", " \n", " 9734_30486 9734_30466\n", "
\n", " +0.162\n", " \n", " 9734_47136 9734_30486\n", "
\n", " +0.160\n", " \n", " 9734_30466 9734_30486\n", "
\n", " +0.157\n", " \n", " 9734_47107 9734_47136\n", "
\n", " … 280 more positive …\n", "
\n", " … 49711 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.412\n", " \n", " 7716_33417\n", "
\n", " +0.394\n", " \n", " 9716_33096\n", "
\n", " +0.262\n", " \n", " 7716_33417 9716_33096\n", "
\n", " +0.252\n", " \n", " 9716_33096 7716_33417\n", "
\n", " +0.246\n", " \n", " 9736_48406\n", "
\n", " +0.215\n", " \n", " 9734_5635\n", "
\n", " +0.214\n", " \n", " 9736_48386\n", "
\n", " +0.197\n", " \n", " 9736_48406 9736_48386\n", "
\n", " +0.193\n", " \n", " 9736_48386 9736_48406\n", "
\n", " +0.155\n", " \n", " 9736_48386 9736_48406 9736_48386\n", "
\n", " … 611 more positive …\n", "
\n", " … 49380 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.507\n", " \n", " 9916_46338\n", "
\n", " +0.306\n", " \n", " 9739_44320\n", "
\n", " +0.257\n", " \n", " 9739_44291\n", "
\n", " +0.221\n", " \n", " 9916_46339\n", "
\n", " +0.201\n", " \n", " 9916_46338 9916_46338\n", "
\n", " +0.196\n", " \n", " 9739_44320 9739_44291\n", "
\n", " +0.187\n", " \n", " 9916_46338 9916_20993\n", "
\n", " +0.185\n", " \n", " 9739_44291 9739_44320\n", "
\n", " +0.180\n", " \n", " 9916_20993 9916_46338\n", "
\n", " +0.154\n", " \n", " 9916_20993\n", "
\n", " … 917 more positive …\n", "
\n", " … 49074 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.424\n", " \n", " 7742_36320\n", "
\n", " +0.393\n", " \n", " 7742_5774\n", "
\n", " +0.320\n", " \n", " 7700_3394\n", "
\n", " +0.266\n", " \n", " 7727_52509\n", "
\n", " +0.246\n", " \n", " 7716_5458\n", "
\n", " +0.227\n", " \n", " 7700_3391\n", "
\n", " +0.226\n", " \n", " 7716_60012\n", "
\n", " +0.176\n", " \n", " 7742_5774 7742_36320\n", "
\n", " +0.172\n", " \n", " 7716_5458 7700_3394\n", "
\n", " +0.149\n", " \n", " 7700_3394 7716_5458\n", "
\n", " … 218 more positive …\n", "
\n", " … 49773 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.368\n", " \n", " 9734_61728\n", "
\n", " +0.352\n", " \n", " 9734_61699 9734_61728\n", "
\n", " +0.351\n", " \n", " 9734_61699\n", "
\n", " +0.320\n", " \n", " 9734_61728 9734_61699\n", "
\n", " +0.276\n", " \n", " 9734_61728 9734_61699 9734_61728\n", "
\n", " +0.272\n", " \n", " 9734_61699 9734_61728 9734_61699\n", "
\n", " +0.203\n", " \n", " 9934_56067\n", "
\n", " +0.201\n", " \n", " 9934_56065\n", "
\n", " +0.199\n", " \n", " 9934_49666\n", "
\n", " +0.109\n", " \n", " 9934_56076\n", "
\n", " … 776 more positive …\n", "
\n", " … 49215 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.424\n", " \n", " 9916_771 9916_800\n", "
\n", " +0.373\n", " \n", " 9916_800 9916_771\n", "
\n", " +0.346\n", " \n", " 9916_771\n", "
\n", " +0.341\n", " \n", " 9916_771 9916_800 9916_771\n", "
\n", " +0.335\n", " \n", " 9916_800 9916_771 9916_800\n", "
\n", " +0.319\n", " \n", " 9916_800\n", "
\n", " +0.254\n", " \n", " 7755_37288\n", "
\n", " +0.181\n", " \n", " 9739_56580\n", "
\n", " +0.115\n", " \n", " 9739_56580 7755_37288\n", "
\n", " +0.105\n", " \n", " 7755_37288 9739_56580\n", "
\n", " … 467 more positive …\n", "
\n", " … 49524 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.503\n", " \n", " 9000_6150\n", "
\n", " +0.466\n", " \n", " 9000_6147\n", "
\n", " +0.243\n", " \n", " 9000_56066\n", "
\n", " +0.224\n", " \n", " 9734_64258\n", "
\n", " +0.221\n", " \n", " 9000_6150 9000_6147\n", "
\n", " +0.219\n", " \n", " 9000_6147 9000_6150\n", "
\n", " +0.214\n", " \n", " 9734_64278\n", "
\n", " +0.175\n", " \n", " 9734_64258 9734_64278\n", "
\n", " +0.172\n", " \n", " 9734_64278 9734_64258\n", "
\n", " +0.148\n", " \n", " 9000_6150 9000_6150\n", "
\n", " … 357 more positive …\n", "
\n", " … 49634 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.480\n", " \n", " 9916_5121\n", "
\n", " +0.405\n", " \n", " 9916_5132\n", "
\n", " +0.298\n", " \n", " 7752_3570\n", "
\n", " +0.241\n", " \n", " 9734_64258\n", "
\n", " +0.203\n", " \n", " 9734_64278\n", "
\n", " +0.171\n", " \n", " 9734_64258 9734_64278\n", "
\n", " +0.168\n", " \n", " 9916_5132 9916_5121\n", "
\n", " +0.168\n", " \n", " 9916_5121 9916_5132\n", "
\n", " +0.153\n", " \n", " 9734_64278 9734_64258\n", "
\n", " +0.141\n", " \n", " 9734_64258 9734_64278 9734_64258\n", "
\n", " … 581 more positive …\n", "
\n", " … 49410 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.429\n", " \n", " 7752_3100\n", "
\n", " +0.396\n", " \n", " 9752_14478\n", "
\n", " +0.293\n", " \n", " 7700_33790\n", "
\n", " +0.229\n", " \n", " 7752_3100 9752_14478\n", "
\n", " +0.229\n", " \n", " 9752_14478 7752_3100\n", "
\n", " +0.224\n", " \n", " 7752_6193\n", "
\n", " +0.170\n", " \n", " 7700_33784\n", "
\n", " +0.151\n", " \n", " 7752_5712\n", "
\n", " +0.142\n", " \n", " 7752_51351\n", "
\n", " +0.131\n", " \n", " 7752_30043\n", "
\n", " … 261 more positive …\n", "
\n", " … 49730 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.510\n", " \n", " 9734_61728\n", "
\n", " +0.381\n", " \n", " 9734_61699\n", "
\n", " +0.269\n", " \n", " 9734_5633\n", "
\n", " +0.224\n", " \n", " 9734_61699 9734_61728\n", "
\n", " +0.213\n", " \n", " 9734_61702\n", "
\n", " +0.207\n", " \n", " 9734_61728 9734_61699\n", "
\n", " +0.188\n", " \n", " 9734_5633 9734_61728\n", "
\n", " +0.178\n", " \n", " 9734_61728 9734_5633\n", "
\n", " +0.152\n", " \n", " 9734_61728 9734_61728\n", "
\n", " +0.149\n", " \n", " 9734_5644\n", "
\n", " … 245 more positive …\n", "
\n", " … 49746 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.371\n", " \n", " 7716_3323\n", "
\n", " +0.356\n", " \n", " 7752_1981\n", "
\n", " +0.278\n", " \n", " 9752_15548\n", "
\n", " +0.261\n", " \n", " 7752_1981 9752_15548\n", "
\n", " +0.258\n", " \n", " 9752_15548 7752_1981\n", "
\n", " +0.229\n", " \n", " 7716_3323 9716_33229\n", "
\n", " +0.214\n", " \n", " 9716_33229\n", "
\n", " +0.201\n", " \n", " 9716_33229 7716_3323\n", "
\n", " +0.185\n", " \n", " 9716_33102 7716_3323\n", "
\n", " +0.144\n", " \n", " 9716_33102\n", "
\n", " … 360 more positive …\n", "
\n", " … 49631 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.406\n", " \n", " 9716_33107\n", "
\n", " +0.318\n", " \n", " 9716_6427\n", "
\n", " +0.310\n", " \n", " 9752_509\n", "
\n", " +0.227\n", " \n", " 7730_3507 9716_6427\n", "
\n", " +0.202\n", " \n", " 7730_3803\n", "
\n", " +0.197\n", " \n", " 9752_509 9700_8601\n", "
\n", " +0.197\n", " \n", " 9716_33107 7730_3803\n", "
\n", " +0.197\n", " \n", " 9716_6427 9716_33107\n", "
\n", " +0.176\n", " \n", " 7730_3803 7755_38849\n", "
\n", " +0.159\n", " \n", " 9716_33107 9716_33107\n", "
\n", " … 101 more positive …\n", "
\n", " … 49890 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.347\n", " \n", " 9934_12038\n", "
\n", " +0.256\n", " \n", " 7752_1350\n", "
\n", " +0.251\n", " \n", " 9739_52741\n", "
\n", " +0.246\n", " \n", " 7752_1346\n", "
\n", " +0.172\n", " \n", " 9770_10154\n", "
\n", " +0.164\n", " \n", " 9733_39685\n", "
\n", " +0.153\n", " \n", " 9916_3586\n", "
\n", " +0.150\n", " \n", " 9754_43526\n", "
\n", " +0.150\n", " \n", " 7755_33269\n", "
\n", " +0.147\n", " \n", " 9752_1333\n", "
\n", " … 706 more positive …\n", "
\n", " … 49285 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.622\n", " \n", " 7716_21024\n", "
\n", " +0.403\n", " \n", " 9716_20729\n", "
\n", " +0.287\n", " \n", " 9716_20649\n", "
\n", " +0.268\n", " \n", " 9716_20729 7716_21024\n", "
\n", " +0.221\n", " \n", " 7716_21024 9716_20729\n", "
\n", " +0.148\n", " \n", " 7716_21024 9716_20649\n", "
\n", " +0.145\n", " \n", " 9716_20649 7716_21024\n", "
\n", " +0.122\n", " \n", " 9716_17280\n", "
\n", " +0.118\n", " \n", " 7716_21024 9716_20729 7716_21024\n", "
\n", " +0.108\n", " \n", " 7716_21024 7716_21024\n", "
\n", " … 357 more positive …\n", "
\n", " … 49634 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.475\n", " \n", " 9776_50694\n", "
\n", " +0.339\n", " \n", " 9776_50691\n", "
\n", " +0.322\n", " \n", " 9776_53765\n", "
\n", " +0.231\n", " \n", " 9043_28421\n", "
\n", " +0.208\n", " \n", " 9043_28420\n", "
\n", " +0.196\n", " \n", " 9734_47110\n", "
\n", " +0.183\n", " \n", " 9776_50720\n", "
\n", " +0.151\n", " \n", " 9776_50694 9776_50691\n", "
\n", " +0.146\n", " \n", " 9776_53765 9776_50694\n", "
\n", " +0.142\n", " \n", " 9776_50694 9776_53765\n", "
\n", " … 489 more positive …\n", "
\n", " … 49502 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.288\n", " \n", " 9716_6427\n", "
\n", " +0.278\n", " \n", " 9716_20257\n", "
\n", " +0.271\n", " \n", " 9716_20257 7730_3803\n", "
\n", " +0.248\n", " \n", " 7730_3803\n", "
\n", " +0.247\n", " \n", " 9752_19080\n", "
\n", " +0.211\n", " \n", " 9716_6427 9716_20257\n", "
\n", " +0.173\n", " \n", " 9716_6427 9716_6427\n", "
\n", " +0.161\n", " \n", " 7730_3803 7755_38849\n", "
\n", " +0.151\n", " \n", " 7755_38849\n", "
\n", " +0.151\n", " \n", " 9716_6427 9716_6427 9716_20257\n", "
\n", " … 124 more positive …\n", "
\n", " … 49867 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.336\n", " \n", " 9734_5634 9734_5654\n", "
\n", " +0.333\n", " \n", " 9734_5634\n", "
\n", " +0.309\n", " \n", " 9734_5654 9734_5634\n", "
\n", " +0.291\n", " \n", " 9734_5654\n", "
\n", " +0.291\n", " \n", " 9734_5634 9734_5654 9734_5634\n", "
\n", " +0.269\n", " \n", " 9916_65283\n", "
\n", " +0.268\n", " \n", " 9916_65312 9916_65283\n", "
\n", " +0.258\n", " \n", " 9916_65312\n", "
\n", " +0.256\n", " \n", " 9734_5654 9734_5634 9734_5654\n", "
\n", " +0.250\n", " \n", " 9916_65283 9916_65312\n", "
\n", " … 830 more positive …\n", "
\n", " … 49161 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.508\n", " \n", " 7716_3387\n", "
\n", " +0.330\n", " \n", " 7755_15818\n", "
\n", " +0.261\n", " \n", " 7716_3386\n", "
\n", " +0.256\n", " \n", " 7755_15810\n", "
\n", " +0.204\n", " \n", " 7755_15818 7716_3387\n", "
\n", " +0.182\n", " \n", " 7755_15810 7716_3387\n", "
\n", " +0.174\n", " \n", " 7716_3387 7755_15818\n", "
\n", " +0.172\n", " \n", " 7716_3385\n", "
\n", " +0.148\n", " \n", " 7716_3387 7755_15810\n", "
\n", " +0.147\n", " \n", " 7755_15830\n", "
\n", " … 322 more positive …\n", "
\n", " … 49669 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.437\n", " \n", " 9935_27916\n", "
\n", " +0.408\n", " \n", " 9935_27905\n", "
\n", " +0.365\n", " \n", " 9739_24326\n", "
\n", " +0.226\n", " \n", " 9716_7174\n", "
\n", " +0.174\n", " \n", " 9935_27916 9935_27905\n", "
\n", " +0.171\n", " \n", " 9935_27905 9935_27916\n", "
\n", " +0.167\n", " \n", " 9716_7171\n", "
\n", " +0.157\n", " \n", " 9739_24326 9716_7171\n", "
\n", " +0.141\n", " \n", " 9716_48388\n", "
\n", " +0.138\n", " \n", " 9716_7171 9739_24326\n", "
\n", " … 658 more positive …\n", "
\n", " … 49333 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.750\n", " \n", " 7757_2510\n", "
\n", " +0.653\n", " \n", " 7757_2510 7757_2510\n", "
\n", " … 49991 more negative …\n", "
\n", " -0.006\n", " \n", " 9702_30576\n", "
\n", " -0.006\n", " \n", " 9700_8607\n", "
\n", " -0.006\n", " \n", " 9916_20226\n", "
\n", " -0.006\n", " \n", " 9734_61702\n", "
\n", " -0.007\n", " \n", " 9702_30571\n", "
\n", " -0.008\n", " \n", " 9752_14642\n", "
\n", " -0.009\n", " \n", " 9752_14633\n", "
\n", " -0.009\n", " \n", " <BIAS>\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.229\n", " \n", " 9773_4612\n", "
\n", " +0.195\n", " \n", " 9071_19715\n", "
\n", " +0.172\n", " \n", " 9773_4610\n", "
\n", " +0.168\n", " \n", " 9739_10499\n", "
\n", " +0.165\n", " \n", " 9759_52993\n", "
\n", " +0.139\n", " \n", " 9739_10528\n", "
\n", " +0.133\n", " \n", " 9773_4357\n", "
\n", " +0.129\n", " \n", " 7765_6723\n", "
\n", " +0.126\n", " \n", " 9754_51232\n", "
\n", " +0.123\n", " \n", " 9754_51203\n", "
\n", " … 887 more positive …\n", "
\n", " … 49104 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.512\n", " \n", " 5046_53704\n", "
\n", " +0.512\n", " \n", " 9091_57626\n", "
\n", " +0.327\n", " \n", " 9091_57626 5046_53704\n", "
\n", " +0.326\n", " \n", " 5046_53704 9091_57626\n", "
\n", " +0.218\n", " \n", " 5046_53704 5046_53704\n", "
\n", " +0.206\n", " \n", " 9091_57626 9091_57626\n", "
\n", " +0.186\n", " \n", " 5046_53704 9091_57626 5046_53704\n", "
\n", " +0.179\n", " \n", " 9091_57626 5046_53704 9091_57626\n", "
\n", " +0.146\n", " \n", " 9091_57626 5046_53704 5046_53704\n", "
\n", " +0.146\n", " \n", " 5046_53704 5046_53704 9091_57626\n", "
\n", " … 189 more positive …\n", "
\n", " … 49802 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.353\n", " \n", " 9713_41730\n", "
\n", " +0.294\n", " \n", " 9713_2562\n", "
\n", " +0.282\n", " \n", " 9716_30210 9716_30230 9716_30210\n", "
\n", " +0.273\n", " \n", " 9716_30230 9716_30210\n", "
\n", " +0.267\n", " \n", " 9716_30230 9716_30210 9716_30230\n", "
\n", " +0.253\n", " \n", " 9900_64002\n", "
\n", " +0.246\n", " \n", " 9716_30210 9716_30230\n", "
\n", " +0.213\n", " \n", " 9900_64001\n", "
\n", " +0.202\n", " \n", " 9716_30210\n", "
\n", " +0.202\n", " \n", " 9713_41730 9713_2562\n", "
\n", " … 184 more positive …\n", "
\n", " … 49807 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.472\n", " \n", " 9739_44290\n", "
\n", " +0.413\n", " \n", " 9739_44310\n", "
\n", " +0.312\n", " \n", " 9739_44290 9739_44310\n", "
\n", " +0.303\n", " \n", " 9739_44310 9739_44290\n", "
\n", " +0.298\n", " \n", " 9934_33537\n", "
\n", " +0.207\n", " \n", " 9739_44310 9739_44290 9739_44310\n", "
\n", " +0.203\n", " \n", " 9739_44290 9739_44310 9739_44290\n", "
\n", " +0.179\n", " \n", " 7752_3385\n", "
\n", " +0.138\n", " \n", " 9739_44293\n", "
\n", " +0.119\n", " \n", " 7752_3385 9934_33537\n", "
\n", " … 559 more positive …\n", "
\n", " … 49432 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.683\n", " \n", " 9953_32909\n", "
\n", " +0.364\n", " \n", " 9746_37923\n", "
\n", " +0.306\n", " \n", " 9953_32909 9746_37923\n", "
\n", " +0.243\n", " \n", " 9746_37923 9953_32909\n", "
\n", " +0.191\n", " \n", " 9953_32909 9746_37923 9953_32909\n", "
\n", " +0.174\n", " \n", " 9746_37926\n", "
\n", " +0.139\n", " \n", " 9746_37927\n", "
\n", " +0.139\n", " \n", " 9746_37926 9953_32909\n", "
\n", " +0.139\n", " \n", " 9953_32909 9746_37926\n", "
\n", " +0.121\n", " \n", " 9953_32909 9746_37927\n", "
\n", " … 106 more positive …\n", "
\n", " … 49885 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.450\n", " \n", " 9752_13162\n", "
\n", " +0.217\n", " \n", " 9091_52619\n", "
\n", " +0.216\n", " \n", " 7752_13178\n", "
\n", " +0.205\n", " \n", " 7752_13176\n", "
\n", " +0.204\n", " \n", " 9752_13168\n", "
\n", " +0.188\n", " \n", " 9752_13162 7752_13176\n", "
\n", " +0.173\n", " \n", " 9091_52614\n", "
\n", " +0.173\n", " \n", " 9011_56717\n", "
\n", " +0.169\n", " \n", " 9752_19471\n", "
\n", " +0.164\n", " \n", " 9716_3665\n", "
\n", " … 247 more positive …\n", "
\n", " … 49744 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.423\n", " \n", " 9716_13058\n", "
\n", " +0.274\n", " \n", " 9716_9219\n", "
\n", " +0.239\n", " \n", " 9916_35852\n", "
\n", " +0.211\n", " \n", " 9916_35841\n", "
\n", " +0.210\n", " \n", " 9716_48899\n", "
\n", " +0.202\n", " \n", " 9716_25366\n", "
\n", " +0.194\n", " \n", " 9916_35852 9916_35841\n", "
\n", " +0.189\n", " \n", " 9916_35841 9916_35852\n", "
\n", " +0.165\n", " \n", " 9716_3841\n", "
\n", " +0.155\n", " \n", " 9716_50689\n", "
\n", " … 733 more positive …\n", "
\n", " … 49258 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.278\n", " \n", " 9732_39180\n", "
\n", " +0.246\n", " \n", " 9732_39169\n", "
\n", " +0.239\n", " \n", " 9732_49932\n", "
\n", " +0.200\n", " \n", " 9916_46339\n", "
\n", " +0.196\n", " \n", " 9732_49921\n", "
\n", " +0.171\n", " \n", " 7767_25554\n", "
\n", " +0.147\n", " \n", " 9732_40192\n", "
\n", " +0.137\n", " \n", " 9732_49921 9732_49932\n", "
\n", " +0.122\n", " \n", " 9900_64513\n", "
\n", " +0.122\n", " \n", " 9736_55043\n", "
\n", " … 1040 more positive …\n", "
\n", " … 48951 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.548\n", " \n", " 9716_31787\n", "
\n", " +0.348\n", " \n", " 9746_16333 9716_31787\n", "
\n", " +0.341\n", " \n", " 9746_16333\n", "
\n", " +0.292\n", " \n", " 9716_31787 9746_16333\n", "
\n", " +0.266\n", " \n", " 9716_31787 9746_16333 9716_31787\n", "
\n", " +0.219\n", " \n", " 9716_31787 9746_16330\n", "
\n", " +0.207\n", " \n", " 9746_16330\n", "
\n", " +0.197\n", " \n", " 9746_16330 9716_31787\n", "
\n", " +0.178\n", " \n", " 9716_31787 9746_16330 9716_31787\n", "
\n", " +0.157\n", " \n", " 9746_16333 9716_31787 9746_16333\n", "
\n", " … 173 more positive …\n", "
\n", " … 49818 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.499\n", " \n", " 7752_12914\n", "
\n", " +0.336\n", " \n", " 7746_6554\n", "
\n", " +0.269\n", " \n", " 9752_31489 7752_12914\n", "
\n", " +0.249\n", " \n", " 9752_31489\n", "
\n", " +0.215\n", " \n", " 7752_12914 9752_31489\n", "
\n", " +0.198\n", " \n", " 9752_30414\n", "
\n", " +0.171\n", " \n", " 9752_12950\n", "
\n", " +0.161\n", " \n", " 7752_12914 9752_31489 7752_12914\n", "
\n", " +0.145\n", " \n", " 7752_30411\n", "
\n", " +0.140\n", " \n", " 7746_6553\n", "
\n", " … 327 more positive …\n", "
\n", " … 49664 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.625\n", " \n", " 9752_10853 9752_10853\n", "
\n", " +0.560\n", " \n", " 9752_10853\n", "
\n", " +0.533\n", " \n", " 9752_10853 9752_10853 9752_10853\n", "
\n", " +0.015\n", " \n", " <BIAS>\n", "
\n", " … 49991 more negative …\n", "
\n", " -0.006\n", " \n", " 9700_8607\n", "
\n", " -0.006\n", " \n", " 9916_20226\n", "
\n", " -0.006\n", " \n", " 9734_61702\n", "
\n", " -0.007\n", " \n", " 9702_30571\n", "
\n", " -0.008\n", " \n", " 9752_14642\n", "
\n", " -0.009\n", " \n", " 9752_14633\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.507\n", " \n", " 9716_32506\n", "
\n", " +0.279\n", " \n", " 9716_33092 9716_32506\n", "
\n", " +0.263\n", " \n", " 9716_33092\n", "
\n", " +0.246\n", " \n", " 9716_32506 9716_33092\n", "
\n", " +0.188\n", " \n", " 9716_32506 9716_33092 9716_32506\n", "
\n", " +0.176\n", " \n", " 7798_14544\n", "
\n", " +0.175\n", " \n", " 9767_1125\n", "
\n", " +0.175\n", " \n", " 9716_33096 9716_32506\n", "
\n", " +0.151\n", " \n", " 9716_32506 9716_32506\n", "
\n", " +0.147\n", " \n", " 9716_33096\n", "
\n", " … 150 more positive …\n", "
\n", " … 49841 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.476\n", " \n", " 7716_3976\n", "
\n", " +0.410\n", " \n", " 7716_3976 9716_33102\n", "
\n", " +0.403\n", " \n", " 9716_33102 7716_3976\n", "
\n", " +0.380\n", " \n", " 9716_33102\n", "
\n", " +0.229\n", " \n", " 7716_3976 9716_33102 7716_3976\n", "
\n", " +0.211\n", " \n", " 9716_33102 7716_3976 9716_33102\n", "
\n", " +0.193\n", " \n", " 7716_3976 7716_3976\n", "
\n", " +0.174\n", " \n", " 9716_33102 7716_3976 7716_3976\n", "
\n", " +0.171\n", " \n", " 7716_3976 7716_3976 9716_33102\n", "
\n", " +0.152\n", " \n", " 9716_33102 9716_33102 7716_3976\n", "
\n", " … 200 more positive …\n", "
\n", " … 49791 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.337\n", " \n", " 9701_36610\n", "
\n", " +0.277\n", " \n", " 9900_14594\n", "
\n", " +0.276\n", " \n", " 9716_13827\n", "
\n", " +0.242\n", " \n", " 9701_16130\n", "
\n", " +0.224\n", " \n", " 9701_36609\n", "
\n", " +0.211\n", " \n", " 9701_16129\n", "
\n", " +0.192\n", " \n", " 9716_58882\n", "
\n", " +0.179\n", " \n", " 9716_58902\n", "
\n", " +0.174\n", " \n", " 9934_39425\n", "
\n", " +0.140\n", " \n", " 9701_16133\n", "
\n", " … 808 more positive …\n", "
\n", " … 49183 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.412\n", " \n", " 7716_48445\n", "
\n", " +0.278\n", " \n", " 7716_62858\n", "
\n", " +0.226\n", " \n", " 7716_2147\n", "
\n", " +0.206\n", " \n", " 7700_14753\n", "
\n", " +0.200\n", " \n", " 9700_32786\n", "
\n", " +0.189\n", " \n", " 7752_44414\n", "
\n", " +0.158\n", " \n", " 7716_38835\n", "
\n", " +0.157\n", " \n", " 7752_44413\n", "
\n", " +0.157\n", " \n", " 7716_48445 7716_62858\n", "
\n", " +0.148\n", " \n", " 7716_6026\n", "
\n", " … 169 more positive …\n", "
\n", " … 49822 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.597\n", " \n", " 9716_33109\n", "
\n", " +0.398\n", " \n", " 7784_36266\n", "
\n", " +0.320\n", " \n", " 9716_33109 9716_33109\n", "
\n", " +0.285\n", " \n", " 7784_36266 7784_36266\n", "
\n", " +0.228\n", " \n", " 9716_33109 9700_33819\n", "
\n", " +0.174\n", " \n", " 9757_9090\n", "
\n", " +0.173\n", " \n", " 9700_33819\n", "
\n", " +0.141\n", " \n", " 9716_33104\n", "
\n", " +0.123\n", " \n", " 9752_1938\n", "
\n", " +0.108\n", " \n", " 9716_33107\n", "
\n", " … 48 more positive …\n", "
\n", " … 49943 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.546\n", " \n", " 9083_40964\n", "
\n", " +0.420\n", " \n", " 9083_40961\n", "
\n", " +0.210\n", " \n", " 9083_40961 9083_40964\n", "
\n", " +0.199\n", " \n", " 9083_40964 9083_40961\n", "
\n", " +0.170\n", " \n", " 9716_19974\n", "
\n", " +0.168\n", " \n", " 9083_40964 9083_40964\n", "
\n", " +0.168\n", " \n", " 9083_40972\n", "
\n", " +0.156\n", " \n", " 9716_27424\n", "
\n", " +0.152\n", " \n", " 9716_27395\n", "
\n", " +0.126\n", " \n", " 9083_53505\n", "
\n", " … 371 more positive …\n", "
\n", " … 49620 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.489\n", " \n", " 9736_11782\n", "
\n", " +0.336\n", " \n", " 9716_48386\n", "
\n", " +0.303\n", " \n", " 9716_48406\n", "
\n", " +0.265\n", " \n", " 9935_63748\n", "
\n", " +0.166\n", " \n", " 9716_48389\n", "
\n", " +0.135\n", " \n", " 9716_18178\n", "
\n", " +0.133\n", " \n", " 9735_24324\n", "
\n", " +0.129\n", " \n", " 9716_48406 9716_48386\n", "
\n", " +0.129\n", " \n", " 9736_11782 9736_11782\n", "
\n", " +0.125\n", " \n", " 9735_24322\n", "
\n", " … 824 more positive …\n", "
\n", " … 49167 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.460\n", " \n", " 9734_64257\n", "
\n", " +0.402\n", " \n", " 9734_64268\n", "
\n", " +0.395\n", " \n", " 9734_64268 9734_64257\n", "
\n", " +0.362\n", " \n", " 9734_64257 9734_64268\n", "
\n", " +0.325\n", " \n", " 9734_64257 9734_64268 9734_64257\n", "
\n", " +0.302\n", " \n", " 9734_64268 9734_64257 9734_64268\n", "
\n", " +0.211\n", " \n", " 9734_64260\n", "
\n", " +0.111\n", " \n", " 7716_902\n", "
\n", " +0.079\n", " \n", " 9734_64257 9734_64260\n", "
\n", " +0.070\n", " \n", " 9734_64260 9734_64257\n", "
\n", " … 368 more positive …\n", "
\n", " … 49623 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.417\n", " \n", " 9732_39180\n", "
\n", " +0.374\n", " \n", " 9732_39172\n", "
\n", " +0.247\n", " \n", " 9732_39172 9732_39180\n", "
\n", " +0.242\n", " \n", " 9732_39180 7755_9519\n", "
\n", " +0.230\n", " \n", " 7755_35295 9732_39172\n", "
\n", " +0.220\n", " \n", " 9732_39169\n", "
\n", " +0.193\n", " \n", " 9739_47361\n", "
\n", " +0.179\n", " \n", " 7755_35295 9732_39172 9732_39180\n", "
\n", " +0.179\n", " \n", " 7755_9519 9732_39172\n", "
\n", " +0.159\n", " \n", " 7755_9519\n", "
\n", " … 53 more positive …\n", "
\n", " … 49938 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.358\n", " \n", " 9752_14479\n", "
\n", " +0.355\n", " \n", " 7716_35365\n", "
\n", " +0.239\n", " \n", " 7752_3257\n", "
\n", " +0.207\n", " \n", " 9752_14479 7752_3257\n", "
\n", " +0.181\n", " \n", " 7752_3257 9752_14479\n", "
\n", " +0.179\n", " \n", " 9752_1949\n", "
\n", " +0.172\n", " \n", " 9752_1948\n", "
\n", " +0.155\n", " \n", " 7716_35364\n", "
\n", " +0.149\n", " \n", " 7752_21240\n", "
\n", " +0.133\n", " \n", " 7716_35364 7716_35365\n", "
\n", " … 323 more positive …\n", "
\n", " … 49668 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.462\n", " \n", " 9752_8589\n", "
\n", " +0.354\n", " \n", " 9752_8586\n", "
\n", " +0.301\n", " \n", " 9702_30571\n", "
\n", " +0.251\n", " \n", " 9752_8586 9702_30571\n", "
\n", " +0.249\n", " \n", " 9752_8589 9702_30571\n", "
\n", " +0.228\n", " \n", " 9702_30571 9752_8586\n", "
\n", " +0.204\n", " \n", " 9702_30571 9752_8589\n", "
\n", " +0.199\n", " \n", " 9702_30576\n", "
\n", " +0.195\n", " \n", " 9702_30576 9752_8589\n", "
\n", " +0.177\n", " \n", " 9752_8589 9702_30576\n", "
\n", " … 217 more positive …\n", "
\n", " … 49774 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.528\n", " \n", " 9700_36237\n", "
\n", " +0.439\n", " \n", " 9700_36237 7700_8608\n", "
\n", " +0.403\n", " \n", " 7700_8608 9700_36237\n", "
\n", " +0.298\n", " \n", " 7700_8608\n", "
\n", " +0.292\n", " \n", " 9700_36237 7700_8608 9700_36237\n", "
\n", " +0.250\n", " \n", " 7700_8608 9700_36237 7700_8608\n", "
\n", " +0.139\n", " \n", " 9700_36237 9700_36237\n", "
\n", " +0.100\n", " \n", " 9700_36237 7700_1152\n", "
\n", " +0.099\n", " \n", " 7700_1152 9700_36237\n", "
\n", " +0.098\n", " \n", " 7700_8608 7700_8608\n", "
\n", " … 116 more positive …\n", "
\n", " … 49875 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.561\n", " \n", " 7725_30004\n", "
\n", " +0.328\n", " \n", " 9752_15544\n", "
\n", " +0.200\n", " \n", " 7752_46836\n", "
\n", " +0.172\n", " \n", " 7755_15811\n", "
\n", " +0.162\n", " \n", " 7725_30004 7755_15803\n", "
\n", " +0.143\n", " \n", " 7755_15832\n", "
\n", " +0.139\n", " \n", " 9702_30571\n", "
\n", " +0.138\n", " \n", " 7752_45684\n", "
\n", " +0.137\n", " \n", " 7755_15803\n", "
\n", " +0.137\n", " \n", " 7755_15832 7725_30004\n", "
\n", " … 531 more positive …\n", "
\n", " … 49460 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.588\n", " \n", " 7752_3917\n", "
\n", " +0.394\n", " \n", " 9752_19201\n", "
\n", " +0.331\n", " \n", " 9752_19205\n", "
\n", " +0.257\n", " \n", " 9752_19205 7752_3917\n", "
\n", " +0.246\n", " \n", " 7752_3917 9752_19201\n", "
\n", " +0.232\n", " \n", " 9752_19201 7752_3917\n", "
\n", " +0.207\n", " \n", " 7752_3917 9752_19205\n", "
\n", " +0.157\n", " \n", " 7752_3917 9752_19205 7752_3917\n", "
\n", " +0.153\n", " \n", " 7752_3918\n", "
\n", " +0.135\n", " \n", " 7752_3917 9752_19201 7752_3917\n", "
\n", " … 206 more positive …\n", "
\n", " … 49785 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.317\n", " \n", " 7755_30229\n", "
\n", " +0.276\n", " \n", " 7755_30228\n", "
\n", " +0.268\n", " \n", " 7755_30224\n", "
\n", " +0.256\n", " \n", " 9752_10376\n", "
\n", " +0.252\n", " \n", " 5061_550 7755_30228\n", "
\n", " +0.252\n", " \n", " 5061_1340 9752_10376\n", "
\n", " +0.245\n", " \n", " 5061_1340\n", "
\n", " +0.197\n", " \n", " 9752_2305 5061_550\n", "
\n", " +0.181\n", " \n", " 5061_550\n", "
\n", " +0.168\n", " \n", " 9752_10376 9752_2305 5061_550\n", "
\n", " … 72 more positive …\n", "
\n", " … 49919 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.435\n", " \n", " 9754_51232\n", "
\n", " +0.400\n", " \n", " 9754_51203\n", "
\n", " +0.369\n", " \n", " 9754_51232 9754_51203\n", "
\n", " +0.366\n", " \n", " 9754_51203 9754_51232\n", "
\n", " +0.319\n", " \n", " 9754_51203 9754_51232 9754_51203\n", "
\n", " +0.316\n", " \n", " 9754_51232 9754_51203 9754_51232\n", "
\n", " +0.159\n", " \n", " 9916_55809\n", "
\n", " +0.151\n", " \n", " 9739_10500\n", "
\n", " +0.104\n", " \n", " 7752_13272\n", "
\n", " +0.084\n", " \n", " 9754_51232 9754_51232\n", "
\n", " … 535 more positive …\n", "
\n", " … 49456 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.300\n", " \n", " 7716_3936\n", "
\n", " +0.298\n", " \n", " 7716_60041\n", "
\n", " +0.236\n", " \n", " 9900_55812\n", "
\n", " +0.214\n", " \n", " 9716_39389\n", "
\n", " +0.213\n", " \n", " 9716_39388\n", "
\n", " +0.201\n", " \n", " 9736_43778\n", "
\n", " +0.198\n", " \n", " 7700_801\n", "
\n", " +0.193\n", " \n", " 7745_46877\n", "
\n", " +0.181\n", " \n", " 9716_50689\n", "
\n", " +0.177\n", " \n", " 9716_6407\n", "
\n", " … 610 more positive …\n", "
\n", " … 49381 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.469\n", " \n", " 7755_31330\n", "
\n", " +0.288\n", " \n", " 7757_7013\n", "
\n", " +0.225\n", " \n", " 5061_590\n", "
\n", " +0.213\n", " \n", " 7755_31330 7755_31330\n", "
\n", " +0.193\n", " \n", " 5061_595\n", "
\n", " +0.160\n", " \n", " 5061_550\n", "
\n", " +0.133\n", " \n", " 7757_7041\n", "
\n", " +0.132\n", " \n", " 7755_37277\n", "
\n", " +0.131\n", " \n", " 9716_31062\n", "
\n", " +0.124\n", " \n", " 7755_31330 7716_3669\n", "
\n", " … 290 more positive …\n", "
\n", " … 49701 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.487\n", " \n", " 9734_14851\n", "
\n", " +0.475\n", " \n", " 9734_14880\n", "
\n", " +0.342\n", " \n", " 9734_14880 9734_14851\n", "
\n", " +0.327\n", " \n", " 9734_14851 9734_14880\n", "
\n", " +0.241\n", " \n", " 9734_14880 9734_14851 9734_14880\n", "
\n", " +0.228\n", " \n", " 9734_14851 9734_14880 9734_14851\n", "
\n", " +0.178\n", " \n", " 9935_14851\n", "
\n", " +0.170\n", " \n", " 9758_23300\n", "
\n", " +0.103\n", " \n", " 9734_14851 9734_14851\n", "
\n", " +0.100\n", " \n", " 9734_14880 9734_14880\n", "
\n", " … 449 more positive …\n", "
\n", " … 49542 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.423\n", " \n", " 9716_2049\n", "
\n", " +0.393\n", " \n", " 9716_2052\n", "
\n", " +0.355\n", " \n", " 9739_22530\n", "
\n", " +0.348\n", " \n", " 9716_2060\n", "
\n", " +0.167\n", " \n", " 9716_2060 9716_2049\n", "
\n", " +0.156\n", " \n", " 9716_2049 9716_2060\n", "
\n", " +0.151\n", " \n", " 9716_2052 9739_22530\n", "
\n", " +0.150\n", " \n", " 9716_2052 9716_2049\n", "
\n", " +0.140\n", " \n", " 9739_22530 9716_2052\n", "
\n", " +0.123\n", " \n", " 9716_2049 9716_2052\n", "
\n", " … 416 more positive …\n", "
\n", " … 49575 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.413\n", " \n", " 7716_3161\n", "
\n", " +0.364\n", " \n", " 7716_49282\n", "
\n", " +0.328\n", " \n", " 9716_3151\n", "
\n", " +0.300\n", " \n", " 9734_5382\n", "
\n", " +0.267\n", " \n", " 9935_32514\n", "
\n", " +0.198\n", " \n", " 9935_32534\n", "
\n", " +0.193\n", " \n", " 9716_31052\n", "
\n", " +0.172\n", " \n", " 9935_32514 9935_32534\n", "
\n", " +0.157\n", " \n", " 9935_32534 9935_32514\n", "
\n", " +0.121\n", " \n", " 9935_32517\n", "
\n", " … 588 more positive …\n", "
\n", " … 49403 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.591\n", " \n", " 7716_3669\n", "
\n", " +0.230\n", " \n", " 7752_26210\n", "
\n", " +0.221\n", " \n", " 7716_3669 7716_3669\n", "
\n", " +0.215\n", " \n", " 7755_307\n", "
\n", " +0.202\n", " \n", " 7755_44698\n", "
\n", " +0.175\n", " \n", " 7755_32044\n", "
\n", " +0.169\n", " \n", " 7755_2984\n", "
\n", " +0.167\n", " \n", " 7755_307 7716_3669\n", "
\n", " +0.147\n", " \n", " 7755_2987\n", "
\n", " +0.135\n", " \n", " 7716_3669 7755_307\n", "
\n", " … 316 more positive …\n", "
\n", " … 49675 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.430\n", " \n", " 9736_11782\n", "
\n", " +0.362\n", " \n", " 9935_63748\n", "
\n", " +0.310\n", " \n", " 9735_13088\n", "
\n", " +0.264\n", " \n", " 9735_13059\n", "
\n", " +0.245\n", " \n", " 9736_11782 9935_63748\n", "
\n", " +0.243\n", " \n", " 9935_63748 9736_11782\n", "
\n", " +0.210\n", " \n", " 9735_13088 9735_13059\n", "
\n", " +0.210\n", " \n", " 9735_13059 9735_13088\n", "
\n", " +0.157\n", " \n", " 9935_63748 9736_11782 9935_63748\n", "
\n", " +0.154\n", " \n", " 9735_13059 9735_13088 9735_13059\n", "
\n", " … 574 more positive …\n", "
\n", " … 49417 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.481\n", " \n", " 9915_7682\n", "
\n", " +0.324\n", " \n", " 9937_28172\n", "
\n", " +0.267\n", " \n", " 9937_28161\n", "
\n", " +0.197\n", " \n", " 9937_35585\n", "
\n", " +0.179\n", " \n", " 9790_45569\n", "
\n", " +0.179\n", " \n", " 5032_515\n", "
\n", " +0.150\n", " \n", " 9915_10754\n", "
\n", " +0.141\n", " \n", " 9915_10774\n", "
\n", " +0.141\n", " \n", " 9915_7681\n", "
\n", " +0.120\n", " \n", " 7743_21745\n", "
\n", " … 748 more positive …\n", "
\n", " … 49243 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.335\n", " \n", " 7700_55154\n", "
\n", " +0.328\n", " \n", " 9754_51222\n", "
\n", " +0.315\n", " \n", " 9754_51202\n", "
\n", " +0.213\n", " \n", " 9754_51202 9754_51222\n", "
\n", " +0.195\n", " \n", " 9754_18690\n", "
\n", " +0.188\n", " \n", " 9754_51222 9754_51202\n", "
\n", " +0.185\n", " \n", " 7700_5871\n", "
\n", " +0.175\n", " \n", " 9701_49154\n", "
\n", " +0.172\n", " \n", " 9946_21250\n", "
\n", " +0.155\n", " \n", " 9754_51222 9754_51202 9754_51222\n", "
\n", " … 886 more positive …\n", "
\n", " … 49105 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.385\n", " \n", " 7755_33348\n", "
\n", " +0.337\n", " \n", " 7755_35297\n", "
\n", " +0.280\n", " \n", " 9742_467\n", "
\n", " +0.199\n", " \n", " 9787_13993\n", "
\n", " +0.199\n", " \n", " 9743_1232\n", "
\n", " +0.191\n", " \n", " 7755_15802\n", "
\n", " +0.183\n", " \n", " 9742_21018\n", "
\n", " +0.169\n", " \n", " 7755_6805\n", "
\n", " +0.144\n", " \n", " 5061_770\n", "
\n", " +0.134\n", " \n", " 9716_3722\n", "
\n", " … 143 more positive …\n", "
\n", " … 49848 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.310\n", " \n", " 7746_6159\n", "
\n", " +0.293\n", " \n", " 7746_31256\n", "
\n", " +0.280\n", " \n", " 7752_515\n", "
\n", " +0.266\n", " \n", " 7746_33171\n", "
\n", " +0.251\n", " \n", " 7752_516\n", "
\n", " +0.220\n", " \n", " 9746_38504\n", "
\n", " +0.195\n", " \n", " 7716_9597\n", "
\n", " +0.162\n", " \n", " 7730_3433\n", "
\n", " +0.155\n", " \n", " 7746_6551\n", "
\n", " +0.146\n", " \n", " 7716_62603\n", "
\n", " … 251 more positive …\n", "
\n", " … 49740 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.466\n", " \n", " 9953_6547\n", "
\n", " +0.371\n", " \n", " 9953_6545\n", "
\n", " +0.272\n", " \n", " 5061_1788 5061_1788\n", "
\n", " +0.272\n", " \n", " 9953_6547 9953_6545\n", "
\n", " +0.232\n", " \n", " 5061_1788 5061_1788 5061_1788\n", "
\n", " +0.218\n", " \n", " 9752_40873\n", "
\n", " +0.207\n", " \n", " 9953_6547 9953_6547\n", "
\n", " +0.199\n", " \n", " 9953_6545 9953_6545\n", "
\n", " +0.182\n", " \n", " 5061_1788\n", "
\n", " +0.174\n", " \n", " 9752_10376 9752_40873\n", "
\n", " … 33 more positive …\n", "
\n", " … 49958 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.519\n", " \n", " 9716_31786\n", "
\n", " +0.204\n", " \n", " 9716_6427\n", "
\n", " +0.166\n", " \n", " 7730_3431\n", "
\n", " +0.158\n", " \n", " 9702_30571\n", "
\n", " +0.153\n", " \n", " 9716_44960\n", "
\n", " +0.149\n", " \n", " 9716_31786 7730_3431\n", "
\n", " +0.145\n", " \n", " 7730_3507 9716_6427 9716_6427\n", "
\n", " +0.143\n", " \n", " 9752_8588\n", "
\n", " +0.139\n", " \n", " 9716_31786 9716_31786\n", "
\n", " +0.133\n", " \n", " 9716_6427 9716_6427\n", "
\n", " … 147 more positive …\n", "
\n", " … 49844 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.447\n", " \n", " 9700_730\n", "
\n", " +0.339\n", " \n", " 9700_49395\n", "
\n", " +0.274\n", " \n", " 9752_30042\n", "
\n", " +0.271\n", " \n", " 9716_37507\n", "
\n", " +0.266\n", " \n", " 9754_3559\n", "
\n", " +0.218\n", " \n", " 9700_14259\n", "
\n", " +0.194\n", " \n", " 9754_26704\n", "
\n", " +0.176\n", " \n", " 9716_37507 7730_380\n", "
\n", " +0.159\n", " \n", " 9700_14256\n", "
\n", " +0.136\n", " \n", " 9700_730 9752_30042\n", "
\n", " … 106 more positive …\n", "
\n", " … 49885 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.444\n", " \n", " 7752_6313\n", "
\n", " +0.337\n", " \n", " 7752_6313 9752_14642\n", "
\n", " +0.309\n", " \n", " 9752_14642\n", "
\n", " +0.296\n", " \n", " 9752_14642 7752_6313\n", "
\n", " +0.283\n", " \n", " 7752_6313 7752_6313\n", "
\n", " +0.256\n", " \n", " 7752_6313 9752_14642 7752_6313\n", "
\n", " +0.216\n", " \n", " 7752_6313 7752_6313 9752_14642\n", "
\n", " +0.206\n", " \n", " 9752_14642 7752_6313 7752_6313\n", "
\n", " +0.200\n", " \n", " 9752_14642 7752_6313 9752_14642\n", "
\n", " +0.187\n", " \n", " 9752_14642 9752_14642\n", "
\n", " … 321 more positive …\n", "
\n", " … 49670 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.385\n", " \n", " 9935_27424\n", "
\n", " +0.341\n", " \n", " 9935_27395\n", "
\n", " +0.285\n", " \n", " 9935_41740\n", "
\n", " +0.217\n", " \n", " 9935_27395 9935_27424\n", "
\n", " +0.193\n", " \n", " 5002_17410\n", "
\n", " +0.191\n", " \n", " 9935_27424 9935_27395\n", "
\n", " +0.191\n", " \n", " 9935_41729\n", "
\n", " +0.165\n", " \n", " 9935_47875\n", "
\n", " +0.162\n", " \n", " 9900_24854\n", "
\n", " +0.156\n", " \n", " 9935_27395 9935_27424 9935_27395\n", "
\n", " … 570 more positive …\n", "
\n", " … 49421 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.480\n", " \n", " 9716_33838\n", "
\n", " +0.409\n", " \n", " 7716_6166\n", "
\n", " +0.250\n", " \n", " 7755_31331\n", "
\n", " +0.250\n", " \n", " 7755_48439\n", "
\n", " +0.234\n", " \n", " 9716_33838 7716_6166\n", "
\n", " +0.213\n", " \n", " 7716_6166 9716_33838\n", "
\n", " +0.195\n", " \n", " 9716_33838 9716_33838\n", "
\n", " +0.122\n", " \n", " 7716_6166 7716_6166\n", "
\n", " +0.114\n", " \n", " 7716_6166 9716_33838 9716_33838\n", "
\n", " +0.114\n", " \n", " 9716_33838 9716_33838 7716_6166\n", "
\n", " … 146 more positive …\n", "
\n", " … 49845 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.591\n", " \n", " 7755_33346\n", "
\n", " +0.215\n", " \n", " 7755_33346 7755_33346\n", "
\n", " +0.195\n", " \n", " 9716_3722\n", "
\n", " +0.186\n", " \n", " 9752_30046\n", "
\n", " +0.175\n", " \n", " 9700_32785\n", "
\n", " +0.164\n", " \n", " 7755_33346 9700_32785\n", "
\n", " +0.156\n", " \n", " 7755_14939\n", "
\n", " +0.154\n", " \n", " 9778_58579\n", "
\n", " +0.141\n", " \n", " 7784_30136\n", "
\n", " +0.123\n", " \n", " 7750_8494\n", "
\n", " … 190 more positive …\n", "
\n", " … 49801 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.619\n", " \n", " 7700_1611\n", "
\n", " +0.314\n", " \n", " 7700_1632\n", "
\n", " +0.297\n", " \n", " 7752_30043\n", "
\n", " +0.219\n", " \n", " 7700_1633\n", "
\n", " +0.207\n", " \n", " 7752_30043 7700_1611\n", "
\n", " +0.186\n", " \n", " 7716_2267\n", "
\n", " +0.181\n", " \n", " 7752_3100\n", "
\n", " +0.150\n", " \n", " 7700_1611 7752_30043\n", "
\n", " +0.126\n", " \n", " 9716_2279\n", "
\n", " +0.107\n", " \n", " 7700_1611 7700_1611\n", "
\n", " … 423 more positive …\n", "
\n", " … 49568 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.398\n", " \n", " 9937_48652\n", "
\n", " +0.368\n", " \n", " 9937_48641\n", "
\n", " +0.310\n", " \n", " 9937_48652 9937_48641\n", "
\n", " +0.310\n", " \n", " 9937_48641 9937_48652\n", "
\n", " +0.252\n", " \n", " 9937_48641 9937_48652 9937_48641\n", "
\n", " +0.236\n", " \n", " 9937_48652 9937_48641 9937_48652\n", "
\n", " +0.227\n", " \n", " 9937_26912\n", "
\n", " +0.196\n", " \n", " 9937_44576\n", "
\n", " +0.136\n", " \n", " 9937_44576 9937_26912\n", "
\n", " +0.124\n", " \n", " 9937_26912 9937_44576\n", "
\n", " … 643 more positive …\n", "
\n", " … 49348 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.499\n", " \n", " 9716_30220\n", "
\n", " +0.444\n", " \n", " 9716_30209\n", "
\n", " +0.276\n", " \n", " 9716_30209 9716_30220\n", "
\n", " +0.273\n", " \n", " 9716_30220 9716_30209\n", "
\n", " +0.187\n", " \n", " 9716_30209 9716_30220 9716_30209\n", "
\n", " +0.180\n", " \n", " 9716_30220 9716_30209 9716_30220\n", "
\n", " +0.149\n", " \n", " 9716_30230\n", "
\n", " +0.143\n", " \n", " 9916_25100\n", "
\n", " +0.137\n", " \n", " 9916_25100 9916_25089\n", "
\n", " +0.135\n", " \n", " 9916_25089 9916_25100\n", "
\n", " … 446 more positive …\n", "
\n", " … 49545 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.362\n", " \n", " 9953_37016\n", "
\n", " +0.250\n", " \n", " 9752_34079\n", "
\n", " +0.237\n", " \n", " 9716_34606 7730_3431 5061_910\n", "
\n", " +0.218\n", " \n", " 7730_3431 5061_910\n", "
\n", " +0.218\n", " \n", " 9716_34606\n", "
\n", " +0.211\n", " \n", " 7730_3431 5061_910 9752_10379\n", "
\n", " +0.188\n", " \n", " 5061_910 9752_10379\n", "
\n", " +0.184\n", " \n", " 9752_10379 9752_34079\n", "
\n", " +0.181\n", " \n", " 9716_34606 7730_3431\n", "
\n", " +0.181\n", " \n", " 5061_550 7730_3047\n", "
\n", " … 117 more positive …\n", "
\n", " … 49874 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.374\n", " \n", " 9745_10301\n", "
\n", " +0.371\n", " \n", " 9745_12668\n", "
\n", " +0.319\n", " \n", " 7745_12684\n", "
\n", " +0.312\n", " \n", " 7755_44696\n", "
\n", " +0.236\n", " \n", " 7745_59010\n", "
\n", " +0.236\n", " \n", " 7755_32044\n", "
\n", " +0.188\n", " \n", " 7745_8223\n", "
\n", " +0.182\n", " \n", " 7755_44696 7755_32044\n", "
\n", " +0.173\n", " \n", " 7745_12684 9745_12668\n", "
\n", " +0.171\n", " \n", " 9745_10301 7745_59010\n", "
\n", " … 226 more positive …\n", "
\n", " … 49765 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.299\n", " \n", " 9774_41987\n", "
\n", " +0.281\n", " \n", " 9790_33281\n", "
\n", " +0.267\n", " \n", " 9734_30466\n", "
\n", " +0.259\n", " \n", " 9774_10243\n", "
\n", " +0.193\n", " \n", " 7742_479\n", "
\n", " +0.180\n", " \n", " 5022_19796\n", "
\n", " +0.168\n", " \n", " 9774_10243 9774_41987\n", "
\n", " +0.161\n", " \n", " 9790_33281 9790_33281\n", "
\n", " +0.157\n", " \n", " 5022_19796 5022_19796\n", "
\n", " +0.148\n", " \n", " 9734_47105\n", "
\n", " … 353 more positive …\n", "
\n", " … 49638 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.665\n", " \n", " 9934_32513\n", "
\n", " +0.276\n", " \n", " 9934_12038\n", "
\n", " +0.252\n", " \n", " 9934_12037\n", "
\n", " +0.236\n", " \n", " 7752_36575\n", "
\n", " +0.198\n", " \n", " 9934_12054\n", "
\n", " +0.197\n", " \n", " 9934_12038 9934_32513\n", "
\n", " +0.187\n", " \n", " 9934_32513 9934_12038\n", "
\n", " +0.178\n", " \n", " 7752_5986\n", "
\n", " +0.123\n", " \n", " 9934_32513 9934_32513\n", "
\n", " +0.116\n", " \n", " 9934_12034\n", "
\n", " … 587 more positive …\n", "
\n", " … 49404 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.394\n", " \n", " 9716_7173\n", "
\n", " +0.253\n", " \n", " 9739_29956\n", "
\n", " +0.230\n", " \n", " 9789_48918\n", "
\n", " +0.180\n", " \n", " 9789_46595\n", "
\n", " +0.178\n", " \n", " 9716_13057\n", "
\n", " +0.170\n", " \n", " 9715_40452\n", "
\n", " +0.168\n", " \n", " 9916_55810\n", "
\n", " +0.167\n", " \n", " 9789_48898\n", "
\n", " +0.166\n", " \n", " 9716_15106\n", "
\n", " +0.165\n", " \n", " 9716_7173 9739_29956\n", "
\n", " … 543 more positive …\n", "
\n", " … 49448 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.352\n", " \n", " 9739_44293\n", "
\n", " +0.316\n", " \n", " 9701_47366\n", "
\n", " +0.313\n", " \n", " 9754_40452\n", "
\n", " +0.244\n", " \n", " 9701_47876\n", "
\n", " +0.221\n", " \n", " 9705_33028\n", "
\n", " +0.191\n", " \n", " 9739_44293 9739_44293\n", "
\n", " +0.182\n", " \n", " 9701_25861\n", "
\n", " +0.163\n", " \n", " 9934_30466\n", "
\n", " +0.148\n", " \n", " 9701_47366 9701_25861\n", "
\n", " +0.147\n", " \n", " 7755_38450\n", "
\n", " … 182 more positive …\n", "
\n", " … 49809 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.561\n", " \n", " 9937_48641\n", "
\n", " +0.389\n", " \n", " 9937_36865\n", "
\n", " +0.337\n", " \n", " 9937_29187\n", "
\n", " +0.216\n", " \n", " 9937_29188\n", "
\n", " +0.169\n", " \n", " 9716_39941\n", "
\n", " +0.168\n", " \n", " 9937_1538\n", "
\n", " +0.164\n", " \n", " 9937_48641 9937_36865\n", "
\n", " +0.153\n", " \n", " 9937_36865 9937_48641\n", "
\n", " +0.145\n", " \n", " 9937_48641 9937_48641\n", "
\n", " +0.127\n", " \n", " 9937_29187 9937_48641\n", "
\n", " … 326 more positive …\n", "
\n", " … 49665 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.486\n", " \n", " 7755_33266\n", "
\n", " +0.398\n", " \n", " 9716_6428\n", "
\n", " +0.306\n", " \n", " 7755_33266 9716_6428\n", "
\n", " +0.227\n", " \n", " 9716_6428 7755_33266\n", "
\n", " +0.198\n", " \n", " 9752_1375\n", "
\n", " +0.162\n", " \n", " 9716_6427 7755_33266\n", "
\n", " +0.152\n", " \n", " 7755_33266 9716_6428 7755_33266\n", "
\n", " +0.143\n", " \n", " 9716_6428 7730_3803\n", "
\n", " +0.142\n", " \n", " 9716_6428 7730_3803 5061_517\n", "
\n", " +0.141\n", " \n", " 7755_33269\n", "
\n", " … 98 more positive …\n", "
\n", " … 49893 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.425\n", " \n", " 7742_62681\n", "
\n", " +0.359\n", " \n", " 9914_29187\n", "
\n", " +0.242\n", " \n", " 7742_6020\n", "
\n", " +0.234\n", " \n", " 9734_64258\n", "
\n", " +0.209\n", " \n", " 9734_64278\n", "
\n", " +0.209\n", " \n", " 9790_60930\n", "
\n", " +0.195\n", " \n", " 9734_64261\n", "
\n", " +0.170\n", " \n", " 9734_64278 9734_64258\n", "
\n", " +0.156\n", " \n", " 9734_48396\n", "
\n", " +0.153\n", " \n", " 9734_64258 9734_64278\n", "
\n", " … 672 more positive …\n", "
\n", " … 49319 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.368\n", " \n", " 7716_12111\n", "
\n", " +0.280\n", " \n", " 7752_20141\n", "
\n", " +0.230\n", " \n", " 7716_7045\n", "
\n", " +0.206\n", " \n", " 7752_42111\n", "
\n", " +0.202\n", " \n", " 7716_28965\n", "
\n", " +0.188\n", " \n", " 7752_2087\n", "
\n", " +0.176\n", " \n", " 7752_6751\n", "
\n", " +0.166\n", " \n", " 9752_10374\n", "
\n", " +0.161\n", " \n", " 7716_7044\n", "
\n", " +0.154\n", " \n", " 5078_59092\n", "
\n", " … 321 more positive …\n", "
\n", " … 49670 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.295\n", " \n", " 9734_5633\n", "
\n", " +0.291\n", " \n", " 9734_5644\n", "
\n", " +0.281\n", " \n", " 9734_5633 9734_5644\n", "
\n", " +0.267\n", " \n", " 9734_5644 9734_5633\n", "
\n", " +0.254\n", " \n", " 9734_5633 9734_5644 9734_5633\n", "
\n", " +0.242\n", " \n", " 9734_5644 9734_5633 9734_5644\n", "
\n", " +0.227\n", " \n", " 9734_61702\n", "
\n", " +0.214\n", " \n", " 9916_65283\n", "
\n", " +0.210\n", " \n", " 9916_65312\n", "
\n", " +0.210\n", " \n", " 9916_65283 9916_65312\n", "
\n", " … 824 more positive …\n", "
\n", " … 49167 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.413\n", " \n", " 9935_55041\n", "
\n", " +0.411\n", " \n", " 9935_55052\n", "
\n", " +0.265\n", " \n", " 9739_56582\n", "
\n", " +0.264\n", " \n", " 9935_55052 9935_55041\n", "
\n", " +0.251\n", " \n", " 9739_56608\n", "
\n", " +0.243\n", " \n", " 9739_56579\n", "
\n", " +0.241\n", " \n", " 9935_55041 9935_55052\n", "
\n", " +0.189\n", " \n", " 9935_55041 9935_55052 9935_55041\n", "
\n", " +0.169\n", " \n", " 9935_55052 9935_55041 9935_55052\n", "
\n", " +0.151\n", " \n", " 9739_56579 9739_56608\n", "
\n", " … 650 more positive …\n", "
\n", " … 49341 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.497\n", " \n", " 9716_13059\n", "
\n", " +0.416\n", " \n", " 9716_25376\n", "
\n", " +0.296\n", " \n", " 9716_25376 9716_13059\n", "
\n", " +0.265\n", " \n", " 9716_13059 9716_25376\n", "
\n", " +0.195\n", " \n", " 9937_37635\n", "
\n", " +0.193\n", " \n", " 9716_13059 9716_13059\n", "
\n", " +0.187\n", " \n", " 9716_25347\n", "
\n", " +0.161\n", " \n", " 9716_25376 9716_25376\n", "
\n", " +0.153\n", " \n", " 7757_46774\n", "
\n", " +0.143\n", " \n", " 9716_25376 9716_13059 9716_25376\n", "
\n", " … 780 more positive …\n", "
\n", " … 49211 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.646\n", " \n", " 7716_62344\n", "
\n", " +0.333\n", " \n", " 9716_33391\n", "
\n", " +0.280\n", " \n", " 9716_30014\n", "
\n", " +0.213\n", " \n", " 7716_62344 7716_62344\n", "
\n", " +0.189\n", " \n", " 7716_33390\n", "
\n", " +0.179\n", " \n", " 7716_62344 9716_33391\n", "
\n", " +0.165\n", " \n", " 9716_33391 7716_62344\n", "
\n", " +0.165\n", " \n", " 9716_14854\n", "
\n", " +0.139\n", " \n", " 9734_8197\n", "
\n", " +0.138\n", " \n", " 7716_62344 9716_30014\n", "
\n", " … 434 more positive …\n", "
\n", " … 49557 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.431\n", " \n", " 9736_56096\n", "
\n", " +0.424\n", " \n", " 9736_56067\n", "
\n", " +0.361\n", " \n", " 9736_56067 9736_56096\n", "
\n", " +0.303\n", " \n", " 9736_56096 9736_56067\n", "
\n", " +0.211\n", " \n", " 9736_56096 9736_56067 9736_56096\n", "
\n", " +0.197\n", " \n", " 9736_56067 9736_56096 9736_56067\n", "
\n", " +0.146\n", " \n", " 9736_56067 9736_56067\n", "
\n", " +0.137\n", " \n", " 9716_62467 9716_62496\n", "
\n", " +0.136\n", " \n", " 9736_27137\n", "
\n", " +0.135\n", " \n", " 9736_56096 9736_56096\n", "
\n", " … 731 more positive …\n", "
\n", " … 49260 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.485\n", " \n", " 9935_48897\n", "
\n", " +0.470\n", " \n", " 9935_48908\n", "
\n", " +0.357\n", " \n", " 9935_48908 9935_48897\n", "
\n", " +0.315\n", " \n", " 9935_48897 9935_48908\n", "
\n", " +0.224\n", " \n", " 9935_48908 9935_48897 9935_48908\n", "
\n", " +0.219\n", " \n", " 9935_48897 9935_48908 9935_48897\n", "
\n", " +0.147\n", " \n", " 9739_10508\n", "
\n", " +0.144\n", " \n", " 9739_10500\n", "
\n", " +0.139\n", " \n", " 9935_48897 9935_48897\n", "
\n", " +0.105\n", " \n", " 9935_48908 9935_48908\n", "
\n", " … 807 more positive …\n", "
\n", " … 49184 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.431\n", " \n", " 7752_61571\n", "
\n", " +0.322\n", " \n", " 9735_7172\n", "
\n", " +0.235\n", " \n", " 9734_30468\n", "
\n", " +0.217\n", " \n", " 9734_30486\n", "
\n", " +0.198\n", " \n", " 7752_61571 9735_7172\n", "
\n", " +0.184\n", " \n", " 9735_7172 7752_61571\n", "
\n", " +0.182\n", " \n", " 9736_36374\n", "
\n", " +0.172\n", " \n", " 9734_47110\n", "
\n", " +0.157\n", " \n", " 9735_7169\n", "
\n", " +0.150\n", " \n", " 9734_30466\n", "
\n", " … 780 more positive …\n", "
\n", " … 49211 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.340\n", " \n", " 9734_33284\n", "
\n", " +0.291\n", " \n", " 9734_5378\n", "
\n", " +0.270\n", " \n", " 9735_7169\n", "
\n", " +0.245\n", " \n", " 9935_63748\n", "
\n", " +0.242\n", " \n", " 9734_5381\n", "
\n", " +0.227\n", " \n", " 7752_61575\n", "
\n", " +0.217\n", " \n", " 9716_10497\n", "
\n", " +0.176\n", " \n", " 9735_7172\n", "
\n", " +0.172\n", " \n", " 9734_5398\n", "
\n", " +0.168\n", " \n", " 9716_50689\n", "
\n", " … 709 more positive …\n", "
\n", " … 49282 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.439\n", " \n", " 9732_39200\n", "
\n", " +0.357\n", " \n", " 9732_39171\n", "
\n", " +0.343\n", " \n", " 9732_27139\n", "
\n", " +0.228\n", " \n", " 9732_27139 9732_39200\n", "
\n", " +0.219\n", " \n", " 9732_27168\n", "
\n", " +0.208\n", " \n", " 9732_39200 9732_27139\n", "
\n", " +0.189\n", " \n", " 9732_39171 9732_39200\n", "
\n", " +0.182\n", " \n", " 9732_39200 9732_39171\n", "
\n", " +0.178\n", " \n", " 9732_39200 9732_27168\n", "
\n", " +0.144\n", " \n", " 9732_39171 9732_39200 9732_39171\n", "
\n", " … 522 more positive …\n", "
\n", " … 49469 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.418\n", " \n", " 7716_31983\n", "
\n", " +0.411\n", " \n", " 7755_3818\n", "
\n", " +0.379\n", " \n", " 7716_36161\n", "
\n", " +0.361\n", " \n", " 7755_36118\n", "
\n", " +0.205\n", " \n", " 7755_3818 7716_31983\n", "
\n", " +0.180\n", " \n", " 7716_31983 7755_3818\n", "
\n", " +0.159\n", " \n", " 7755_36118 7716_36161\n", "
\n", " +0.159\n", " \n", " 7716_36161 7755_36118\n", "
\n", " +0.155\n", " \n", " 7755_36118 7716_31983\n", "
\n", " +0.153\n", " \n", " 7716_36161 7755_3818\n", "
\n", " … 285 more positive …\n", "
\n", " … 49706 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.543\n", " \n", " 9716_13827\n", "
\n", " +0.404\n", " \n", " 9716_43779\n", "
\n", " +0.279\n", " \n", " 7716_6166\n", "
\n", " +0.263\n", " \n", " 9716_43779 9716_13827\n", "
\n", " +0.230\n", " \n", " 9716_13827 9716_43779\n", "
\n", " +0.175\n", " \n", " 9716_64516\n", "
\n", " +0.165\n", " \n", " 9716_13827 9716_13827\n", "
\n", " +0.149\n", " \n", " 9716_64517\n", "
\n", " +0.132\n", " \n", " 9716_43779 9716_13827 9716_43779\n", "
\n", " +0.120\n", " \n", " 9716_43779 9716_43779\n", "
\n", " … 410 more positive …\n", "
\n", " … 49581 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.357\n", " \n", " 9752_14478\n", "
\n", " +0.272\n", " \n", " 9716_6427\n", "
\n", " +0.232\n", " \n", " 5061_1195 7730_2658\n", "
\n", " +0.227\n", " \n", " 5061_1195\n", "
\n", " +0.224\n", " \n", " 5061_1195 7730_2658 9716_6427\n", "
\n", " +0.221\n", " \n", " 7730_3803 5061_517\n", "
\n", " +0.217\n", " \n", " 7730_3803 5061_517 9752_14478\n", "
\n", " +0.216\n", " \n", " 7730_2658 9716_6427\n", "
\n", " +0.203\n", " \n", " 5061_517 9752_14478\n", "
\n", " +0.183\n", " \n", " 9752_14478 5061_1195\n", "
\n", " … 52 more positive …\n", "
\n", " … 49939 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.433\n", " \n", " 9937_46851\n", "
\n", " +0.365\n", " \n", " 9716_13058\n", "
\n", " +0.364\n", " \n", " 7757_1047\n", "
\n", " +0.324\n", " \n", " 7743_1045\n", "
\n", " +0.230\n", " \n", " 9937_28162\n", "
\n", " +0.162\n", " \n", " 9757_1045\n", "
\n", " +0.148\n", " \n", " 9937_46851 7757_1047\n", "
\n", " +0.144\n", " \n", " 9716_13058 9716_13058\n", "
\n", " +0.123\n", " \n", " 9937_46851 7743_1045\n", "
\n", " +0.110\n", " \n", " 9937_28162 9937_46851\n", "
\n", " … 605 more positive …\n", "
\n", " … 49386 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.412\n", " \n", " 9716_35306\n", "
\n", " +0.361\n", " \n", " 9716_33096\n", "
\n", " +0.253\n", " \n", " 5060_17339\n", "
\n", " +0.208\n", " \n", " 9752_10379\n", "
\n", " +0.193\n", " \n", " 9700_33819\n", "
\n", " +0.190\n", " \n", " 9752_10379 9700_1655\n", "
\n", " +0.190\n", " \n", " 9752_10379 9700_1655 9716_35306\n", "
\n", " +0.190\n", " \n", " 9716_33096 9716_33096\n", "
\n", " +0.179\n", " \n", " 9752_30046\n", "
\n", " +0.178\n", " \n", " 9716_35306 9716_33096\n", "
\n", " … 61 more positive …\n", "
\n", " … 49930 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.545\n", " \n", " 9916_59906\n", "
\n", " +0.257\n", " \n", " 9901_4354\n", "
\n", " +0.221\n", " \n", " 9916_59906 9916_33025\n", "
\n", " +0.216\n", " \n", " 9901_26881\n", "
\n", " +0.208\n", " \n", " 9916_33025 9916_59906\n", "
\n", " +0.182\n", " \n", " 9751_19713\n", "
\n", " +0.182\n", " \n", " 9916_59906 9916_59906\n", "
\n", " +0.162\n", " \n", " 9751_19716\n", "
\n", " +0.131\n", " \n", " 9916_33025\n", "
\n", " +0.130\n", " \n", " 9751_19713 9751_19716\n", "
\n", " … 797 more positive …\n", "
\n", " … 49194 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.615\n", " \n", " 9953_6546\n", "
\n", " +0.289\n", " \n", " 7746_6554\n", "
\n", " +0.269\n", " \n", " 7746_6555\n", "
\n", " +0.258\n", " \n", " 7746_6552\n", "
\n", " +0.213\n", " \n", " 9953_6547\n", "
\n", " +0.208\n", " \n", " 7746_6554 9953_6546\n", "
\n", " +0.195\n", " \n", " 9953_6546 7746_6552\n", "
\n", " +0.170\n", " \n", " 7746_6552 9953_6546\n", "
\n", " +0.162\n", " \n", " 9953_6546 7746_6555\n", "
\n", " +0.145\n", " \n", " 9953_6546 7746_6554\n", "
\n", " … 358 more positive …\n", "
\n", " … 49633 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.532\n", " \n", " 9716_19970\n", "
\n", " +0.451\n", " \n", " 9716_19990\n", "
\n", " +0.322\n", " \n", " 9716_19970 9716_19990\n", "
\n", " +0.320\n", " \n", " 9716_19990 9716_19970\n", "
\n", " +0.225\n", " \n", " 9716_19970 9716_19990 9716_19970\n", "
\n", " +0.222\n", " \n", " 9716_19973\n", "
\n", " +0.221\n", " \n", " 9716_19990 9716_19970 9716_19990\n", "
\n", " +0.146\n", " \n", " 9716_19970 9716_19970\n", "
\n", " +0.137\n", " \n", " 9716_19973 9716_19970\n", "
\n", " +0.132\n", " \n", " 9716_19970 9716_19973\n", "
\n", " … 303 more positive …\n", "
\n", " … 49688 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.554\n", " \n", " 7755_6981\n", "
\n", " +0.374\n", " \n", " 9700_1653\n", "
\n", " +0.310\n", " \n", " 7755_6980\n", "
\n", " +0.258\n", " \n", " 7755_6980 7755_6981\n", "
\n", " +0.203\n", " \n", " 7755_6981 7755_6980\n", "
\n", " +0.164\n", " \n", " 7755_6981 7755_6981\n", "
\n", " +0.157\n", " \n", " 5077_58279\n", "
\n", " +0.157\n", " \n", " 9700_1653 9700_1635\n", "
\n", " +0.143\n", " \n", " 9700_1635\n", "
\n", " +0.129\n", " \n", " 7755_6981 7755_6980 7755_6981\n", "
\n", " … 121 more positive …\n", "
\n", " … 49870 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.347\n", " \n", " 9916_1793\n", "
\n", " +0.345\n", " \n", " 9734_5637\n", "
\n", " +0.323\n", " \n", " 9916_1804\n", "
\n", " +0.316\n", " \n", " 9916_1793 9916_1804\n", "
\n", " +0.303\n", " \n", " 9916_1804 9916_1793\n", "
\n", " +0.280\n", " \n", " 9916_1793 9916_1804 9916_1793\n", "
\n", " +0.269\n", " \n", " 9916_1804 9916_1793 9916_1804\n", "
\n", " +0.226\n", " \n", " 9734_5634\n", "
\n", " +0.207\n", " \n", " 9734_5637 9734_5634\n", "
\n", " +0.199\n", " \n", " 9734_5634 9734_5637\n", "
\n", " … 426 more positive …\n", "
\n", " … 49565 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.378\n", " \n", " 7752_3235\n", "
\n", " +0.331\n", " \n", " 9752_2904\n", "
\n", " +0.330\n", " \n", " 7749_15177\n", "
\n", " +0.307\n", " \n", " 7752_3235 9752_2904\n", "
\n", " +0.289\n", " \n", " 9752_2904 7752_3235\n", "
\n", " +0.269\n", " \n", " 7729_31441\n", "
\n", " +0.191\n", " \n", " 7752_3235 9752_2904 7752_3235\n", "
\n", " +0.178\n", " \n", " 7749_15177 7729_31441\n", "
\n", " +0.176\n", " \n", " 7729_31441 7749_15177\n", "
\n", " +0.171\n", " \n", " 7752_3235 7752_3235\n", "
\n", " … 273 more positive …\n", "
\n", " … 49718 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.427\n", " \n", " 7757_3276\n", "
\n", " +0.425\n", " \n", " 9757_46770\n", "
\n", " +0.369\n", " \n", " 7757_1053\n", "
\n", " +0.239\n", " \n", " 9757_46770 7757_3276\n", "
\n", " +0.225\n", " \n", " 7757_3276 9757_46770\n", "
\n", " +0.193\n", " \n", " 7743_46770\n", "
\n", " +0.138\n", " \n", " 5061_595\n", "
\n", " +0.126\n", " \n", " 7757_1053 9757_46770\n", "
\n", " +0.126\n", " \n", " 7716_2219\n", "
\n", " +0.122\n", " \n", " 7746_6551\n", "
\n", " … 240 more positive …\n", "
\n", " … 49751 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.500\n", " \n", " 9934_12033\n", "
\n", " +0.396\n", " \n", " 7752_8145\n", "
\n", " +0.241\n", " \n", " 7752_5986\n", "
\n", " +0.207\n", " \n", " 9934_12044\n", "
\n", " +0.203\n", " \n", " 7752_8145 9934_12033\n", "
\n", " +0.190\n", " \n", " 9934_12033 7752_8145\n", "
\n", " +0.178\n", " \n", " 9716_14853\n", "
\n", " +0.167\n", " \n", " 9734_59905\n", "
\n", " +0.159\n", " \n", " 9934_12033 9934_12033\n", "
\n", " +0.121\n", " \n", " 9934_15872\n", "
\n", " … 804 more positive …\n", "
\n", " … 49187 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.505\n", " \n", " 9734_61702\n", "
\n", " +0.366\n", " \n", " 9734_16642\n", "
\n", " +0.320\n", " \n", " 9734_16642 9734_61702\n", "
\n", " +0.301\n", " \n", " 9734_61702 9734_16642\n", "
\n", " +0.169\n", " \n", " 9734_16642 9734_61702 9734_16642\n", "
\n", " +0.167\n", " \n", " 9734_61702 9734_61702\n", "
\n", " +0.165\n", " \n", " 9734_61699\n", "
\n", " +0.162\n", " \n", " 9934_61186\n", "
\n", " +0.158\n", " \n", " 9734_61702 9734_16642 9734_61702\n", "
\n", " +0.139\n", " \n", " 9734_61699 9734_61702\n", "
\n", " … 685 more positive …\n", "
\n", " … 49306 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.469\n", " \n", " 9916_41475\n", "
\n", " +0.461\n", " \n", " 9916_41504\n", "
\n", " +0.350\n", " \n", " 9916_41504 9916_41475\n", "
\n", " +0.344\n", " \n", " 9916_41475 9916_41504\n", "
\n", " +0.269\n", " \n", " 9916_41475 9916_41504 9916_41475\n", "
\n", " +0.258\n", " \n", " 9916_41504 9916_41475 9916_41504\n", "
\n", " +0.152\n", " \n", " 9732_39180\n", "
\n", " +0.137\n", " \n", " 9732_39169\n", "
\n", " +0.103\n", " \n", " 9916_41475 9916_41475\n", "
\n", " +0.103\n", " \n", " 9732_40196\n", "
\n", " … 661 more positive …\n", "
\n", " … 49330 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.506\n", " \n", " 9937_48641\n", "
\n", " +0.497\n", " \n", " 9937_48652\n", "
\n", " +0.298\n", " \n", " 9937_42242\n", "
\n", " +0.228\n", " \n", " 9937_42262\n", "
\n", " +0.224\n", " \n", " 9937_48652 9937_48641\n", "
\n", " +0.217\n", " \n", " 9937_48641 9937_48652\n", "
\n", " +0.146\n", " \n", " 9937_48641 9937_42242\n", "
\n", " +0.121\n", " \n", " 9937_48641 9937_48652 9937_48641\n", "
\n", " +0.119\n", " \n", " 9937_42262 9937_48652\n", "
\n", " +0.119\n", " \n", " 9937_42242 9937_48641\n", "
\n", " … 583 more positive …\n", "
\n", " … 49408 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.331\n", " \n", " 7772_101\n", "
\n", " +0.328\n", " \n", " 5061_1721\n", "
\n", " +0.316\n", " \n", " 7716_3251\n", "
\n", " +0.314\n", " \n", " 9734_33284\n", "
\n", " +0.217\n", " \n", " 7772_34134\n", "
\n", " +0.203\n", " \n", " 7772_101 5061_1721\n", "
\n", " +0.169\n", " \n", " 9705_26627\n", "
\n", " +0.161\n", " \n", " 7772_34134 5061_1721\n", "
\n", " +0.147\n", " \n", " 9734_47105\n", "
\n", " +0.138\n", " \n", " 9716_32507\n", "
\n", " … 225 more positive …\n", "
\n", " … 49766 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.416\n", " \n", " 7745_3090\n", "
\n", " +0.380\n", " \n", " 9752_13212\n", "
\n", " +0.273\n", " \n", " 7752_7816\n", "
\n", " +0.270\n", " \n", " 7745_3091\n", "
\n", " +0.255\n", " \n", " 9752_13217\n", "
\n", " +0.190\n", " \n", " 7752_3290\n", "
\n", " +0.159\n", " \n", " 7746_33183\n", "
\n", " +0.157\n", " \n", " 7752_61571\n", "
\n", " +0.155\n", " \n", " 7716_55676\n", "
\n", " +0.152\n", " \n", " 9745_3082\n", "
\n", " … 433 more positive …\n", "
\n", " … 49558 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.422\n", " \n", " 7716_65296\n", "
\n", " +0.399\n", " \n", " 7746_6509\n", "
\n", " +0.378\n", " \n", " 7716_65295\n", "
\n", " +0.372\n", " \n", " 7746_62518\n", "
\n", " +0.225\n", " \n", " 7746_6509 7716_65296\n", "
\n", " +0.216\n", " \n", " 7716_65296 7746_6509\n", "
\n", " +0.181\n", " \n", " 7716_65295 7746_62518\n", "
\n", " +0.177\n", " \n", " 7746_62518 7716_65295\n", "
\n", " +0.117\n", " \n", " 7746_6509 7716_65295\n", "
\n", " +0.104\n", " \n", " 7746_62518 7716_65296\n", "
\n", " … 313 more positive …\n", "
\n", " … 49678 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.506\n", " \n", " 9752_8585\n", "
\n", " +0.311\n", " \n", " 9709_3656\n", "
\n", " +0.284\n", " \n", " 9709_3657\n", "
\n", " +0.234\n", " \n", " 9702_30571\n", "
\n", " +0.214\n", " \n", " 9702_30576\n", "
\n", " +0.213\n", " \n", " 9752_8585 9702_30571\n", "
\n", " +0.183\n", " \n", " 9702_30571 9752_8585\n", "
\n", " +0.181\n", " \n", " 9752_46818\n", "
\n", " +0.165\n", " \n", " 9752_8585 9702_30576\n", "
\n", " +0.132\n", " \n", " 9709_3656 9752_8585\n", "
\n", " … 303 more positive …\n", "
\n", " … 49688 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.692\n", " \n", " 7757_2262\n", "
\n", " +0.350\n", " \n", " 9757_10810\n", "
\n", " +0.280\n", " \n", " 9937_38150\n", "
\n", " +0.214\n", " \n", " 7757_2262 9757_10810\n", "
\n", " +0.206\n", " \n", " 9757_10810 7757_2262\n", "
\n", " +0.191\n", " \n", " 7757_2262 7757_2262\n", "
\n", " +0.162\n", " \n", " 9937_38150 7757_2262\n", "
\n", " +0.162\n", " \n", " 7757_2262 9937_38150\n", "
\n", " +0.115\n", " \n", " 7757_2262 9757_10810 7757_2262\n", "
\n", " +0.112\n", " \n", " 9757_10810 7757_2262 9757_10810\n", "
\n", " … 648 more positive …\n", "
\n", " … 49343 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.292\n", " \n", " 9937_37644\n", "
\n", " +0.280\n", " \n", " 9734_9996\n", "
\n", " +0.272\n", " \n", " 9734_30465\n", "
\n", " +0.271\n", " \n", " 9937_37633\n", "
\n", " +0.253\n", " \n", " 9734_61702\n", "
\n", " +0.213\n", " \n", " 9734_16641\n", "
\n", " +0.210\n", " \n", " 9937_37633 9937_37644\n", "
\n", " +0.184\n", " \n", " 9734_9985\n", "
\n", " +0.182\n", " \n", " 9937_37644 9937_37633\n", "
\n", " +0.167\n", " \n", " 9734_61728\n", "
\n", " … 859 more positive …\n", "
\n", " … 49132 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.571\n", " \n", " 9916_21506\n", "
\n", " +0.471\n", " \n", " 9916_21526\n", "
\n", " +0.262\n", " \n", " 7752_3591\n", "
\n", " +0.197\n", " \n", " 9752_19471\n", "
\n", " +0.159\n", " \n", " 7752_19479\n", "
\n", " +0.156\n", " \n", " 7752_3591 9916_21506\n", "
\n", " +0.146\n", " \n", " 7752_3592\n", "
\n", " +0.134\n", " \n", " 9745_2096\n", "
\n", " +0.130\n", " \n", " 9916_21506 9916_21526\n", "
\n", " +0.129\n", " \n", " 9916_21536\n", "
\n", " … 553 more positive …\n", "
\n", " … 49438 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.444\n", " \n", " 9752_13217\n", "
\n", " +0.420\n", " \n", " 9745_11838\n", "
\n", " +0.320\n", " \n", " 9745_11838 9752_13217\n", "
\n", " +0.287\n", " \n", " 9745_11838 9752_13217 9745_11838\n", "
\n", " +0.268\n", " \n", " 9752_13217 9745_11838\n", "
\n", " +0.251\n", " \n", " 9752_13217 9745_11838 9752_13217\n", "
\n", " +0.215\n", " \n", " 9752_13217 9752_13217 9752_13217\n", "
\n", " +0.209\n", " \n", " 9752_13217 9752_13217\n", "
\n", " +0.197\n", " \n", " 9716_11890\n", "
\n", " +0.185\n", " \n", " 9745_11838 9752_13212\n", "
\n", " … 37 more positive …\n", "
\n", " … 49954 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.328\n", " \n", " 9916_62469\n", "
\n", " +0.325\n", " \n", " 9916_51458\n", "
\n", " +0.300\n", " \n", " 9916_25089\n", "
\n", " +0.254\n", " \n", " 9916_62486\n", "
\n", " +0.252\n", " \n", " 9916_62466\n", "
\n", " +0.232\n", " \n", " 9916_32770\n", "
\n", " +0.199\n", " \n", " 9720_12293\n", "
\n", " +0.170\n", " \n", " 9916_62466 9916_62486\n", "
\n", " +0.154\n", " \n", " 9916_62486 9916_62466\n", "
\n", " +0.124\n", " \n", " 9794_31489\n", "
\n", " … 555 more positive …\n", "
\n", " … 49436 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.516\n", " \n", " 9701_2818\n", "
\n", " +0.379\n", " \n", " 9752_30042\n", "
\n", " +0.255\n", " \n", " 9701_2818 9752_30042\n", "
\n", " +0.222\n", " \n", " 9701_2817\n", "
\n", " +0.213\n", " \n", " 9752_30042 9701_2818\n", "
\n", " +0.209\n", " \n", " 9739_24324\n", "
\n", " +0.191\n", " \n", " 7700_815\n", "
\n", " +0.179\n", " \n", " 9701_2817 9701_2818\n", "
\n", " +0.146\n", " \n", " 9700_33783\n", "
\n", " +0.132\n", " \n", " 9701_2818 9701_2817\n", "
\n", " … 603 more positive …\n", "
\n", " … 49388 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.381\n", " \n", " 9734_48386\n", "
\n", " +0.306\n", " \n", " 9734_48406\n", "
\n", " +0.271\n", " \n", " 7716_44974\n", "
\n", " +0.219\n", " \n", " 9734_3078\n", "
\n", " +0.211\n", " \n", " 9734_48406 9734_48386\n", "
\n", " +0.210\n", " \n", " 9934_45313\n", "
\n", " +0.206\n", " \n", " 9934_45313 9934_45324\n", "
\n", " +0.205\n", " \n", " 9934_45313 9934_45324 9934_45313\n", "
\n", " +0.204\n", " \n", " 9734_48386 9734_48406\n", "
\n", " +0.201\n", " \n", " 9734_48388\n", "
\n", " … 609 more positive …\n", "
\n", " … 49382 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.372\n", " \n", " 9916_20226\n", "
\n", " +0.347\n", " \n", " 9916_20246\n", "
\n", " +0.312\n", " \n", " 9758_34564\n", "
\n", " +0.295\n", " \n", " 9916_20226 9916_20246\n", "
\n", " +0.294\n", " \n", " 9916_20246 9916_20226\n", "
\n", " +0.246\n", " \n", " 9916_20246 9916_20226 9916_20246\n", "
\n", " +0.241\n", " \n", " 9916_20226 9916_20246 9916_20226\n", "
\n", " +0.239\n", " \n", " 9746_34226\n", "
\n", " +0.135\n", " \n", " 7746_14896\n", "
\n", " +0.111\n", " \n", " 9746_14880\n", "
\n", " … 854 more positive …\n", "
\n", " … 49137 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.414\n", " \n", " 9734_48406\n", "
\n", " +0.412\n", " \n", " 9734_48386\n", "
\n", " +0.362\n", " \n", " 9734_48386 9734_48406\n", "
\n", " +0.330\n", " \n", " 9734_48406 9734_48386\n", "
\n", " +0.283\n", " \n", " 9734_48406 9734_48386 9734_48406\n", "
\n", " +0.266\n", " \n", " 9734_48386 9734_48406 9734_48386\n", "
\n", " +0.158\n", " \n", " 9715_40452\n", "
\n", " +0.125\n", " \n", " 7752_7412\n", "
\n", " +0.112\n", " \n", " 9734_48388\n", "
\n", " +0.083\n", " \n", " 9734_48406 9734_48388\n", "
\n", " … 324 more positive …\n", "
\n", " … 49667 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.428\n", " \n", " 9746_14891\n", "
\n", " +0.207\n", " \n", " 9746_3610\n", "
\n", " +0.207\n", " \n", " 9754_10278 5061_498\n", "
\n", " +0.194\n", " \n", " 9716_33827\n", "
\n", " +0.181\n", " \n", " 5061_1720 5061_1721 9700_10918\n", "
\n", " +0.180\n", " \n", " 9746_14891 9746_14891\n", "
\n", " +0.176\n", " \n", " 5061_498\n", "
\n", " +0.172\n", " \n", " 5061_1720\n", "
\n", " +0.170\n", " \n", " 9746_14893\n", "
\n", " +0.162\n", " \n", " 5061_1721 9700_10918\n", "
\n", " … 92 more positive …\n", "
\n", " … 49899 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.481\n", " \n", " 7716_3944\n", "
\n", " +0.341\n", " \n", " 7755_15809\n", "
\n", " +0.329\n", " \n", " 7755_3817\n", "
\n", " +0.248\n", " \n", " 7755_55462\n", "
\n", " +0.202\n", " \n", " 7755_15809 7716_3944\n", "
\n", " +0.191\n", " \n", " 7716_3944 7755_15809\n", "
\n", " +0.191\n", " \n", " 7716_3944 7755_3817\n", "
\n", " +0.180\n", " \n", " 7716_3937\n", "
\n", " +0.152\n", " \n", " 7755_6988\n", "
\n", " +0.150\n", " \n", " 7745_59010\n", "
\n", " … 217 more positive …\n", "
\n", " … 49774 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.227\n", " \n", " 9700_14256 9754_26709\n", "
\n", " +0.223\n", " \n", " 9716_6408\n", "
\n", " +0.217\n", " \n", " 9700_14256\n", "
\n", " +0.213\n", " \n", " 9754_26709\n", "
\n", " +0.213\n", " \n", " 9700_49395 9700_14256\n", "
\n", " +0.202\n", " \n", " 9700_49395\n", "
\n", " +0.202\n", " \n", " 9700_14256 9754_26709 5061_498\n", "
\n", " +0.202\n", " \n", " 9700_49395 9700_14256 9754_26709\n", "
\n", " +0.202\n", " \n", " 9754_26709 5061_498\n", "
\n", " +0.195\n", " \n", " 9743_8542\n", "
\n", " … 101 more positive …\n", "
\n", " … 49890 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.565\n", " \n", " 7799_39909\n", "
\n", " +0.417\n", " \n", " 7757_65159\n", "
\n", " +0.267\n", " \n", " 7799_39960\n", "
\n", " +0.240\n", " \n", " 7757_65154\n", "
\n", " +0.185\n", " \n", " 7757_65159 7799_39909\n", "
\n", " +0.175\n", " \n", " 7799_39909 7757_65159\n", "
\n", " +0.147\n", " \n", " 5007_5119\n", "
\n", " +0.147\n", " \n", " 7797_63090\n", "
\n", " +0.134\n", " \n", " 7799_39909 7757_65154\n", "
\n", " +0.134\n", " \n", " 7757_65154 7799_39909\n", "
\n", " … 239 more positive …\n", "
\n", " … 49752 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.475\n", " \n", " 9701_47362\n", "
\n", " +0.337\n", " \n", " 9701_47382\n", "
\n", " +0.252\n", " \n", " 9701_47365\n", "
\n", " +0.249\n", " \n", " 9701_25859\n", "
\n", " +0.247\n", " \n", " 9701_25861\n", "
\n", " +0.238\n", " \n", " 7716_25270\n", "
\n", " +0.203\n", " \n", " 9701_25888\n", "
\n", " +0.154\n", " \n", " 9701_47382 9701_47362\n", "
\n", " +0.149\n", " \n", " 9716_62469\n", "
\n", " +0.144\n", " \n", " 9716_9219\n", "
\n", " … 537 more positive …\n", "
\n", " … 49454 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.492\n", " \n", " 9739_56582\n", "
\n", " +0.366\n", " \n", " 9934_56067\n", "
\n", " +0.246\n", " \n", " 9739_56608\n", "
\n", " +0.228\n", " \n", " 9934_56076\n", "
\n", " +0.204\n", " \n", " 9739_22529\n", "
\n", " +0.204\n", " \n", " 9739_56579\n", "
\n", " +0.189\n", " \n", " 9739_10502\n", "
\n", " +0.181\n", " \n", " 9934_11009\n", "
\n", " +0.173\n", " \n", " 9739_24837\n", "
\n", " +0.165\n", " \n", " 9934_56065\n", "
\n", " … 539 more positive …\n", "
\n", " … 49452 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.586\n", " \n", " 9716_26298\n", "
\n", " +0.339\n", " \n", " 9716_26298 7730_3431\n", "
\n", " +0.226\n", " \n", " 7730_3431\n", "
\n", " +0.212\n", " \n", " 9716_26298 9716_26298\n", "
\n", " +0.182\n", " \n", " 9716_26295\n", "
\n", " +0.179\n", " \n", " 9700_32786\n", "
\n", " +0.154\n", " \n", " 7755_2985\n", "
\n", " +0.141\n", " \n", " 9716_26298 9716_26298 7730_3431\n", "
\n", " +0.122\n", " \n", " 9700_32786 7755_2985\n", "
\n", " +0.121\n", " \n", " 9716_34606\n", "
\n", " … 192 more positive …\n", "
\n", " … 49799 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.540\n", " \n", " 7755_2456\n", "
\n", " +0.449\n", " \n", " 7755_35903\n", "
\n", " +0.358\n", " \n", " 7755_2456 7755_35903\n", "
\n", " +0.353\n", " \n", " 7755_35903 7755_2456\n", "
\n", " +0.259\n", " \n", " 7755_2456 7755_35903 7755_2456\n", "
\n", " +0.237\n", " \n", " 7755_35903 7755_2456 7755_35903\n", "
\n", " +0.142\n", " \n", " 7755_33288\n", "
\n", " +0.093\n", " \n", " 9757_12117\n", "
\n", " +0.088\n", " \n", " 9757_12058\n", "
\n", " +0.083\n", " \n", " 7755_2456 7755_2456\n", "
\n", " … 112 more positive …\n", "
\n", " … 49879 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.571\n", " \n", " 7752_37850\n", "
\n", " +0.358\n", " \n", " 9752_11191\n", "
\n", " +0.278\n", " \n", " 9752_19491\n", "
\n", " +0.258\n", " \n", " 7752_19490\n", "
\n", " +0.241\n", " \n", " 7752_37850 7752_37850\n", "
\n", " +0.196\n", " \n", " 7752_37850 9752_11191\n", "
\n", " +0.196\n", " \n", " 9752_10378\n", "
\n", " +0.174\n", " \n", " 9752_11191 7752_37850\n", "
\n", " +0.155\n", " \n", " 9752_19491 7752_37850\n", "
\n", " +0.151\n", " \n", " 7752_37850 9752_19491\n", "
\n", " … 227 more positive …\n", "
\n", " … 49764 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.332\n", " \n", " 9716_61955\n", "
\n", " +0.320\n", " \n", " 9716_61984\n", "
\n", " +0.290\n", " \n", " 9748_2\n", "
\n", " +0.254\n", " \n", " 9744_63235\n", "
\n", " +0.240\n", " \n", " 9716_61955 9716_61984\n", "
\n", " +0.217\n", " \n", " 9716_61984 9716_61955\n", "
\n", " +0.203\n", " \n", " 9716_61958\n", "
\n", " +0.163\n", " \n", " 9716_61984 9716_61955 9716_61984\n", "
\n", " +0.160\n", " \n", " 9716_16898\n", "
\n", " +0.156\n", " \n", " 9934_30467\n", "
\n", " … 798 more positive …\n", "
\n", " … 49193 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.527\n", " \n", " 9716_34609\n", "
\n", " +0.284\n", " \n", " 9752_864\n", "
\n", " +0.257\n", " \n", " 9716_33229\n", "
\n", " +0.203\n", " \n", " 9716_34609 9716_33229\n", "
\n", " +0.201\n", " \n", " 7730_3431\n", "
\n", " +0.196\n", " \n", " 9716_34609 9716_34609\n", "
\n", " +0.191\n", " \n", " 7755_38849\n", "
\n", " +0.185\n", " \n", " 9716_34609 7730_3431\n", "
\n", " +0.142\n", " \n", " 9716_34609 9716_34609 7730_3431\n", "
\n", " +0.142\n", " \n", " 9752_14633 9752_864\n", "
\n", " … 152 more positive …\n", "
\n", " … 49839 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.558\n", " \n", " 9934_6659\n", "
\n", " +0.336\n", " \n", " 9934_45313 9934_6659\n", "
\n", " +0.325\n", " \n", " 9934_6659 9934_45313\n", "
\n", " +0.324\n", " \n", " 9934_45313\n", "
\n", " +0.210\n", " \n", " 9934_6659 9934_6659\n", "
\n", " +0.169\n", " \n", " 9934_6659 9934_45324\n", "
\n", " +0.168\n", " \n", " 9934_45324\n", "
\n", " +0.164\n", " \n", " 9934_6659 9934_45313 9934_6659\n", "
\n", " +0.144\n", " \n", " 9934_45324 9934_6659\n", "
\n", " +0.133\n", " \n", " 9934_6659 9934_6659 9934_45313\n", "
\n", " … 605 more positive …\n", "
\n", " … 49386 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.614\n", " \n", " 9935_14850\n", "
\n", " +0.384\n", " \n", " 7752_19204\n", "
\n", " +0.285\n", " \n", " 9752_10504\n", "
\n", " +0.217\n", " \n", " 9935_14850 9935_14850\n", "
\n", " +0.208\n", " \n", " 9934_40963\n", "
\n", " +0.207\n", " \n", " 7752_19204 9935_14850\n", "
\n", " +0.201\n", " \n", " 9935_14850 7752_19204\n", "
\n", " +0.191\n", " \n", " 7752_3291\n", "
\n", " +0.133\n", " \n", " 9752_10504 9935_14850\n", "
\n", " +0.118\n", " \n", " 9935_14850 9752_10504\n", "
\n", " … 407 more positive …\n", "
\n", " … 49584 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.302\n", " \n", " 9709_3657\n", "
\n", " +0.272\n", " \n", " 9709_3655\n", "
\n", " +0.189\n", " \n", " 7755_30226\n", "
\n", " +0.183\n", " \n", " 9709_3657 9709_3655\n", "
\n", " +0.182\n", " \n", " 9700_43994\n", "
\n", " +0.177\n", " \n", " 7731_1545\n", "
\n", " +0.173\n", " \n", " 5061_966\n", "
\n", " +0.171\n", " \n", " 9752_1879\n", "
\n", " +0.169\n", " \n", " 9752_46818\n", "
\n", " +0.166\n", " \n", " 9754_40450\n", "
\n", " … 219 more positive …\n", "
\n", " … 49772 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.355\n", " \n", " 9716_13058\n", "
\n", " +0.320\n", " \n", " 7716_60325\n", "
\n", " +0.300\n", " \n", " 9716_25346\n", "
\n", " +0.210\n", " \n", " 9916_55810\n", "
\n", " +0.194\n", " \n", " 9716_25366\n", "
\n", " +0.191\n", " \n", " 9752_15946\n", "
\n", " +0.161\n", " \n", " 9716_25346 7716_60325\n", "
\n", " +0.158\n", " \n", " 7752_15942\n", "
\n", " +0.138\n", " \n", " 7716_60325 9716_13058\n", "
\n", " +0.134\n", " \n", " 9716_9217\n", "
\n", " … 693 more positive …\n", "
\n", " … 49298 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.286\n", " \n", " 7755_30226\n", "
\n", " +0.268\n", " \n", " 9709_3657\n", "
\n", " +0.227\n", " \n", " 9752_46818\n", "
\n", " +0.218\n", " \n", " 9752_8585\n", "
\n", " +0.216\n", " \n", " 5061_1340\n", "
\n", " +0.210\n", " \n", " 7752_1880\n", "
\n", " +0.200\n", " \n", " 7755_30228\n", "
\n", " +0.187\n", " \n", " 7755_30226 5061_1340\n", "
\n", " +0.167\n", " \n", " 5009_55924\n", "
\n", " +0.157\n", " \n", " 9709_3654\n", "
\n", " … 196 more positive …\n", "
\n", " … 49795 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.464\n", " \n", " 9716_32508\n", "
\n", " +0.273\n", " \n", " 9716_32508 7730_3431\n", "
\n", " +0.248\n", " \n", " 9716_32508 7730_3431 5061_910\n", "
\n", " +0.244\n", " \n", " 9716_32508 9716_32508\n", "
\n", " +0.233\n", " \n", " 9757_2490\n", "
\n", " +0.226\n", " \n", " 7730_3431 5061_910\n", "
\n", " +0.223\n", " \n", " 7730_3431 5061_910 9757_46770\n", "
\n", " +0.223\n", " \n", " 5061_910 9757_46770\n", "
\n", " +0.213\n", " \n", " 9757_1045\n", "
\n", " +0.198\n", " \n", " 9716_32508 9716_32508 7730_3431\n", "
\n", " … 49 more positive …\n", "
\n", " … 49942 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.333\n", " \n", " 7755_30226\n", "
\n", " +0.276\n", " \n", " 9752_1879\n", "
\n", " +0.217\n", " \n", " 7755_30228\n", "
\n", " +0.213\n", " \n", " 7755_30226 5061_1340\n", "
\n", " +0.204\n", " \n", " 5061_1427\n", "
\n", " +0.200\n", " \n", " 9752_46818\n", "
\n", " +0.196\n", " \n", " 7755_30228 7755_30226\n", "
\n", " +0.186\n", " \n", " 5061_1340\n", "
\n", " +0.166\n", " \n", " 7755_37877\n", "
\n", " +0.147\n", " \n", " 5061_1427 7755_30228\n", "
\n", " … 202 more positive …\n", "
\n", " … 49789 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.540\n", " \n", " 9007_54871\n", "
\n", " +0.508\n", " \n", " 9016_51473\n", "
\n", " +0.311\n", " \n", " 9007_54871 9016_51473\n", "
\n", " +0.311\n", " \n", " 9016_51473 9007_54871\n", "
\n", " +0.209\n", " \n", " 9016_51473 9007_54871 9016_51473\n", "
\n", " +0.203\n", " \n", " 9007_54871 9016_51473 9007_54871\n", "
\n", " +0.198\n", " \n", " 9016_51478\n", "
\n", " +0.112\n", " \n", " 9007_54871 9016_51478\n", "
\n", " +0.109\n", " \n", " 9016_51478 9007_54871\n", "
\n", " +0.091\n", " \n", " 9701_24835\n", "
\n", " … 469 more positive …\n", "
\n", " … 49522 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.372\n", " \n", " 9746_16333\n", "
\n", " +0.341\n", " \n", " 9701_21475\n", "
\n", " +0.266\n", " \n", " 9701_21475 9701_21475\n", "
\n", " +0.228\n", " \n", " 9701_21475 9701_21475 9701_21475\n", "
\n", " +0.204\n", " \n", " 9716_34609\n", "
\n", " +0.183\n", " \n", " 9746_16334\n", "
\n", " +0.173\n", " \n", " 9953_6545\n", "
\n", " +0.159\n", " \n", " 5061_3615\n", "
\n", " +0.152\n", " \n", " 9746_16330\n", "
\n", " +0.135\n", " \n", " 9953_39154\n", "
\n", " … 159 more positive …\n", "
\n", " … 49832 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.379\n", " \n", " 9916_41475\n", "
\n", " +0.289\n", " \n", " 9916_41504\n", "
\n", " +0.286\n", " \n", " 9734_14870\n", "
\n", " +0.255\n", " \n", " 9916_33025\n", "
\n", " +0.237\n", " \n", " 9934_36609\n", "
\n", " +0.204\n", " \n", " 9916_33036\n", "
\n", " +0.198\n", " \n", " 9734_14850\n", "
\n", " +0.197\n", " \n", " 9734_14850 9734_14870\n", "
\n", " +0.181\n", " \n", " 7752_14263\n", "
\n", " +0.172\n", " \n", " 9734_14870 9734_14850\n", "
\n", " … 718 more positive …\n", "
\n", " … 49273 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.540\n", " \n", " 9716_34606\n", "
\n", " +0.274\n", " \n", " 7716_60325\n", "
\n", " +0.228\n", " \n", " 9916_25110\n", "
\n", " +0.214\n", " \n", " 9716_34606 9716_34606\n", "
\n", " +0.199\n", " \n", " 7752_8746\n", "
\n", " +0.196\n", " \n", " 9716_34606 7716_60325\n", "
\n", " +0.195\n", " \n", " 7716_3578\n", "
\n", " +0.189\n", " \n", " 7716_60325 9716_34606\n", "
\n", " +0.170\n", " \n", " 9916_25090\n", "
\n", " +0.168\n", " \n", " 9716_9217\n", "
\n", " … 523 more positive …\n", "
\n", " … 49468 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.440\n", " \n", " 9935_53516\n", "
\n", " +0.391\n", " \n", " 9935_53505\n", "
\n", " +0.272\n", " \n", " 9935_53505 9935_53516\n", "
\n", " +0.270\n", " \n", " 9739_24844 9739_24833\n", "
\n", " +0.264\n", " \n", " 9739_24844\n", "
\n", " +0.257\n", " \n", " 9739_24833\n", "
\n", " +0.248\n", " \n", " 9739_24833 9739_24844\n", "
\n", " +0.248\n", " \n", " 9935_53516 9935_53505\n", "
\n", " +0.212\n", " \n", " 9739_24844 9739_24833 9739_24844\n", "
\n", " +0.207\n", " \n", " 9739_24833 9739_24844 9739_24833\n", "
\n", " … 509 more positive …\n", "
\n", " … 49482 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.331\n", " \n", " 7755_6984\n", "
\n", " +0.314\n", " \n", " 9902_60674\n", "
\n", " +0.244\n", " \n", " 9739_10497\n", "
\n", " +0.232\n", " \n", " 9739_10500\n", "
\n", " +0.183\n", " \n", " 9902_40214\n", "
\n", " +0.165\n", " \n", " 9902_40194\n", "
\n", " +0.149\n", " \n", " 5061_550\n", "
\n", " +0.146\n", " \n", " 7767_17635\n", "
\n", " +0.146\n", " \n", " 5061_55\n", "
\n", " +0.142\n", " \n", " 7755_6936\n", "
\n", " … 366 more positive …\n", "
\n", " … 49625 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.462\n", " \n", " 7700_55154\n", "
\n", " +0.381\n", " \n", " 7700_5871\n", "
\n", " +0.263\n", " \n", " 9716_62468\n", "
\n", " +0.233\n", " \n", " 9705_46338\n", "
\n", " +0.176\n", " \n", " 9701_49157\n", "
\n", " +0.174\n", " \n", " 9716_62476\n", "
\n", " +0.173\n", " \n", " 9701_42245\n", "
\n", " +0.155\n", " \n", " 9716_28684\n", "
\n", " +0.151\n", " \n", " 9701_42242\n", "
\n", " +0.142\n", " \n", " 9705_262\n", "
\n", " … 574 more positive …\n", "
\n", " … 49417 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.430\n", " \n", " 9734_48388\n", "
\n", " +0.318\n", " \n", " 9734_48387 9734_48388\n", "
\n", " +0.301\n", " \n", " 9734_48387\n", "
\n", " +0.286\n", " \n", " 9734_48388 9734_48387\n", "
\n", " +0.277\n", " \n", " 9934_24834\n", "
\n", " +0.216\n", " \n", " 9934_24854\n", "
\n", " +0.196\n", " \n", " 9734_48388 9734_48387 9734_48388\n", "
\n", " +0.193\n", " \n", " 9934_45313\n", "
\n", " +0.178\n", " \n", " 7752_12914\n", "
\n", " +0.158\n", " \n", " 9734_48388 9734_48388\n", "
\n", " … 625 more positive …\n", "
\n", " … 49366 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.471\n", " \n", " 9916_19458\n", "
\n", " +0.452\n", " \n", " 9752_14043\n", "
\n", " +0.265\n", " \n", " 7752_21101\n", "
\n", " +0.210\n", " \n", " 7752_23980\n", "
\n", " +0.190\n", " \n", " 9752_14043 9916_19458\n", "
\n", " +0.185\n", " \n", " 9916_19458 9752_14043\n", "
\n", " +0.181\n", " \n", " 9734_33286\n", "
\n", " +0.180\n", " \n", " 7716_3253\n", "
\n", " +0.151\n", " \n", " 9752_14043 7752_21101\n", "
\n", " +0.134\n", " \n", " 7752_21101 9752_14043\n", "
\n", " … 388 more positive …\n", "
\n", " … 49603 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.435\n", " \n", " 7752_21240\n", "
\n", " +0.421\n", " \n", " 7752_21240 7752_21240\n", "
\n", " +0.360\n", " \n", " 7752_21240 7752_21240 7752_21240\n", "
\n", " +0.264\n", " \n", " 7755_31332\n", "
\n", " +0.225\n", " \n", " 7752_1959\n", "
\n", " +0.173\n", " \n", " 7716_3668\n", "
\n", " +0.170\n", " \n", " 9752_15548\n", "
\n", " +0.169\n", " \n", " 7755_31332 7716_3669 7755_31332\n", "
\n", " +0.161\n", " \n", " 7702_15765\n", "
\n", " +0.155\n", " \n", " 7716_3669 7755_31332\n", "
\n", " … 58 more positive …\n", "
\n", " … 49933 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.435\n", " \n", " 9716_25346\n", "
\n", " +0.364\n", " \n", " 7716_25849\n", "
\n", " +0.296\n", " \n", " 9716_13058\n", "
\n", " +0.271\n", " \n", " 9716_25366\n", "
\n", " +0.205\n", " \n", " 9916_16130\n", "
\n", " +0.178\n", " \n", " 9916_16150\n", "
\n", " +0.175\n", " \n", " 9716_28135\n", "
\n", " +0.169\n", " \n", " 7716_25983\n", "
\n", " +0.137\n", " \n", " 9716_25346 7716_25849\n", "
\n", " +0.136\n", " \n", " 9716_25346 9716_25346\n", "
\n", " … 716 more positive …\n", "
\n", " … 49275 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.459\n", " \n", " 7752_892\n", "
\n", " +0.405\n", " \n", " 9916_16130\n", "
\n", " +0.313\n", " \n", " 9916_16150\n", "
\n", " +0.269\n", " \n", " 9916_16132\n", "
\n", " +0.202\n", " \n", " 7716_60049\n", "
\n", " +0.160\n", " \n", " 9734_5637\n", "
\n", " +0.138\n", " \n", " 9734_5634\n", "
\n", " +0.135\n", " \n", " 9916_16130 7752_892\n", "
\n", " +0.133\n", " \n", " 9916_16130 9916_16150\n", "
\n", " +0.133\n", " \n", " 9916_16150 9916_16130\n", "
\n", " … 632 more positive …\n", "
\n", " … 49359 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.433\n", " \n", " 7716_31050\n", "
\n", " +0.406\n", " \n", " 9702_30733\n", "
\n", " +0.285\n", " \n", " 7702_6616\n", "
\n", " +0.270\n", " \n", " 7702_65328\n", "
\n", " +0.203\n", " \n", " 7702_374\n", "
\n", " +0.188\n", " \n", " 9708_32621\n", "
\n", " +0.142\n", " \n", " 7716_59660\n", "
\n", " +0.141\n", " \n", " 9716_31052\n", "
\n", " +0.130\n", " \n", " 9702_30733 7702_6616\n", "
\n", " +0.130\n", " \n", " 7702_6616 9702_30733\n", "
\n", " … 415 more positive …\n", "
\n", " … 49576 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.365\n", " \n", " 9935_63750\n", "
\n", " +0.331\n", " \n", " 9937_59906\n", "
\n", " +0.316\n", " \n", " 9739_5377\n", "
\n", " +0.296\n", " \n", " 9739_5388\n", "
\n", " +0.282\n", " \n", " 7752_61571\n", "
\n", " +0.205\n", " \n", " 9739_5398\n", "
\n", " +0.202\n", " \n", " 9739_24325\n", "
\n", " +0.178\n", " \n", " 9739_5378\n", "
\n", " +0.161\n", " \n", " 9739_5377 9739_5388\n", "
\n", " +0.155\n", " \n", " 9739_5388 9739_5377\n", "
\n", " … 490 more positive …\n", "
\n", " … 49501 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.407\n", " \n", " 9937_48652\n", "
\n", " +0.353\n", " \n", " 9937_48641\n", "
\n", " +0.313\n", " \n", " 9937_48641 9937_48652\n", "
\n", " +0.301\n", " \n", " 9937_48652 9937_48641\n", "
\n", " +0.225\n", " \n", " 9937_48652 9937_48641 9937_48652\n", "
\n", " +0.225\n", " \n", " 9937_48641 9937_48652 9937_48641\n", "
\n", " +0.200\n", " \n", " 9742_20492\n", "
\n", " +0.173\n", " \n", " 9742_20481\n", "
\n", " +0.153\n", " \n", " 9903_37377\n", "
\n", " +0.137\n", " \n", " 9902_42242\n", "
\n", " … 731 more positive …\n", "
\n", " … 49260 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.394\n", " \n", " 9916_26390\n", "
\n", " +0.366\n", " \n", " 9916_26370\n", "
\n", " +0.264\n", " \n", " 9916_26370 9916_26390\n", "
\n", " +0.240\n", " \n", " 9916_26390 9916_26370\n", "
\n", " +0.195\n", " \n", " 9736_8449\n", "
\n", " +0.192\n", " \n", " 9916_26390 9916_26370 9916_26390\n", "
\n", " +0.176\n", " \n", " 9720_63748\n", "
\n", " +0.160\n", " \n", " 9720_63745\n", "
\n", " +0.145\n", " \n", " 9720_63756\n", "
\n", " +0.144\n", " \n", " 9736_8460\n", "
\n", " … 933 more positive …\n", "
\n", " … 49058 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.587\n", " \n", " 9716_33106\n", "
\n", " +0.333\n", " \n", " 7716_1831\n", "
\n", " +0.258\n", " \n", " 7716_1831 9716_33106\n", "
\n", " +0.256\n", " \n", " 9716_33106 7716_1831\n", "
\n", " +0.185\n", " \n", " 7716_1843\n", "
\n", " +0.184\n", " \n", " 9716_33106 9716_33106\n", "
\n", " +0.166\n", " \n", " 7716_3976\n", "
\n", " +0.158\n", " \n", " 9716_33106 7716_1831 9716_33106\n", "
\n", " +0.148\n", " \n", " 9716_33106 7716_3976\n", "
\n", " +0.129\n", " \n", " 9716_1832\n", "
\n", " … 241 more positive …\n", "
\n", " … 49750 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.591\n", " \n", " 9716_62011\n", "
\n", " +0.290\n", " \n", " 7716_55795\n", "
\n", " +0.287\n", " \n", " 7716_55654\n", "
\n", " +0.271\n", " \n", " 7716_55654 9716_62011\n", "
\n", " +0.252\n", " \n", " 9716_62011 7716_55654\n", "
\n", " +0.241\n", " \n", " 7716_55795 9716_62011\n", "
\n", " +0.223\n", " \n", " 9716_62011 7716_55795\n", "
\n", " +0.183\n", " \n", " 9716_62011 7716_55654 9716_62011\n", "
\n", " +0.178\n", " \n", " 9716_62011 9716_62011\n", "
\n", " +0.157\n", " \n", " 7716_55654 9716_62011 7716_55654\n", "
\n", " … 203 more positive …\n", "
\n", " … 49788 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.535\n", " \n", " 9716_31787\n", "
\n", " +0.354\n", " \n", " 9716_31787 9746_16333\n", "
\n", " +0.351\n", " \n", " 9746_16333 9716_31787\n", "
\n", " +0.339\n", " \n", " 9746_16333\n", "
\n", " +0.306\n", " \n", " 9716_31787 9746_16333 9716_31787\n", "
\n", " +0.224\n", " \n", " 9746_16333 9716_31787 9746_16333\n", "
\n", " +0.203\n", " \n", " 9746_16330 9716_31787\n", "
\n", " +0.180\n", " \n", " 9746_16330\n", "
\n", " +0.157\n", " \n", " 9716_31787 9746_16330\n", "
\n", " +0.145\n", " \n", " 9716_31787 9746_16330 9716_31787\n", "
\n", " … 161 more positive …\n", "
\n", " … 49830 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.321\n", " \n", " 9734_12812 9734_12801\n", "
\n", " +0.304\n", " \n", " 9734_12812\n", "
\n", " +0.301\n", " \n", " 9734_12801 9734_12812\n", "
\n", " +0.293\n", " \n", " 9734_12801\n", "
\n", " +0.277\n", " \n", " 9734_12801 9734_12812 9734_12801\n", "
\n", " +0.268\n", " \n", " 9734_12812 9734_12801 9734_12812\n", "
\n", " +0.243\n", " \n", " 9937_40193\n", "
\n", " +0.235\n", " \n", " 9937_19724\n", "
\n", " +0.227\n", " \n", " 9937_28161\n", "
\n", " +0.197\n", " \n", " 9937_19716\n", "
\n", " … 431 more positive …\n", "
\n", " … 49560 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.439\n", " \n", " 9705_46337\n", "
\n", " +0.205\n", " \n", " 9701_23298\n", "
\n", " +0.201\n", " \n", " 9734_5637\n", "
\n", " +0.187\n", " \n", " 9908_45078\n", "
\n", " +0.171\n", " \n", " 9701_23299\n", "
\n", " +0.164\n", " \n", " 9734_10006\n", "
\n", " +0.157\n", " \n", " 9908_45058\n", "
\n", " +0.154\n", " \n", " 9908_45078 9908_45058\n", "
\n", " +0.153\n", " \n", " 9734_9986\n", "
\n", " +0.152\n", " \n", " 9903_49153\n", "
\n", " … 777 more positive …\n", "
\n", " … 49214 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.536\n", " \n", " 7741_5926\n", "
\n", " +0.409\n", " \n", " 9741_48901\n", "
\n", " +0.275\n", " \n", " 9900_6659\n", "
\n", " +0.266\n", " \n", " 9900_10753\n", "
\n", " +0.182\n", " \n", " 9741_48901 7741_5926\n", "
\n", " +0.180\n", " \n", " 7741_5926 9741_48901\n", "
\n", " +0.179\n", " \n", " 9014_60422\n", "
\n", " +0.158\n", " \n", " 7741_5926 7741_5926\n", "
\n", " +0.141\n", " \n", " 9900_6668\n", "
\n", " +0.137\n", " \n", " 5028_4824\n", "
\n", " … 506 more positive …\n", "
\n", " … 49485 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.489\n", " \n", " 9709_3657\n", "
\n", " +0.329\n", " \n", " 9752_8585\n", "
\n", " +0.320\n", " \n", " 9752_46818\n", "
\n", " +0.266\n", " \n", " 9709_3656\n", "
\n", " +0.227\n", " \n", " 9709_3657 9752_46818\n", "
\n", " +0.227\n", " \n", " 9752_46818 9709_3657\n", "
\n", " +0.191\n", " \n", " 9709_3657 9752_8585\n", "
\n", " +0.153\n", " \n", " 9709_3657 9752_46818 9709_3657\n", "
\n", " +0.139\n", " \n", " 9752_46818 9709_3657 9752_46818\n", "
\n", " +0.127\n", " \n", " 9752_8585 9709_3657\n", "
\n", " … 251 more positive …\n", "
\n", " … 49740 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.629\n", " \n", " 7755_30226\n", "
\n", " +0.495\n", " \n", " 7755_30226 7755_30226\n", "
\n", " +0.388\n", " \n", " 7755_30226 7755_30226 7755_30226\n", "
\n", " +0.208\n", " \n", " 7755_30229 7755_30226 7755_30226\n", "
\n", " +0.191\n", " \n", " 7755_30229 7755_30226\n", "
\n", " +0.182\n", " \n", " 7755_30229\n", "
\n", " +0.182\n", " \n", " 7755_30226 7755_30226 7755_30229\n", "
\n", " +0.161\n", " \n", " 7755_30226 7755_30229\n", "
\n", " +0.130\n", " \n", " 7755_30226 7755_30229 7755_30226\n", "
\n", " +0.042\n", " \n", " 7755_30229 7755_30229 7755_30226\n", "
\n", " … 1 more positive …\n", "
\n", " … 49990 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.449\n", " \n", " 7716_6166\n", "
\n", " +0.413\n", " \n", " 9716_33838\n", "
\n", " +0.315\n", " \n", " 9716_33838 7716_6166\n", "
\n", " +0.312\n", " \n", " 7716_6166 9716_33838\n", "
\n", " +0.184\n", " \n", " 9716_33838 7716_6166 9716_33838\n", "
\n", " +0.167\n", " \n", " 7716_6166 7716_6166\n", "
\n", " +0.166\n", " \n", " 7716_6166 9716_33838 7716_6166\n", "
\n", " +0.140\n", " \n", " 7755_48439\n", "
\n", " +0.138\n", " \n", " 9716_33838 7716_6166 7716_6166\n", "
\n", " +0.133\n", " \n", " 7716_6166 7716_6166 9716_33838\n", "
\n", " … 331 more positive …\n", "
\n", " … 49660 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.343\n", " \n", " 9934_39427\n", "
\n", " +0.325\n", " \n", " 9716_33107\n", "
\n", " +0.243\n", " \n", " 7752_517\n", "
\n", " +0.195\n", " \n", " 9934_39427 7752_517\n", "
\n", " +0.181\n", " \n", " 9785_17932\n", "
\n", " +0.180\n", " \n", " 9934_45313\n", "
\n", " +0.165\n", " \n", " 9785_17921\n", "
\n", " +0.163\n", " \n", " 9934_29472\n", "
\n", " +0.152\n", " \n", " 9934_51714\n", "
\n", " +0.148\n", " \n", " 9716_33102 9716_33107\n", "
\n", " … 859 more positive …\n", "
\n", " … 49132 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.428\n", " \n", " 7752_766\n", "
\n", " +0.415\n", " \n", " 9752_15544\n", "
\n", " +0.292\n", " \n", " 7757_2990\n", "
\n", " +0.275\n", " \n", " 7752_985\n", "
\n", " +0.266\n", " \n", " 9752_11327\n", "
\n", " +0.206\n", " \n", " 7752_45684\n", "
\n", " +0.188\n", " \n", " 9702_30571\n", "
\n", " +0.163\n", " \n", " 7757_2991\n", "
\n", " +0.136\n", " \n", " 7752_10367\n", "
\n", " +0.136\n", " \n", " 9752_772\n", "
\n", " … 340 more positive …\n", "
\n", " … 49651 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.373\n", " \n", " 9734_39958\n", "
\n", " +0.337\n", " \n", " 9734_48386\n", "
\n", " +0.327\n", " \n", " 9734_48406\n", "
\n", " +0.321\n", " \n", " 9734_39938\n", "
\n", " +0.297\n", " \n", " 9734_48388\n", "
\n", " +0.164\n", " \n", " 9935_39681\n", "
\n", " +0.145\n", " \n", " 9734_48406 9734_48386\n", "
\n", " +0.142\n", " \n", " 9935_14336\n", "
\n", " +0.141\n", " \n", " 7752_22712\n", "
\n", " +0.140\n", " \n", " 9734_39958 9734_39938\n", "
\n", " … 820 more positive …\n", "
\n", " … 49171 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", "\n", " \n", "
\n", " Weight?\n", " Feature
\n", " +0.462\n", " \n", " 9746_38506\n", "
\n", " +0.318\n", " \n", " 9953_6545\n", "
\n", " +0.297\n", " \n", " 9757_13626\n", "
\n", " +0.225\n", " \n", " 9745_38058\n", "
\n", " +0.193\n", " \n", " 9953_6545 9746_38506\n", "
\n", " +0.178\n", " \n", " 9746_38506 9953_6545\n", "
\n", " +0.162\n", " \n", " 9953_6544\n", "
\n", " +0.155\n", " \n", " 9746_38506 9746_38506\n", "
\n", " +0.150\n", " \n", " 9757_13626 9745_38058\n", "
\n", " +0.147\n", " \n", " 9757_14429\n", "
\n", " … 149 more positive …\n", "
\n", " … 49842 more negative …\n", "
\n", "\n", " \n", " \n", "
\n", " \n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", " \n", "\n", "\n", " \n", 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"\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 81, "metadata": {}, "output_type": "execute_result" } ], "source": [ "eli5.show_weights(estimator=clf, feature_names=vectorizer.get_feature_names(), top=10)" ] }, { "cell_type": "markdown", "id": "d4fafc2f-3980-4a19-9459-e6bff3b361c2", "metadata": {}, "source": [ "Maybe increasing `max_features` for TF-IDF vectorizer will improve the model. \n", "Also, we see that unigrams and bigrams are used extensively, while trigrams are not that important." ] }, { "cell_type": "markdown", "id": "e07fa921-49c2-4fa8-a11c-b804a372be63", "metadata": {}, "source": [ "### Tuning" ] }, { "cell_type": "markdown", "id": "9b64bfec-18ce-428a-b563-1e63b75deed2", "metadata": { "tags": [] }, "source": [ "#### TF-IDF" ] }, { "cell_type": "code", "execution_count": 82, "id": "80c7e79c-95db-403f-b819-74cc1d4f55c5", "metadata": {}, "outputs": [], "source": [ "X_train_tfidf, X_test_tfidf = tf_idf_transform(\n", " ngram_range=(1, 3),\n", " max_features=100_000,\n", " train_texts=train_journeys,\n", " test_texts=test_journeys,\n", ")" ] }, { "cell_type": "code", "execution_count": 83, "id": "21fac768-86f0-4394-a371-a082810c9b0b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Precision: 0.856 \n", "Recall: 0.898\n" ] } ], "source": [ "res = fit_and_score(\n", " C=15,\n", " X_train=X_train_tfidf,\n", " y_train=y_train,\n", " X_val=X_test_tfidf,\n", " y_val=y_test,\n", ")\n", "\n", "print(f\"Precision: {res[0]} \\nRecall: {res[1]}\")" ] }, { "cell_type": "markdown", "id": "71383ec5-32f8-42b8-a405-5e2e259f6e23", "metadata": {}, "source": [ "##### `ngram_range`" ] }, { "cell_type": "code", "execution_count": 84, "id": "bbadd4c6-f3f6-4485-82ab-c8add4a702f8", "metadata": {}, "outputs": [], "source": [ "ngram_ranges = [(1, 1), (1, 2), (1, 3), (1, 4), (1, 5)]" ] }, { "cell_type": "code", "execution_count": 85, "id": "57e1d866-e0fa-48b2-a109-64937f19de95", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "fa3351afaffe4b3f965a7c094a38a833", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Tuning ngram ranges: 0it [00:00, ?it/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(0) (1, 1): (0.837, 0.884)\n", "(1) (1, 2): (0.849, 0.892)\n", "(2) (1, 3): (0.856, 0.898)\n", "(3) (1, 4): (0.856, 0.898)\n", "(4) (1, 5): (0.856, 0.898)\n" ] } ], "source": [ "scores = {}\n", "for i, ngram_range in tqdm(enumerate(ngram_ranges), desc=\"Tuning ngram ranges\"):\n", " X_train_tfidf, X_test_tfidf = tf_idf_transform(\n", " ngram_range=ngram_range,\n", " max_features=100_000,\n", " train_texts=train_journeys,\n", " test_texts=test_journeys,\n", " )\n", " scores[ngram_range] = fit_and_score(\n", " C=15,\n", " X_train=X_train_tfidf,\n", " y_train=y_train,\n", " X_val=X_test_tfidf,\n", " y_val=y_test,\n", " )\n", " print(f\"({i}) {ngram_range}: {scores[ngram_range]}\")" ] }, { "cell_type": "markdown", "id": "2c99f0db-7260-4bf9-a25e-11a28660c424", "metadata": {}, "source": [ "Seems like $(1, 3)$ ngram range is optimal for this task" ] }, { "cell_type": "markdown", "id": "16426273-e6d2-4bdf-8fd5-23f9f2e2dd4a", "metadata": {}, "source": [ "##### `max_features`" ] }, { "cell_type": "code", "execution_count": 86, "id": "3a1d3962-1550-4597-aa2b-bd2bbd9478e8", "metadata": {}, "outputs": [], "source": [ "max_features_ = [10_000, 50_000, 100_000, 250_000, 500_000]" ] }, { "cell_type": "code", "execution_count": 87, "id": "f27cff97-868c-4b69-80e4-5dca44525b8b", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "719b84a70f724ff48551ad852ea5d6a9", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Tuning maximum number of features: 0it [00:00, ?it/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(0) 10000: (0.83, 0.88)\n", "(1) 50000: (0.85, 0.894)\n", "(2) 100000: (0.856, 0.898)\n", "(3) 250000: (0.853, 0.894)\n", "(4) 500000: (0.853, 0.894)\n" ] } ], "source": [ "scores = {}\n", "for i, max_features in tqdm(\n", " enumerate(max_features_), desc=\"Tuning maximum number of features\"\n", "):\n", " X_train_tfidf, X_test_tfidf = tf_idf_transform(\n", " ngram_range=(1, 3),\n", " max_features=max_features,\n", " train_texts=train_journeys,\n", " test_texts=test_journeys,\n", " )\n", " scores[max_features] = fit_and_score(\n", " C=15,\n", " X_train=X_train_tfidf,\n", " y_train=y_train,\n", " X_val=X_test_tfidf,\n", " y_val=y_test,\n", " )\n", " print(f\"({i}) {max_features}: {scores[max_features]}\")" ] }, { "cell_type": "markdown", "id": "dba180e9-8168-477a-8b60-55c3529e2852", "metadata": {}, "source": [ "$\\text{100 000}$ looks like an optimal choice" ] }, { "cell_type": "markdown", "id": "4ea70217-6629-4f58-a041-022401945848", "metadata": {}, "source": [ "##### Final params" ] }, { "cell_type": "markdown", "id": "5bbaf958-6d07-4a80-b68f-835e219e04da", "metadata": {}, "source": [ "```python\n", "{ngram_range=(1, 3), max_features=100_000}\n", "```" ] }, { "cell_type": "markdown", "id": "5a2d5c1c-bc5e-4a7d-b46b-0fe846eaea20", "metadata": {}, "source": [ "#### Logistic Regression" ] }, { "cell_type": "markdown", "id": "7fd7b751-6a96-452b-9dba-d9c7b0c8742f", "metadata": {}, "source": [ "Let's split test dataset into validation and testing datasets " ] }, { "cell_type": "code", "execution_count": 88, "id": "b0cdd9f4-590c-4151-af5b-01743b6164d8", "metadata": {}, "outputs": [], "source": [ "X_train_tfidf, X_test_tfidf = tf_idf_transform(\n", " ngram_range=(1, 3),\n", " max_features=100_000,\n", " train_texts=train_journeys,\n", " test_texts=test_journeys,\n", ")" ] }, { "cell_type": "code", "execution_count": 89, "id": "0ac89b06-0d36-47a4-86be-bfa6c317853b", "metadata": {}, "outputs": [], "source": [ "X_test_tfidf_test, X_test_tfidf_val, y_test_test, y_test_val = train_test_split(\n", " X_test_tfidf, y_test, test_size=0.5\n", ")" ] }, { "cell_type": "code", "execution_count": 90, "id": "6c723928-5e80-40a5-b9cb-bd6aed80e11f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([ 1. , 1.66810054, 2.7825594 , 4.64158883,\n", " 7.74263683, 12.91549665, 21.5443469 , 35.93813664,\n", " 59.94842503, 100. ])" ] }, "execution_count": 90, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Cs = np.logspace(0, 2, 10)\n", "Cs" ] }, { "cell_type": "code", "execution_count": 91, "id": "46541fbe-b325-4f1a-9da7-c6207b005ee3", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9158e2bf3c3245beaabcdea76bf967b2", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Tuning Logistic Regression: 0it [00:00, ?it/s]" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(0) 1.0: (0.816, 0.842)\n", "(1) 1.6681005372000588: (0.829, 0.853)\n", "(2) 2.7825594022071245: (0.839, 0.863)\n", "(3) 4.641588833612778: (0.846, 0.871)\n", "(4) 7.742636826811269: (0.846, 0.871)\n", "(5) 12.91549665014884: (0.853, 0.878)\n", "(6) 21.544346900318832: (0.853, 0.878)\n", "(7) 35.93813663804626: (0.853, 0.878)\n", "(8) 59.94842503189409: (0.853, 0.878)\n", "(9) 100.0: (0.853, 0.878)\n" ] } ], "source": [ "scores = {}\n", "\n", "for i, C in tqdm(enumerate(Cs), desc=\"Tuning Logistic Regression\"):\n", " scores[C] = fit_and_score(C, X_train_tfidf, y_train, X_test_tfidf_val, y_test_val)\n", " print(f\"({i}) {C}: {scores[C]}\")" ] }, { "cell_type": "markdown", "id": "03c0b5da-1860-4181-bc1b-917e5448d76e", "metadata": {}, "source": [ "Seems like, there is no more room for improvement, and we can pick C values from range $(10, 60)$." ] }, { "cell_type": "markdown", "id": "424832ef-02d6-4799-a99a-f8084ab041b6", "metadata": {}, "source": [ "Let's test on the part of the test dataset" ] }, { "cell_type": "code", "execution_count": 92, "id": "39511c4e-52b3-4fa4-ad70-ca85541f6d96", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Precision: 0.825 \n", "Recall: 0.845\n" ] } ], "source": [ "res = fit_and_score(\n", " C=15,\n", " X_train=X_train_tfidf,\n", " y_train=y_train,\n", " X_val=X_test_tfidf_test,\n", " y_val=y_test_test,\n", ")\n", "print(f\"Precision: {res[0]} \\nRecall: {res[1]}\")" ] }, { "cell_type": "markdown", "id": "a68f7f22-e1da-4a54-8f77-41d00c46de4a", "metadata": {}, "source": [ "And on the whole test dataset" ] }, { "cell_type": "code", "execution_count": 93, "id": "40bce2e0-40a9-4bf3-98db-9621175701b4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Precision: 0.856 \n", "Recall: 0.898\n" ] } ], "source": [ "res = fit_and_score(\n", " C=15, X_train=X_train_tfidf, y_train=y_train, X_val=X_test_tfidf, y_val=y_test\n", ")\n", "print(f\"Precision: {res[0]} \\nRecall: {res[1]}\")" ] }, { "cell_type": "markdown", "id": "0f476653-ef6c-40fa-9ee5-ff8f0e456df1", "metadata": {}, "source": [ "The result on the whole test dataset is better because we tuned the algorithm on one of its parts" ] }, { "cell_type": "markdown", "id": "18ef8183-f822-4994-8fa8-8d59f57d0182", "metadata": {}, "source": [ "##### Final params" ] }, { "cell_type": "markdown", "id": "2b4dbb05-9c0c-45f7-9427-55b5a9de123b", "metadata": {}, "source": [ "```python\n", "C=15\n", "```" ] }, { "cell_type": "markdown", "id": "4b0728f6-e411-4b08-8d50-4cb096b7ee15", "metadata": {}, "source": [ "## Training and Prediction on unlabeled data" ] }, { "cell_type": "code", "execution_count": 94, "id": "a6f1c3b2-1d77-4052-8b3b-18c0c2d825bd", "metadata": {}, "outputs": [], "source": [ "X_train = test_data_left.drop_duplicates([\"hash_id\", \"user_journey\"])\n", "X_test = test_data_right.drop_duplicates([\"hash_id\", \"user_journey\"])\n", "\n", "y_train = X_train[\"hash_id\"].values\n", "y_test = X_test[\"hash_id\"].values\n", "train_journeys = X_train[\"user_journey\"].values\n", "test_journeys = X_test[\"user_journey\"].values" ] }, { "cell_type": "code", "execution_count": 95, "id": "912b61cf-a0d1-4edc-b5a5-69f22faaa581", "metadata": {}, "outputs": [], "source": [ "X_train_tfidf, X_test_tfidf = tf_idf_transform(\n", " ngram_range=(1, 3),\n", " max_features=100_000,\n", " train_texts=train_journeys,\n", " test_texts=test_journeys,\n", ")" ] }, { "cell_type": "code", "execution_count": 96, "id": "0136bc12-3b81-454f-b241-886ee4a3824e", "metadata": {}, "outputs": [], "source": [ "clf = LogisticRegression(\n", " C=15,\n", " random_state=SEED,\n", " n_jobs=-1,\n", " verbose=2,\n", " multi_class=\"multinomial\", # to solve the task like Softmax Classifier\n", " solver=\"sag\", # for faster training\n", ")" ] }, { "cell_type": "code", "execution_count": 97, "id": "ce5206a2-b1c8-497d-bef8-299d88da7b44", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[Parallel(n_jobs=-1)]: Using backend ThreadingBackend with 16 concurrent workers.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "convergence after 54 epochs took 384 seconds\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "[Parallel(n_jobs=-1)]: Done 1 out of 1 | elapsed: 6.4min finished\n" ] }, { "data": { "text/html": [ "
LogisticRegression(C=15, multi_class='multinomial', n_jobs=-1, random_state=42,\n",
       "                   solver='sag', verbose=2)
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" ], "text/plain": [ "LogisticRegression(C=15, multi_class='multinomial', n_jobs=-1, random_state=42,\n", " solver='sag', verbose=2)" ] }, "execution_count": 97, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clf.fit(X_train_tfidf, y_train)" ] }, { "cell_type": "code", "execution_count": 98, "id": "45daaed9-c363-4872-800c-b241045d67b3", "metadata": {}, "outputs": [], "source": [ "y_pred = clf.predict(X_test_tfidf)" ] }, { "cell_type": "markdown", "id": "29d8b7f1-dbf8-4c87-9644-10f129ebe62b", "metadata": {}, "source": [ "### Saving results" ] }, { "cell_type": "code", "execution_count": 99, "id": "af4e8dba-49b2-406d-aa51-40ce8a13e022", "metadata": {}, "outputs": [], "source": [ "res = pd.DataFrame.from_dict({\"id1\": y_test, \"id2\": y_pred})" ] }, { "cell_type": "code", "execution_count": 100, "id": "9bc85864-3bf0-4a23-8f24-e717d6553c7e", "metadata": {}, "outputs": [], "source": [ "res.to_csv(FINAL_MAPPING_PATH_CSV, index=False)" ] } ], "metadata": { "kernelspec": { "display_name": "mini-projects", "language": "python", "name": "mini-projects" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }