{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Data Processing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Reproduce results of our [AAAI paper](http://www.cs.iit.edu/~culotta/pubs/culotta15predicting.pdf)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook assumes the data is in place. You can get data either by running [data_collection.ipynb](https://github.com/tapilab/aaai-2015-demographics/blob/master/src/data_collection.ipynb)\n", "or by running the next cell, which downloads it." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "username2brand.pklalready exists.\n", "brand2counts.pklalready exists.\n", "id2brand.pklalready exists.\n", "brands.jsonalready exists.\n" ] } ], "source": [ "# Download Twitter data from server if not already present.\n", "import os\n", "import urllib\n", "\n", "for fname in ['username2brand.pkl', 'brand2counts.pkl', 'id2brand.pkl', 'brands.json']:\n", " if not os.path.isfile('../data/' + fname):\n", " url = 'http://tapi.cs.iit.edu/data/aaai-2015-demographics/originals/' + fname\n", " print('downloading %s to %s' % (url, '../data/' + fname))\n", " urllib.urlretrieve(url, \"../data/\" + fname)\n", " else:\n", " print(fname + 'already exists.')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Unpickle everything\n", "import pickle\n", "id2brand = pickle.load(open('../data/id2brand.pkl', 'rb'))\n", "brand2counts = pickle.load(open('../data/brand2counts.pkl', 'rb'))\n", "username2brand = pickle.load(open('../data/username2brand.pkl', 'rb'))" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "total friend links: 177997246.0\n" ] }, { "data": { "image/png": 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8E+lL/I2kiXyvBs7KjzdEsLRXdewkd/eZmY1iOWi9BHgDqbW1I2km+suBi4CzIrixdzVs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\n3dc8j1tSZmbWinyn3w0ieKC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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "\n", "# Plot descriptive stats of the data.\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "\n", "def plot_data_figs():\n", " figure, axes = plt.subplots(2, 1, sharex=True)\n", " unique_friends = sorted([len(d.keys()) for d in brand2counts.values()], reverse=True)\n", " axes[0].plot(unique_friends)\n", " axes[0].set_xscale('log')\n", " axes[0].set_yscale('log')\n", " axes[0].set_title('number of unique neighbors', size=16)\n", "\n", " brcounts = sorted([sum(d.values()) for d in brand2counts.values()], reverse=True)\n", " print('total friend links:', sum(brcounts))\n", " axes[1].plot(brcounts)\n", " axes[1].set_xscale('log')\n", " axes[1].set_yscale('log')\n", " axes[1].set_title('number of neighbor links', size=16)\n", " axes[1].set_xlim((0,1500))\n", " axes[1].set_xlabel('rank', size=14)\n", " axes[1].set_ylabel(' ' * 30 + 'count', size=14)\n", " figure.tight_layout()\n", " plt.savefig('data.pdf', bbox_inches='tight')\n", "\n", "plot_data_figs()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The feature vector for one brand looks like this:\n", " (0, 0)\t20.0\n", " (0, 1)\t15.0\n", " (0, 2)\t18.0\n", " (0, 4)\t1.0\n", " (0, 5)\t3.0\n", " (0, 6)\t3.0\n", " (0, 9)\t3.0\n", " (0, 10)\t1.0\n", " (0, 11)\t8.0\n", " (0, 13)\t6.0\n", " (0, 14)\t5.0\n", " (0, 15)\t3.0\n", " (0, 17)\t6.0\n", " (0, 18)\t3.0\n", " (0, 19)\t1.0\n", " (0, 20)\t1.0\n", " (0, 24)\t3.0\n", " (0, 26)\t16.0\n", " (0, 27)\t2.0\n", " (0, 28)\t1.0\n", " (0, 29)\t2.0\n", " (0, 31)\t3.0\n", " (0, 32)\t1.0\n", " (0, 33)\t1.0\n", " (0, 34)\t4.0\n", " :\t:\n", " (0, 46553)\t5.0\n", " (0, 46554)\t1.0\n", " (0, 46555)\t18.0\n", " (0, 46556)\t3.0\n", " (0, 46559)\t1.0\n", " (0, 46562)\t4.0\n", " (0, 46565)\t3.0\n", " (0, 46567)\t2.0\n", " (0, 46568)\t4.0\n", " (0, 46573)\t1.0\n", " (0, 46577)\t1.0\n", " (0, 46580)\t2.0\n", " (0, 46583)\t8.0\n", " (0, 46584)\t2.0\n", " (0, 46587)\t1.0\n", " (0, 46592)\t1.0\n", " (0, 46604)\t3.0\n", " (0, 46613)\t1.0\n", " (0, 46618)\t1.0\n", " (0, 46621)\t3.0\n", " (0, 46622)\t4.0\n", " (0, 46631)\t3.0\n", " (0, 46640)\t2.0\n", " (0, 46642)\t1.0\n", " (0, 46648)\t2.0\n" ] } ], "source": [ "# Normalize data and create sparse matrix.\n", "import numpy as np\n", "from numpy import array as npa\n", "from sklearn.feature_extraction import DictVectorizer\n", "from sklearn.feature_extraction.text import TfidfTransformer\n", "from sklearn.preprocessing import scale\n", "\n", "brand_ids = npa(list(brand2counts.keys()))\n", "vec = DictVectorizer()\n", "X = vec.fit_transform(brand2counts.values())\n", "print('The feature vector for one brand looks like this:\\n%s' % str(X[0]))" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "177997246 total friend links\n", "The normalized feature vector for one brand looks like this:\n", " (0, 0)\t0.000156586416128\n", " (0, 1)\t0.000117439812096\n", " (0, 2)\t0.000140927774516\n", " (0, 4)\t7.82932080642e-06\n", " (0, 5)\t2.34879624193e-05\n", " (0, 6)\t2.34879624193e-05\n", " (0, 9)\t2.34879624193e-05\n", " (0, 10)\t7.82932080642e-06\n", " (0, 11)\t6.26345664514e-05\n", " (0, 13)\t4.69759248385e-05\n", " (0, 14)\t3.91466040321e-05\n", " (0, 15)\t2.34879624193e-05\n", " (0, 17)\t4.69759248385e-05\n", " (0, 18)\t2.34879624193e-05\n", " (0, 19)\t7.82932080642e-06\n", " (0, 20)\t7.82932080642e-06\n", " (0, 24)\t2.34879624193e-05\n", " (0, 26)\t0.000125269132903\n", " (0, 27)\t1.56586416128e-05\n", " (0, 28)\t7.82932080642e-06\n", " (0, 29)\t1.56586416128e-05\n", " (0, 31)\t2.34879624193e-05\n", " (0, 32)\t7.82932080642e-06\n", " (0, 33)\t7.82932080642e-06\n", " (0, 34)\t3.13172832257e-05\n", " :\t:\n", " (0, 46553)\t3.91466040321e-05\n", " (0, 46554)\t7.82932080642e-06\n", " (0, 46555)\t0.000140927774516\n", " (0, 46556)\t2.34879624193e-05\n", " (0, 46559)\t7.82932080642e-06\n", " (0, 46562)\t3.13172832257e-05\n", " (0, 46565)\t2.34879624193e-05\n", " (0, 46567)\t1.56586416128e-05\n", " (0, 46568)\t3.13172832257e-05\n", " (0, 46573)\t7.82932080642e-06\n", " (0, 46577)\t7.82932080642e-06\n", " (0, 46580)\t1.56586416128e-05\n", " (0, 46583)\t6.26345664514e-05\n", " (0, 46584)\t1.56586416128e-05\n", " (0, 46587)\t7.82932080642e-06\n", " (0, 46592)\t7.82932080642e-06\n", " (0, 46604)\t2.34879624193e-05\n", " (0, 46613)\t7.82932080642e-06\n", " (0, 46618)\t7.82932080642e-06\n", " (0, 46621)\t2.34879624193e-05\n", " (0, 46622)\t3.13172832257e-05\n", " (0, 46631)\t2.34879624193e-05\n", " (0, 46640)\t1.56586416128e-05\n", " (0, 46642)\t7.82932080642e-06\n", " (0, 46648)\t1.56586416128e-05\n" ] } ], "source": [ "# Normalize by row.\n", "from sklearn.preprocessing import normalize\n", "print('%d total friend links' % X.sum())\n", "X = normalize(X, norm='l1', axis=1)\n", "print('The normalized feature vector for one brand looks like this:\\n%s' % str(X[0]))" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "predicting ['No Kids', 'Has Kids'] for 1051 brands\n" ] }, { "data": { "image/png": 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HNBeIBmNzY22viGFUNZfNda35/bBmrR0bsBCm74Avq2vTdwAL3bbuW9069e3LClOGYb66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\nYeQdEwJ1pdW9bfLo4WQYRiWYEDCqxjy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doC4kzDH0N8Dh/vPdOJXTIuBxX1dU70Hg8kmxO+h8ic8FmIcbq0T2hw3AuknA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\nUWBl8tzS1ArJc89IqWpOzFD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Uda//OAWYBOwAzlDVb/v9XwJeX8821Jj+Rjcgg/5GNyCD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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top Coefficients for No Kids\n", "pos:14677919 (1.4e+02) 16303106 (97) 807095 (96) 5988062 (95) 1344951 (88) 22027186 (84) 14075928 (81) 158414847 (81) 16129920 (80) 15164565 (79)\n", "neg:29730065 (-1.5e+02) 18784113 (-1.5e+02) 15846407 (-1.3e+02) 14709355 (-1.2e+02) 16581734 (-1.2e+02) 94919897 (-1.1e+02) 16492009 (-1.1e+02) 106837463 (-1.1e+02) 16310534 (-1.1e+02) 36782022 (-1.1e+02)\n", "Top Coefficients for Has Kids\n", "pos:29730065 (1.5e+02) 18784113 (1.5e+02) 15846407 (1.3e+02) 14709355 (1.2e+02) 16581734 (1.2e+02) 94919897 (1.1e+02) 16492009 (1.1e+02) 106837463 (1.1e+02) 16310534 (1.1e+02) 36782022 (1.1e+02)\n", "neg:14677919 (-1.4e+02) 16303106 (-97) 807095 (-96) 5988062 (-95) 1344951 (-88) 22027186 (-84) 14075928 (-81) 158414847 (-81) 16129920 (-80) 15164565 (-79)\n", "predicting ['Male', 'Female'] for 1066 brands\n" ] }, { "data": { "image/png": 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FNIhT4+zAPaFfFmVP3YhTiLyTJAL7Qlxm2FNJIrN/jluVaPT6E7jVxhdIAuUO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\nAzl88VcBXJbeAAAAAElFTkSuQmCC\n", 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zqNATq7rfm6mBprLVOm82/ALqdWHWCu/rhHPZ5/uqNEK4+iCmdB9Zv/hkvqDS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\nkKsdcErgyTpKV5E0jq5QZ0+IAtBCBuF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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top Coefficients for Male\n", "pos:51263592 (3.6e+02) 26257166 (3e+02) 2557521 (2.8e+02) 1344951 (2.6e+02) 28870086 (2.5e+02) 10671602 (2.4e+02) 32765534 (2.3e+02) 36362259 (2.2e+02) 18927441 (2.2e+02) 19426551 (2.1e+02)\n", "neg:15846407 (-6.3e+02) 19397785 (-5.5e+02) 21324258 (-4e+02) 106837463 (-3.7e+02) 20710809 (-3.5e+02) 15131310 (-3.4e+02) 11522502 (-3.2e+02) 38531995 (-3.2e+02) 25589776 (-3.1e+02) 25087685 (-3e+02)\n", "Top Coefficients for Female\n", "pos:15846407 (6.3e+02) 19397785 (5.5e+02) 21324258 (4e+02) 106837463 (3.7e+02) 20710809 (3.5e+02) 15131310 (3.4e+02) 11522502 (3.2e+02) 38531995 (3.2e+02) 25589776 (3.1e+02) 25087685 (3e+02)\n", "neg:51263592 (-3.6e+02) 26257166 (-3e+02) 2557521 (-2.8e+02) 1344951 (-2.6e+02) 28870086 (-2.5e+02) 10671602 (-2.4e+02) 32765534 (-2.3e+02) 36362259 (-2.2e+02) 18927441 (-2.2e+02) 19426551 (-2.1e+02)\n", "predicting ['No College', 'College', 'Grad School'] for 1046 brands\n" ] }, { "data": { "image/png": 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rIhqzUW9GpdBLrf49Cb3cnfKbDPNiZqBdKXWTvDlq1S5zweeOAbeR5jEMswrz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\n5FIj/abNBJpA19hoMO95mn3erEXltfY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VIoEdITmNwglTQYW56JrdoApFb13y2tJYsdLoQrCqJL+8OiHtnGomnV/Ipw6qnmMI2JJV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\nYyxYzDAMwwjGJgGjJbA4AcOoD6YOMpo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OwuetrkUfZjtZN8ME3EwCsZ2LCQErLVdmmuCSJs9KJtVyr51Z/dTYCbwZJuBm6IOVJjMM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\nIyj3Ahz4Hgx/sHjdMDB6C/A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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top Coefficients for No College\n", "pos:10228272 (1.2e+02) 10671602 (75) 29758446 (68) 21447363 (68) 23151437 (64) 24742040 (63) 18927441 (60) 180505807 (57) 17919972 (56) 15234657 (55)\n", "neg:14677919 (-1.1e+02) 16303106 (-1e+02) 5988062 (-95) 807095 (-91) 3108351 (-89) 16017475 (-85) 2735591 (-81) 1344951 (-81) 972651 (-80) 158414847 (-75)\n", "Top Coefficients for College\n", "pos:115485051 (35) 22027186 (26) 25521487 (25) 6480682 (25) 1344951 (23) 36686415 (23) 15485441 (22) 66561957 (22) 972651 (20) 90420314 (20)\n", "neg:2467791 (-43) 30313925 (-38) 807095 (-29) 813286 (-29) 3108351 (-27) 500704345 (-27) 9300262 (-26) 759251 (-25) 17006157 (-23) 51241574 (-22)\n", "Top Coefficients for Grad School\n", "pos:14677919 (1.3e+02) 807095 (1.2e+02) 5988062 (1.2e+02) 3108351 (1.2e+02) 2467791 (1.1e+02) 16017475 (1e+02) 16303106 (90) 5392522 (89) 1339835893 (88) 15164565 (85)\n", "neg:10228272 (-1.1e+02) 21447363 (-74) 10671602 (-68) 180505807 (-66) 23151437 (-65) 29758446 (-59) 18927441 (-59) 24742040 (-58) 17919972 (-57) 52551600 (-57)\n", "predicting ['Caucasian', 'Hispanic', 'African American', 'Asian'] for 1035 brands\n" ] }, { "data": { "image/png": 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VS7BEeUdi0Unde8DLEvsAzlAYPgtYGUdYZckmt9nz2DgA3fsnorQO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\n2SKeIqfuYuz4ZWeJyMr8zrR/CJaRmlc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1GD5dthwCxqvPK43D4d2w/ZJIPv9FGO6tztk/cwqM/oSnuErec+wF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\nADAMw+hSTAAYhmF0KSYADMMwupT/B1HcCTX0itJfAAAAAElFTkSuQmCC\n", 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NvwVmHJSqtF4HC7ty/QQLp8JPkrDR0UR3nfvGN1TYXxVKnSBE9Ujs60jpVmZh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\nCNEBSOyFEKIDkNgLIUQHILEXQogO4P8DEZePpL/qB4IAAAAASUVORK5CYII=\n", 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gMSFE8aLvaP9CmOvw+uhwdQW5u7vDXkPnAV+K9JeWcLx5KP+d1Afb/FVPbJ0G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\nG4ZhtAGm7A3DMNqA/wsAZlRhdhRtjAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top Coefficients for Caucasian\n", "pos:1367531 (2.8e+02) 15485441 (2.7e+02) 15846407 (2.7e+02) 14920785 (2.6e+02) 428333 (2.4e+02) 25521487 (2.1e+02) 14075928 (2e+02) 51241574 (2e+02) 16303106 (1.8e+02) 34738598 (1.7e+02)\n", "neg:27195114 (-2.8e+02) 23561980 (-2.6e+02) 18220175 (-2.4e+02) 23151437 (-2.4e+02) 338084918 (-2.4e+02) 117778179 (-2.3e+02) 19028953 (-2.3e+02) 17169320 (-2.2e+02) 25110374 (-2.2e+02) 17929027 (-2.2e+02)\n", "Top Coefficients for Hispanic\n", "pos:16664681 (83) 20346956 (77) 36511031 (74) 1059194370 (69) 14093707 (68) 16374678 (68) 23043294 (66) 18132494 (59) 10252962 (59) 17379685 (59)\n", "neg:1367531 (-1e+02) 14920785 (-99) 15485441 (-96) 428333 (-95) 15846407 (-90) 51241574 (-75) 34738598 (-65) 120943272 (-62) 7744592 (-62) 17074714 (-61)\n", "Top Coefficients for African American\n", "pos:23151437 (2.3e+02) 27195114 (2.1e+02) 18220175 (2e+02) 117778179 (2e+02) 23561980 (2e+02) 25110374 (2e+02) 17169320 (1.9e+02) 19028953 (1.9e+02) 17929027 (1.9e+02) 84358766 (1.9e+02)\n", "neg:15485441 (-1.2e+02) 115485051 (-1.2e+02) 14075928 (-1.2e+02) 15846407 (-1.2e+02) 25521487 (-1.2e+02) 16303106 (-1.1e+02) 1367531 (-1.1e+02) 14920785 (-1.1e+02) 90420314 (-1e+02) 14824849 (-95)\n", "Top Coefficients for Asian\n", "pos:36511031 (50) 14093707 (48) 816653 (47) 1344951 (43) 18132494 (39) 30068744 (37) 16664681 (35) 16562949 (32) 18993395 (31) 20346956 (31)\n", "neg:1367531 (-57) 15846407 (-55) 14920785 (-53) 428333 (-49) 15485441 (-49) 34738598 (-36) 51241574 (-35) 7744592 (-33) 25521487 (-32) 28785486 (-32)\n", "predicting ['18-24', '25-34', '35-44', '45-54', '55-64', '65+'] for 1072 brands\n" ] }, { "data": { "image/png": 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BsdHW3sPoNSyAnGF0Cdk8kHonS9pColVeX93iHWQYRtOcTs0Daesc5/RKlrSFQd7rOKYE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\nn0VTAt20Sv0iVT0DeClwiYj8dt4CLQD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+huBtvl59ElrxxKyD+g403rfPtynLYmloOiEqmVdRZa0JxGYR63clzEB2ZX13\n/jvIEWUtS13UPRY+rf6O8/yPdKh92nSdsju1kw/TbalbhUA7/1ikLNK2M+1v9Z7VZxmcDXbCzuYX\nTDF10JAm7BjWat3BhF3Bg37AlQQBIqGPnwQhsL4iQOYSBIg381y9p/G6q0OfRAltWuPblBkpLUH9\ntdGbiKab0ub7H4hv+Oq2gb6o/+l2BEgT/5/abB1TBxVK9/lNcVPZoevgMRUVyfNE5BzNMaUNgq9X\nnucSEdnp6u6/DCaeB/jrTsx04lnj96ywSuBkf7w/UHHEfAMBLBykIUjLglcHDVLr3+danL+dCoN9\nTnVyXpA34VUvGyLRwcDtmXwz1YA1twefW7UK3l933wsqfoU2uUhhFRPRGZ9XYc1AbQwEgAu9aW2W\ne+SDD8NEYLY6AUx5k9iYKW0e4hu+tEf89GhXBtCxeAKF0p1f+vA2WBXufB10eXn+CbN0mrFIXK0K\nxKx7Dn0QhvoD/Xo/8EHgDFg4LkGHflz1fHHEDXaVNt/p8wAWF2lw2La4WD2WgcYYCDKQ/TwAMwuw\ntr92/eSIt9nvkwQncF6wDax2TaoIvElqw1bGdirH4gUAjA4m2PoPVut+9axaZ3pTQd0Y3fci1B7t\nPU9XCryyp1ednNZYytOv8WDl8brtWXLQkolophojosvOsvUfOdyo5qjskpUE3bwE1jTpztxgIKFs\nQIM2pwZ9j+02dn6FGtYwAjVTurrI9WPDGsbOPP3s1EEN5rK51EH+e09V5y3H1MrveAnbps3WsZnA\nCiRuvZAVrDxGGW9BczSqTjQoX5zjqAvjmjzg8EG4al3drt+D1c/1RWLyDnvVyJVB2XCgLhmkVm0D\nVeugPnVupcNZUV/Q6DlJ8PHjv4NhElQ6/q8mfE9h3uyNIK+tVRfN3ujbdGpj3TDv4c/BROBqegKY\n/Jw7Hjw1wToo4XqN5FPnLS9a+x13LyYEVhjZZqm6C3hqbS3dRQ40qt7KFhDZcQGSBNfMCc7DQqg6\nmTqhetW5h2FLMDhv8XkAfRsaVVR9G4IWJfz+K3lZJpWxmL1rSNDrB5/rW4T39tUJH69qEoXbpE7N\n5AWIJJiWTgcNGXuF09ff4s9fDnzjFe740Ax8hKpK52vA/ExQdzxBHTQObPNxBercRuSNNdClZpFG\nlbKnL52c1ljKVsuQYTbZ5neW4XM+2VSQqOlpuurElW9IUPlUXCBn1R1ZSFCNeWdta+caVUVrAxcN\nsU1dGzXIKdFwAAAgAElEQVRBRaXVujET0YEEy6KBhax6vk0Rk9esHdBZGwFHZ4M2zeb9zRSlJrSU\n+j+oTdcpu9GdfBhL3ftPF3dLkG5G6EwmGwbbcDBOXeOAkekEnX/gZmHj4YRdsn5NoDIQh+0d1Wrd\nUW1ssyt36wX1LhrC4C9DCQJkyNddn3Df9b5s3YHGsnXBOsXQnoTr+jWBjQm7jUOBmOX6YWg2eJ4m\nhEDrbiMstfJ/hjZdp+xGd/JhLHXvP1XcJj/m0jkrXu/6XQkbqLzTtNHphIE6EAL9CQup/ZVBM2Ew\nDt/mh7X6mY/642F1ZUPa+DxDdXUbfPFo1n2zfRLFBG3cDUb1t9O8c8BY3eyycvbSrNTZRyvjpq0J\ndDGtbE/XEs1S4+2d2tvoomFmrzvuH21coL1g1JfdAZxYe6f+O6rH85NwFfA4f/51YMEHd1kcaFyA\nXQwWkYc3JCzu+jWDORLcUYRtWIQX9lVNOV8IfN3r9QdpfJ5wj4EsOvfQP/PnM8DgYvW43my1Ym47\nOuDWKUK9/TXB88R09/M/bYwxPP/T8JOauuAZX1RuI2BQKZib6TrKllydlGgrKVGoI7jOvwVltdfd\nq171ctS8NPIGm+X6ITaLSPfI6csXEsq9/n1AG1U6oZln374E9w6+zVnhJVfPN157dQ4T0VwqnTS3\n2tE4wNXPJO0Gj5uIdvsu2sZ7dudO/g79H2rTdSIXuz5IX6w/78aHWUmpqB9qUf907fgOivm1ITO+\nbcy+PUsIxIK6r02wyV8bun5IVa/A2vmEReVwQVoji8qRRePsCF5pAj7H95OxcB+NMdzWb7WIl5Iy\n/re6IbUybsbUQRXzvlcBxwKfxtnA/SHwQKSe0dXETfayVFCtelDUqJpKJmGWqgpklmq83rGL4fzB\nwFRzELYHJoYxdwizc7A5UJds9nlHn2YBnt9fVek8H7jR79xdowluIzS4R7Druj6vb1WCaWrggXSA\nhL0alYNZjrreIMwD+Cc48hq/Kxo4Mu/yqmjLqpexzY0qrM2bgW3+uzsH7vbf3VTd977cdtGutF3M\nbZJDsvxbnrxukGgrKVHCG3vWPYlYibTT3rh1UJ6AJmltWr3HqXWO8WlAax2upXsKrZpEhv00GizC\njhxIcPTmrZI2aoJpqlbrjiZ4IB31b/ux6GC5LL9SVDpZarV4HOF8v9fls9C63NrbxHNp03VyXHQX\ncFpwfiqQy43sUj/MSktF/FBjg3W2yiAzRGHUPUDGAJWmKko1e6xeM1nX7TyKNgyowUAes8QZXnCz\ngYp30jUKw4E6iBsS1Cc+itdQglnrUGDWGgtNObyz0R10ZY2jSJVOMcHiLS1tKkoInAPcB3zTp/uA\n3+vGh7GUu29b1BvH/PRkziKy/MqnCIisxdD0TVDZZp6xUI5rEhZo1wSLuxsTzE83erfN6bMEXzfi\ntjm2xpG5+N7SXox85Wx33//GWRMO3ZsKEQL+wmuBpwO/jdv1krfeKcC3cO4W7wLe6vMvx9m+3Ql8\nCdjUiYex1PYPKGOQiS2GthPPN2bVkrW4G1tIzaq7aq5xFrFqLl/daBjIXY2WUOuDGVN6kJZ8C+yp\nNvcZcYJbs/CxWcLySUXNBNYB7wSu8eePAl6Rs0HHA0/wxyPA3cCTcA5O+nz+u4ErOvEwljryI4oM\nMq3rq+MD1IadjYNm5e13TYLefk3OCF9Z0cGGFxI2fPk1gfSdu1nl2cFfhnYlbCYLrKFaXVtJH6yz\nvbFGXXekzgAtdVdqZdzMs1nsE8B3gd/x53uAz+NMRaOo6l5grz8+JCK3Aieq6leDj/0r8Kc52rHi\nKCbmbpEM3wMveHTVmuYs4Bv3uOOseL77r4eJ11bPJ4BJ/xuafnxjfNvZx7vjvjlgsNabZ19g4XNE\n4SqprTuj1fL6ICwhAwnBXy70MQTmadwsFsZIUKXBi5z6+w4fmxBU5tig/cclWA8d566gN4jIO71l\nDjB5efi7iP9mxk6qDf5yFvCNk/w9o0Flsu5rrGBySJbb/N+bg7xbWpBQpwG7gXV1+dcDf9IJibac\nEl3o3iGrTbFysq1PIhZAMZVOursJV74u4Y18nbqy9H0A/toJdSsLw1nO54amExZ/K6EcE9q8IWhz\nTK2W2ccZ8ZaTVT5tfrepi+C19Veetc1yS62Mm3kuuhO3JnCzP/+NZoUAThX0Q+CVdfl/DXwu7WGA\nS4M0XnYHd/bL6r4NK+04n8uhDoronNMXf2O+gXzd2ECe4XUz5sgtrgePBX0ncxE8PdhNvJ+y+jiP\nyqd5Hz6u7NkKx/n07Lr7dt8LTa8kYLxunNRmr5FHHfTfgf8XOFlEPoabb/7XHPUAEJEB4HPAp1T1\nC0H+ecDLcE5XElHVS/Pex1gaNHVjz+KmxnCLi4Efm/2XwcQ4RwPATMxVN+g89HF402ur6pFbgamP\nu+NpnG+gGnVPcN+Yj5+F+2jwO7RwX3AyA0cCVdMRgovvSgiXuaumakO7Knu62Anzc3Clf9b5OZdX\nYWpvY7Cbih+ldsiKI9wOb6B249zmoMxiBpSFqu4AdlTOReQdrVwkJmX6gFfjFnj/D59OaEJKCfAx\n6hZ+gRcDdwDHROo2LdGWUyLH2xNLvp0+bkvuP5Niypm+aFytl2bPz9kwuhDUXeCoKqKiYtLgDTX0\nBDo02+jeYWi2es/YG/nQLhjU6mayQa0u0I7tS1Bf7avW3Tib8Dbv75tlbtmaGWjWb6a8ut03q+3V\n1Mq4meeiLe8OBp4DLOJCHd3s00twb1S7g7wPd+JhlluKDfJ5hEQx7Un3Gx8bVLN2nMb05PFBMUul\n03+gUbj0H6heNxZXNxaTd3g2Qb8ebDSL7TFoz+Fa9u8i/cUgrbwdVV83/lYtpf4Pa9N1clz03TjH\nJqcAY5XUjQ+zklKRb1fpA0W6R07fptS34/YCwkft2xOif4U7dzcmmIhWFpWzBFOsTVmeQEcWG/uq\n4nwuUze/fant7ot+W88STpaWJrUybuZZE/gvuEXaibr803PUNbqMuC/1gTManYhdeEb1eDbBP/+s\n13vHApUDHH4A3nRird5/3jsinNkNW4L1gy0+D2B+AQ72Vc08DwIsBA1chDNXVdt0rc8DmH4IJjbV\n+eZ/KKibEKS+sqAQiyEMMDcLi8F6wjSw4BcFsnTzY69IiOf7ioQbdpBinaZpl8UMMJogh2QZArYC\nX8Ht7n07zoSi6yTaSkq0t2ko1YdPhpVOqjsDVx7b6Zq+4cuVx1QvsfWCkYWEN+7Qh8+/J9T9d1eW\ntU4R2/y2OiFewOpgFjG8M8G3UE5zzLgJabG/KXtbX8mplXEzz0W/BPwvnFXQC4H/CXypGx9mpaVW\n/mnJXAyNCYGsYOQx3X16rF9XHlO9DO90Hj7HfBoIBtQstcxAgpO4gYpKJ8NePxroJrWs+t1EHbJF\ndOhxR3yWLLWaihICt+fJ64aHsaRk68HTBy83kNdb2oQDeTSKV8aAG7ONjw3k6xN0/utzbvjakGBZ\ntGG6ti9as4jxn4l6TY18R1EBY8lSq6mVcTPPmsCPROQZqvoDABF5OvCjHPWMrqUfeKM/Dpd6+n8G\nf/7UIIALcPXPquU62hj8RX0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lkJtrmc24aSsBowL1YGZaemJx6CLAhSeWtysw0RU4HKUr3DbLGbzTuCRwV/vr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\n", 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gB1a/A+eW6szfDdxyrr9tF5UulCGf+5jQDu24hW96tV4lDA894gkzEbg/VSoU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\nuzx+5oGV8uxTwAmeOg+dA05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HdwQofJCI77iI7IC+K0ruhcNXiAiqemW8r76Cw4vG4fqYDHfsqltbcISLcPT1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\nWa0ho1VLsAM1uft1ILF7t3e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lnjmzt7jvP2blNpunoH+wpIrpBeam3R8aqt1Xltj+/R4IiYPCmgeApYQ2Q0uw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\nSB40AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top Coefficients for 18-24\n", "pos:10671602 (59) 18927441 (57) 29758446 (57) 14922225 (49) 36803580 (48) 24742040 (48) 15234657 (45) 39538010 (41) 10228272 (41) 7157132 (40)\n", "neg:428333 (-78) 51241574 (-68) 1367531 (-68) 3108351 (-61) 30313925 (-58) 2467791 (-54) 28785486 (-52) 759251 (-50) 14173315 (-49) 15012486 (-49)\n", "Top Coefficients for 25-34\n", "pos:6480682 (74) 22027186 (67) 31080039 (60) 23544596 (59) 1344951 (53) 14089195 (51) 169686021 (49) 972651 (48) 16303106 (48) 30364057 (46)\n", "neg:1367531 (-1.2e+02) 428333 (-1e+02) 28785486 (-77) 15012486 (-72) 759251 (-72) 51241574 (-70) 30313925 (-63) 14173315 (-63) 6017542 (-59) 15754281 (-59)\n", "Top Coefficients for 35-44\n", "pos:16331010 (26) 19397785 (20) 813286 (18) 15224867 (17) 428333 (17) 23832022 (16) 19697415 (16) 248900032 (16) 23151437 (16) 58598187 (16)\n", "neg:10671602 (-32) 36803580 (-31) 29758446 (-31) 18927441 (-30) 5162861 (-30) 14922225 (-30) 24742040 (-27) 10228272 (-27) 15234657 (-25) 7157132 (-24)\n", "Top Coefficients for 45-54\n", "pos:428333 (83) 1367531 (80) 51241574 (61) 759251 (59) 28785486 (57) 15012486 (53) 3108351 (52) 30313925 (51) 14173315 (49) 14920785 (47)\n", "neg:18927441 (-46) 10671602 (-45) 29758446 (-41) 6480682 (-39) 169686021 (-38) 22027186 (-38) 24742040 (-35) 14922225 (-35) 15234657 (-35) 36803580 (-33)\n", "Top Coefficients for 55-64\n", "pos:1367531 (83) 428333 (74) 51241574 (66) 3108351 (59) 30313925 (58) 28785486 (57) 759251 (54) 15012486 (54) 2467791 (52) 14173315 (50)\n", "neg:18927441 (-44) 10671602 (-43) 29758446 (-40) 169686021 (-39) 24742040 (-37) 6480682 (-36) 27195114 (-36) 15234657 (-35) 14922225 (-34) 23561980 (-34)\n", "Top Coefficients for 65+\n", "pos:1367531 (47) 428333 (36) 3108351 (35) 51241574 (34) 14669951 (29) 28785486 (29) 30313925 (28) 2467791 (28) 759251 (28) 15012486 (28)\n", "neg:169686021 (-21) 6480682 (-20) 18927441 (-19) 27195114 (-18) 22027186 (-18) 10671602 (-17) 90420314 (-17) 23151437 (-17) 1344951 (-17) 23561980 (-16)\n", "predicting ['$0-50k', '$50-100k', '$100-150k', '$150k+'] for 1043 brands\n" ] }, { "data": { "image/png": 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SXkXgcgUkwkafDltPg+vin7k93pJmNtw2VlhEE+PthWMReV81jdRTP/Vs4MfAPbjBfhAY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\nrFT8jDOGFqg4/MCs855JeqeUEE7bnM1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CJ57TwmLf22HvN2CdVxHtnYPZt2f70unsPTW0/TAMEwJGc4nNBlaZlWcFQjic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\niaohNr3hM9fDSCI94wgwdn3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eEzUwg+6n8pGKEF4E+nUz3W5LSfHYgZGozmeG9KDtr056JHmIy+XAZwIKIHdZ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\n0c40XAGIyBrgHcALVPV5wBxwWaPlqCc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tumxjP4mEy4TFAjKWjJpsAqvqp4BPAYjIFpyOo4ioPM+Iqo4sRd+qSXpP4Ak8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\nLlRzPGzz7lB45TNgpg3ySbJ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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Top Coefficients for $0-50k\n", "pos:10228272 (1.3e+02) 10671602 (1.2e+02) 18927441 (1.1e+02) 29758446 (1.1e+02) 23151437 (93) 24742040 (91) 14922225 (91) 27195114 (89) 15234657 (88) 36803580 (87)\n", "neg:3108351 (-1.8e+02) 807095 (-1.3e+02) 5988062 (-1.2e+02) 2467791 (-1.2e+02) 91478624 (-1.1e+02) 51241574 (-1.1e+02) 34713362 (-1e+02) 51263592 (-98) 428333 (-95) 2557521 (-90)\n", "Top Coefficients for $50-100k\n", "pos:428333 (56) 2557521 (46) 26257166 (44) 51241574 (44) 3108351 (43) 120943272 (43) 15485441 (43) 51263592 (40) 21324258 (40) 807095 (40)\n", "neg:10671602 (-55) 18927441 (-52) 29758446 (-52) 10228272 (-47) 14922225 (-45) 24742040 (-43) 15234657 (-43) 36803580 (-42) 27195114 (-40) 7157132 (-37)\n", "Top Coefficients for $100-150k\n", "pos:3108351 (67) 5988062 (49) 807095 (48) 2467791 (43) 91478624 (43) 34713362 (39) 51241574 (36) 51263592 (36) 14800270 (36) 816653 (34)\n", "neg:10228272 (-45) 10671602 (-37) 18927441 (-34) 29758446 (-33) 23151437 (-32) 27195114 (-29) 24742040 (-28) 21447363 (-28) 14922225 (-28) 180505807 (-27)\n", "Top Coefficients for $150k+\n", "pos:3108351 (68) 5988062 (53) 807095 (48) 91478624 (45) 34713362 (44) 14677919 (41) 2467791 (40) 14800270 (40) 816653 (36) 2735591 (34)\n", "neg:10228272 (-37) 15846407 (-34) 23151437 (-29) 180505807 (-28) 21447363 (-26) 10671602 (-25) 17919972 (-24) 18927441 (-23) 29758446 (-22) 28706024 (-22)\n", "average correlation= 0.772615670626\n" ] } ], "source": [ "# Do cross-fold validation for different demographics.\n", "from scipy.stats import pearsonr\n", "from sklearn.cross_validation import KFold\n", "from sklearn.feature_selection import f_regression\n", "from sklearn.linear_model import ElasticNet, Lasso, MultiTaskElasticNet, MultiTaskElasticNetCV, Ridge, RidgeCV\n", "from sklearn.metrics import mean_squared_error\n", "\n", "feats = npa(vec.get_feature_names())\n", "\n", "def plot_scatter(preds, truths, ylabels):\n", " for yi, ylabel in enumerate(ylabels):\n", " pr = [p[yi] for p in preds]\n", " tr = [t[yi] for t in truths]\n", " plt.figure()\n", " plt.scatter(tr, pr)\n", " plt.xlabel('truth')\n", " plt.ylabel('pred')\n", " corr = pearsonr(pr, tr)\n", " plt.title('%s r=%.2f (%.2g)' % (ylabel, corr[0], corr[1]))\n", " plt.show()\n", " \n", "def print_top_feats(m, feature_names, labels, n=10):\n", " for yi, ylabel in enumerate(labels):\n", " print('Top Coefficients for', ylabel)\n", " coef = m.coef_[yi]\n", " srted = np.argsort(coef)\n", " topi = srted[::-1][:n]\n", " boti = srted[:n]\n", " print('pos:' + ' '.join('%s (%.2g)' % (n, c) for n, c in zip(feature_names[topi], coef[topi])))\n", " print('neg:' + ' '.join('%s (%.2g)' % (n, c) for n, c in zip(feature_names[boti], coef[boti])))\n", "\n", "def get_yvalues(ylabels, demo):\n", " return npa([float(demo[yl][:-1]) for yl in ylabels])\n", "\n", "def get_correlations(preds, truths, ylabels):\n", " results = []\n", " for i, y in enumerate(ylabels):\n", " pr = [p[i] for p in preds]\n", " tr = [t[i] for t in truths]\n", " results.append(pearsonr(pr, tr)[0])\n", " return results\n", "\n", "correlations = []\n", "category_results = {}\n", "outputs = {'Education': ['No College', 'College', 'Grad School'],\n", " 'Children': ['No Kids', 'Has Kids'],\n", " 'Income': ['$0-50k', '$50-100k', '$100-150k', '$150k+'],\n", " 'Gender': ['Male', 'Female'],\n", " 'Age': ['18-24', '25-34', '35-44', '45-54', '55-64', '65+'],\n", " 'Ethnicity': ['Caucasian', 'Hispanic', 'African American', 'Asian']}\n", "\n", "def get_model():\n", " # return Ridge(.1)\n", " # return ElasticNet(alpha=1e-5, l1_ratio=0.5)\n", " return MultiTaskElasticNet(alpha=1e-5, l1_ratio=0.5)\n", " \n", "# Labels grouped together for use by MultiTaskElasticNet.\n", "for category, ylabels in outputs.items():\n", " indices = [i for i, bid in enumerate(brand_ids) if len(set(ylabels) & set(id2brand[bid]['demo'].keys())) == len(ylabels)]\n", " print('predicting', ylabels, 'for', len(indices), 'brands')\n", " y = npa([get_yvalues(ylabels, id2brand[brand_ids[bid]]['demo']) for bid in indices])\n", " thisX = X[indices].toarray()\n", " cv = KFold(len(y), 5, shuffle=True, random_state=123456)\n", " preds = []\n", " truths = []\n", " for train, test in cv:\n", " m = get_model()\n", " m.fit(thisX[train], y[train])\n", " pred = m.predict(thisX[test])\n", " preds.extend(pred)\n", " truths.extend(y[test])\n", " m = get_model()\n", " m.fit(thisX, y)\n", " category_results[category] = {'preds': preds, 'truths': truths, 'model': m}\n", " plot_scatter(preds, truths, ylabels)\n", " print_top_feats(m, feats, ylabels)\n", " correlations.append(np.mean(get_correlations(preds, truths, ylabels)))\n", "print('average correlation=', np.mean(correlations))" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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Liuda/Rv9r7FyDudPBTbJ0kfHx2JLQWwf9jfEFhVetdW/0f8aL+ta9RbrSOL0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\ns5Ced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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot scatters.\n", "import math\n", "from matplotlib import lines\n", "\n", "def nrmsd(truths, preds):\n", " \"\"\" Normalized root mean squared deviation. \"\"\"\n", " return rmsd(truths, preds) / (max(truths) - min(truths))\n", "\n", "def rmsd(truths, preds):\n", " \"\"\" Normalized root mean squared deviation. \"\"\"\n", " return math.sqrt(mean_squared_error(preds, truths))\n", "\n", "def plot_scatter_subfig(axis, category, yidx):\n", " results = category_results[category]\n", " name = outputs[category][yidx]\n", " preds = [p[yidx] for p in results['preds']]\n", " truths = [p[yidx] for p in results['truths']]\n", "\n", " fit = np.polyfit(truths, preds, 1)\n", " fit_fn = np.poly1d(fit)\n", " axis.plot(truths, preds, 'o', truths, fit_fn(truths), 'k', linewidth=1.5,\n", " ms=2, markerfacecolor='None', markeredgecolor='b')\n", " axis.set_title('%s\\n$r=%.2f$' % (name, pearsonr(preds, truths)[0]), size=14)\n", " axis.locator_params(nbins=4, tight=True) \n", " mean = np.mean(truths)\n", " start, end = axis.get_xlim()\n", " \n", "def make_scatters_fig():\n", " figure, axes = plt.subplots(3, 7, figsize=(15,8))\n", " # Row 1\n", " plot_scatter_subfig(axes[0][0], 'Education', 0)\n", " plot_scatter_subfig(axes[0][1], 'Education', 1)\n", " plot_scatter_subfig(axes[0][2], 'Education', 2)\n", " plot_scatter_subfig(axes[0][3], 'Income', 0)\n", " plot_scatter_subfig(axes[0][4], 'Income', 1)\n", " plot_scatter_subfig(axes[0][5], 'Income', 2)\n", " plot_scatter_subfig(axes[0][6], 'Income', 3)\n", " # Row 2\n", " for i in range(6):\n", " plot_scatter_subfig(axes[1][i], 'Age', i) \n", " # Row 3\n", " for i in range(4):\n", " plot_scatter_subfig(axes[2][i], 'Ethnicity', i) \n", " plot_scatter_subfig(axes[2][4], 'Gender', 0) \n", " plot_scatter_subfig(axes[2][5], 'Children', 0) \n", " # Now add titles.\n", " axes[1, 6].axis('off')\n", " axes[2, 6].axis('off')\n", " axes[0, 1].text(.5, 1.35, 'Education',\n", " verticalalignment='bottom', horizontalalignment='center',\n", " color='black', fontsize=18, weight='bold', transform=axes[0, 1].transAxes)\n", " axes[0, 4].text(1.1, 1.35, 'Income',\n", " verticalalignment='bottom', horizontalalignment='center',\n", " color='black', fontsize=18, weight='bold', transform=axes[0, 4].transAxes)\n", " axes[1, 2].text(1.1, 1.3, 'Age',\n", " verticalalignment='bottom', horizontalalignment='center',\n", " color='black', fontsize=18, weight='bold', transform=axes[1, 2].transAxes)\n", " axes[2, 1].text(1.1, 1.32, 'Ethnicity',\n", " verticalalignment='bottom', horizontalalignment='center',\n", " color='black', fontsize=18, weight='bold', transform=axes[2, 1].transAxes)\n", " axes[2, 4].text(.5, 1.32, 'Gender',\n", " verticalalignment='bottom', horizontalalignment='center',\n", " color='black', fontsize=18, weight='bold', transform=axes[2, 4].transAxes)\n", " axes[2, 5].text(.5, 1.32, 'Family',\n", " verticalalignment='bottom', horizontalalignment='center',\n", " color='black', fontsize=18, weight='bold', transform=axes[2, 5].transAxes)\n", "\n", " axes[1][0].set_ylabel('Predicted Value (%)', size=18)\n", " plt.subplots_adjust(hspace=.7) \n", " plt.figtext(0.5,.08,\"True Value (%)\",fontdict={'fontsize':18}, verticalalignment='top', horizontalalignment='center')\n", " plt.savefig('scatters.pdf', bbox_inches='tight')\n", "\n", "make_scatters_fig()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Print the top features.\n", "from collections import defaultdict\n", "from twutil import collect\n", "\n", "def get_top_user_ids():\n", " id_list = []\n", " top_user_ids = defaultdict(lambda: defaultdict(lambda: []))\n", " for category in category_results:\n", " results = category_results[category]\n", " coef = results['model'].coef_\n", " for yi, ylabel in enumerate(outputs[category]):\n", " topi = np.argsort(coef[yi])[::-1][:5]\n", " print(category, ylabel, ' '.join('%d' % x for x in feats[topi]))\n", " id_list.extend(feats[topi])\n", " top_user_ids[category][ylabel] = feats[topi]\n", " return top_user_ids, id_list\n", "\n", "def get_top_user_names():\n", " top_user_ids, id_list = get_top_user_ids()\n", " user_names = collect.lookup_handles(id_list)\n", " id2user = dict([(int(x[1]), x[0]) for x in user_names])\n", " for category in top_user_ids:\n", " for label in top_user_ids[category]:\n", " top_user_ids[category][label] = [id2user[x] for x in top_user_ids[category][label] if x in id2user]\n", " return top_user_ids\n", "\n", "top_users = get_top_user_names()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import re\n", "\n", "def list2row(mylist, fmt='%s'):\n", " return ' & '.join([fmt % i for i in mylist])\n", "\n", "def verb(s, delim=';'):\n", " return '\\\\verb' + delim + s + delim\n", "\n", "def clean(s):\n", " return re.sub('_', '\\\\_', re.sub('\\$', '\\\\$', s))\n", "\n", "def make_user_table(top_users):\n", " outf = open('users.tex', 'wt')\n", " outf.write('\\\\begin{table*}[t]\\n\\\\centering\\n\\\\begin{tabular}{|c|c|l|}\\n\\\\hline\\n')\n", " outf.write(list2row(['{\\\\bf Category}', '{\\\\bf Value}', '{\\\\bf Top Accounts}']) +\n", " '\\\\\\\\\\n\\\\hline\\n')\n", " for ci, category in enumerate(outputs):\n", " for li, label in enumerate(outputs[category]):\n", " row = [''] * 3\n", " row[0] = category if li == 0 else ''\n", " row[1] = clean(label)\n", " row[2] = ', '.join(clean(x) for x in top_users[category][label])\n", " outf.write(list2row(row) + '\\\\\\\\\\n')\n", " outf.write('\\\\hline\\n')\n", " outf.write('\\\\end{tabular}\\\\caption{Accounts with the highest estimated coefficients for each category.\\\\label{tab.users}}\\n\\\\end{table*}\\n')\n", "\n", "make_user_table(top_users)\n", " " ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\\begin{table*}[t]\r\n", "\\centering\r\n", "\\begin{tabular}{|c|c|l|}\r\n", "\\hline\r\n", "{\\bf Category} & {\\bf Value} & {\\bf Top Accounts}\\\\\r\n", "\\hline\r\n", "Gender & Male & AdamSchefter, SportsCenter, espn, WIRED, mortreport\\\\\r\n", " & Female & TheEllenShow, Oprah, MarthaStewart, Pinterest, FoodNetwork\\\\\r\n", "\\hline\r\n", "Age & 18-24 & PlayStation, IGN, RockstarGames, Ubisoft, steam\\_games\\\\\r\n", " & 25-34 & azizansari, lenadunham, mindykaling, WIRED\\\\\r\n", " & 35-44 & TMZ, Oprah, BarackObama, andersoncooper, cnnbrk\\\\\r\n", " & 45-54 & cnnbrk, FoxNews, AP, CNN, ABC\\\\\r\n", " & 55-64 & FoxNews, cnnbrk, AP, WSJ, WhiteHouse\\\\\r\n", " & 65+ & FoxNews, cnnbrk, WSJ, AP, DRUDGE\\_REPORT\\\\\r\n", "\\hline\r\n", "Income & \\$0-50k & YouTube, PlayStation, IGN, RockstarGames, KevinHart4real\\\\\r\n", " & \\$50-100k & cnnbrk, espn, SportsCenter, AP, WSJ\\\\\r\n", " & \\$100-150k & WSJ, TheEconomist, nytimes, washingtonpost, Forbes\\\\\r\n", " & \\$150k+ & WSJ, TheEconomist, nytimes, Forbes, business\\\\\r\n", "\\hline\r\n", "Education & No College & YouTube, PlayStation, RockstarGames, katyperry, KevinHart4real\\\\\r\n", " & College & ConanOBrien, danieltosh, azizansari, WIRED\\\\\r\n", " & Grad School & NewYorker, nytimes, TheEconomist, WSJ, washingtonpost\\\\\r\n", "\\hline\r\n", "Children & No Kids & NewYorker, StephenAtHome, nytimes, TheEconomist, WIRED\\\\\r\n", " & Has Kids & parentsmagazine, parenting, TheEllenShow, thepioneerwoman, HuffPostParents\\\\\r\n", "\\hline\r\n", "Ethnicity & Caucasian & FoxNews, jimmyfallon, TheEllenShow, blakeshelton, cnnbrk\\\\\r\n", " & Hispanic & latimes, Lakers, SFGate, kobebryant, SFist\\\\\r\n", " & African American & KevinHart4real, Drake, iamdiddy, Tip, kendricklamar\\\\\r\n", " & Asian & SFGate, SFist, TechCrunch, WIRED, SFWeekly\\\\\r\n", "\\hline\r\n", "\\end{tabular}\\caption{Accounts with the highest estimated coefficients for each category.\\label{tab.users}}\r\n", "\\end{table*}\r\n" ] } ], "source": [ "!cat users.tex" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Comparison with supervised learning (logistic regression)**\n", "\n", "We manually labeled individual Twitter users with race/gender to compare accuracy of the model trained above. For comparison, we also train a supervised logistic regression classifier, which uses the same feature vector as our model.\n", "\n", "Because the labeled data contains personally identifiable information, we have elected not to share it publicly. Please contact the authors to discuss possible data sharing agreements." ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "X_race shape= (615, 46649) total matches= 17366.0\n", "training race model on 1035 brands\n", "acc= 0.614634146341 f1= 0.609443159441\n", "[[128 108 29]\n", " [ 34 86 9]\n", " [ 36 21 164]]\n", "acc= 0.544715447154 f1= 0.449208508549\n", "[[209 6 50]\n", " [ 88 13 28]\n", " [106 2 113]]\n", "acc= 0.582113821138 f1= 0.547361314201\n", "[[172 25 68]\n", " [ 59 41 29]\n", " [ 70 6 145]]\n", "acc= 0.634146341463 f1= 0.563982946188\n", "[[237 3 25]\n", " [ 82 29 18]\n", " [ 94 3 124]]\n", "acc= 0.658536585366 f1= 0.587987412216\n", "[[233 5 27]\n", " [ 78 30 21]\n", " [ 75 4 142]]\n", "acc= 0.671544715447 f1= 0.636219535313\n", "[[215 12 38]\n", " [ 63 49 17]\n", " [ 67 5 149]]\n", "acc= 0.673170731707 f1= 0.632460829646\n", "[[237 6 22]\n", " [ 74 46 9]\n", " [ 86 4 131]]\n", "acc= 0.692682926829 f1= 0.646355937889\n", "[[224 6 35]\n", " [ 63 45 21]\n", " [ 56 8 157]]\n", "acc= 0.70243902439 f1= 0.662444780879\n", "[[233 11 21]\n", " [ 67 49 13]\n", " [ 68 3 150]]\n", "acc= 0.705691056911 f1= 0.668858591958\n", "[[226 9 30]\n", " [ 65 51 13]\n", " [ 59 5 157]]\n", "acc= 0.713821138211 f1= 0.682798607784\n", "[[225 10 30]\n", " [ 59 56 14]\n", " [ 58 5 158]]\n" ] } ], "source": [ "# Compute accuracy on users labeled by race.\n", "from collections import Counter\n", "import random\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import accuracy_score, confusion_matrix, f1_score\n", "from sklearn.utils.extmath import safe_sparse_dot\n", "\n", "def train_demo_model(ylabels):\n", " indices = [i for i, bid in enumerate(brand_ids) if len(set(ylabels) & set(id2brand[bid]['demo'].keys())) == len(ylabels)]\n", " print('training race model on', len(indices), 'brands')\n", " y = npa([get_yvalues(ylabels, id2brand[brand_ids[bid]]['demo']) for bid in indices])\n", " thisX = X[indices].toarray()\n", " m = get_model()\n", " m.fit(thisX, scale(y))\n", " m.coef_ = m.coef_[0:3]\n", " return m\n", "\n", "def map_race_label(label):\n", " return ['white', 'latin', 'black', 'asian'].index(label)\n", " \n", "def read_labeled_data(fname, label_map_f):\n", " users = []\n", " labels = []\n", " friends = []\n", " for line in open(fname):\n", " parts = line.strip().split()\n", " if len(parts) > 10:\n", " users.append(parts[0])\n", " labels.append(label_map_f(parts[1]))\n", " friends.append(Counter([int(x) for x in parts[2:]]))\n", " X_race = vec.transform(friends)\n", " return users, npa(labels), X_race\n", "\n", "def label_by_reg(X_race, m):\n", " \"\"\" Scale coefficients per class to make them comparable;\n", " then keep only positive coefficients. \"\"\"\n", " coef = m.coef_\n", " coef = scale(m.coef_, axis=0) # Scale by class label\n", " for i in range(len(coef)):\n", " topi = np.where(coef[i] > 0)\n", " topv = coef[i][topi]\n", " coef[i] = [0] * len(coef[i])\n", " coef[i][topi] = topv\n", " pred = safe_sparse_dot(coef, X_race.T, dense_output=True).T\n", " return np.argmax(pred, axis=1)\n", "\n", "def label_by_clf(X_race, y_race, pct):\n", " clf = LogisticRegression()\n", " cv = KFold(len(y_race), 3, shuffle=True, random_state=123456)\n", " preds = np.zeros(len(y_race), int)\n", " for train, test in cv:\n", " train = random.sample(set(train), int(len(train) * pct))\n", " clf.fit(X_race[train], y_race[train])\n", " preds[test] = clf.predict(X_race[test])\n", " return preds\n", "\n", "def eval_labeled(truth, pred, labels):\n", " label_idx = np.arange(len(labels))\n", " acc, f1 = (accuracy_score(pred, truth),\n", " f1_score(truth, pred, labels=label_idx,\n", " average='macro', pos_label=None))\n", " print('acc=', acc, 'f1=', f1)\n", " print(confusion_matrix(truth, pred))\n", " return f1\n", "\n", " \n", "def do_race_expt():\n", " labels = ['Caucasian', 'Hispanic', 'African American', 'Asian']\n", " users_race, y_race, X_race = read_labeled_data('../data/race.txt', map_race_label)\n", " X_race = X_race[np.where(y_race != 3)]\n", " y_race = y_race[np.where(y_race != 3)]\n", " print('X_race shape=', str(X_race.get_shape()), 'total matches=', X_race.sum())\n", " labels = labels[0:3]\n", " reg = train_demo_model(labels)\n", " pred_reg = label_by_reg(X_race, reg)\n", " reg_f1 = eval_labeled(y_race, pred_reg, labels)\n", " clf_f1s = []\n", " for pct in [.1, .2, .3, .4, .5, .6, .7, .8, .9, 1.]:\n", " pred_clf = label_by_clf(X_race, y_race, pct)\n", " clf_f1s.append(eval_labeled(y_race, pred_clf, labels))\n", " return reg_f1, clf_f1s\n", "\n", "race_results = do_race_expt()" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "X_gender shape= (213, 46649) total matches= 7516.0\n", "training race model on 1066 brands\n", "acc= 0.741784037559 f1= 0.741784037559\n", "[[79 7]\n", " [48 79]]\n", "acc= 0.643192488263 f1= 0.489015151515\n", "[[ 10 76]\n", " [ 0 127]]\n", "acc= 0.68544600939 f1= 0.654229157076\n", "[[ 41 45]\n", " [ 22 105]]\n", "acc= 0.676056338028 f1= 0.634266517357\n", "[[ 36 50]\n", " [ 19 108]]\n", "acc= 0.661971830986 f1= 0.529570552147\n", "[[ 14 72]\n", " [ 0 127]]\n", "acc= 0.732394366197 f1= 0.671020186967\n", "[[ 32 54]\n", " [ 3 124]]\n", "acc= 0.699530516432 f1= 0.61237488626\n", "[[ 24 62]\n", " [ 2 125]]\n", "acc= 0.704225352113 f1= 0.620599960417\n", "[[ 25 61]\n", " [ 2 125]]\n", "acc= 0.741784037559 f1= 0.688637873754\n", "[[ 35 51]\n", " [ 4 123]]\n", "acc= 0.741784037559 f1= 0.691491322782\n", "[[ 36 50]\n", " [ 5 122]]\n", "acc= 0.741784037559 f1= 0.68566368832\n", "[[ 34 52]\n", " [ 3 124]]\n" ] } ], "source": [ "# Compute accuracy on data labeled by gender.\n", "def map_gender_label(label):\n", " return ['Male', 'Female'].index(label)\n", "\n", "def do_gender_expt():\n", " labels = ['Male', 'Female']\n", " users_gender, y_gender, X_gender = read_labeled_data('../data/gender.txt', map_gender_label)\n", " print('X_gender shape=', str(X_gender.get_shape()), 'total matches=', X_gender.sum())\n", " \n", " reg = train_demo_model(labels)\n", " pred_reg = label_by_reg(X_gender, reg)\n", " reg_f1 = eval_labeled(y_gender, pred_reg, labels)\n", " clf_f1s = []\n", " for pct in [.1, .2, .3, .4, .5, .6, .7, .8, .9, 1.]:\n", " pred_clf = label_by_clf(X_gender, y_gender, pct)\n", " clf_f1s.append(eval_labeled(y_gender, pred_clf, labels))\n", " return reg_f1, clf_f1s\n", " \n", "gender_results = do_gender_expt()" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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DJO1qZg9LWgXYGzi1TO07TiOKUiRm1rvCcjhONZjQlonuSL6DyYL4mvwPWX49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\nmiDpxFhW1evU2nulpBGSJkoal7bWrwl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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "def plot_labeled_results(reg_results, clf_results, xticks, axis, title):\n", " axis.plot(xticks, [reg_results] * len(clf_results), 'g--', label='regression', lw=3)\n", " axis.plot(xticks, clf_results, 'bo-', label='classification')\n", " axis.set_title(title, size=16)\n", " \n", "def make_labeled_plot(gender_results, race_results):\n", " xticks = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]\n", " figure, axes = plt.subplots(2, 1, sharex=True)\n", " plot_labeled_results(gender_results[0], gender_results[1], xticks, axes[0], 'Gender')\n", " plot_labeled_results(race_results[0], race_results[1], xticks, axes[1], 'Ethnicity')\n", " axes[1].set_ylabel((' ' * 25) + 'Macro F1', size=16)\n", " axes[1].set_xlabel('% of labeled training data', size=16)\n", " axes[1].legend(loc='lower right')\n", " plt.savefig('labeled.pdf', bbox_inches='tight')\n", "\n", " \n", "make_labeled_plot(gender_results, race_results)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "training race model on 1035 brands\n", "acc= 0.549593495935 f1= 0.505811358585\n", "[[208 41 16]\n", " [ 79 42 8]\n", " [115 18 88]]\n", "acc= 0.484552845528 f1= 0.432301583071\n", "[[195 40 30]\n", " [ 83 34 12]\n", " [129 23 69]]\n", "acc= 0.526829268293 f1= 0.477198788156\n", "[[208 37 20]\n", " [ 83 38 8]\n", " [127 16 78]]\n", "acc= 0.526829268293 f1= 0.480685138828\n", "[[205 37 23]\n", " [ 80 40 9]\n", " [125 17 79]]\n", "acc= 0.551219512195 f1= 0.512479320936\n", "[[207 40 18]\n", " [ 73 47 9]\n", " [119 17 85]]\n", "acc= 0.569105691057 f1= 0.548909157785\n", "[[175 52 38]\n", " [ 62 57 10]\n", " [ 78 25 118]]\n", "acc= 0.551219512195 f1= 0.533941429648\n", "[[169 68 28]\n", " [ 65 57 7]\n", " [ 83 25 113]]\n", "acc= 0.551219512195 f1= 0.523876394573\n", "[[182 57 26]\n", " [ 68 50 11]\n", " [ 88 26 107]]\n", "acc= 0.588617886179 f1= 0.562933681604\n", "[[182 55 28]\n", " [ 62 54 13]\n", " [ 70 25 126]]\n", "acc= 0.565853658537 f1= 0.54267031674\n", "[[186 53 26]\n", " [ 60 58 11]\n", " [ 90 27 104]]\n", "acc= 0.580487804878 f1= 0.573140254929\n", "[[156 84 25]\n", " [ 50 72 7]\n", " [ 66 26 129]]\n", "acc= 0.556097560976 f1= 0.54924858256\n", "[[149 77 39]\n", " [ 50 71 8]\n", " [ 70 29 122]]\n", "acc= 0.551219512195 f1= 0.54425245045\n", "[[147 85 33]\n", " [ 52 68 9]\n", " [ 73 24 124]]\n", "acc= 0.582113821138 f1= 0.57204472865\n", "[[156 78 31]\n", " [ 46 70 13]\n", " [ 64 25 132]]\n", "acc= 0.582113821138 f1= 0.566507486488\n", "[[163 69 33]\n", " [ 53 63 13]\n", " [ 62 27 132]]\n", "acc= 0.564227642276 f1= 0.556706864314\n", "[[146 81 38]\n", " [ 44 72 13]\n", " [ 63 29 129]]\n", "acc= 0.567479674797 f1= 0.558730434447\n", "[[145 86 34]\n", " [ 48 68 13]\n", " [ 64 21 136]]\n", "acc= 0.575609756098 f1= 0.567650369551\n", "[[146 79 40]\n", " [ 43 73 13]\n", " [ 58 28 135]]\n", "acc= 0.582113821138 f1= 0.574745043925\n", "[[146 87 32]\n", " [ 46 73 10]\n", " [ 56 26 139]]\n", "acc= 0.556097560976 f1= 0.548148186031\n", "[[145 82 38]\n", " [ 46 70 13]\n", " [ 64 30 127]]\n", "acc= 0.562601626016 f1= 0.558780120436\n", "[[128 105 32]\n", " [ 44 76 9]\n", " [ 47 32 142]]\n", "acc= 0.593495934959 f1= 0.588913975552\n", "[[146 82 37]\n", " [ 36 82 11]\n", " [ 57 27 137]]\n", "acc= 0.569105691057 f1= 0.564751039131\n", "[[130 95 40]\n", " [ 38 79 12]\n", " [ 51 29 141]]\n", "acc= 0.570731707317 f1= 0.565967027687\n", "[[134 89 42]\n", " [ 41 77 11]\n", " [ 56 25 140]]\n", "acc= 0.559349593496 f1= 0.555983935743\n", "[[132 100 33]\n", " [ 43 76 10]\n", " [ 58 27 136]]\n", "acc= 0.614634146341 f1= 0.609051509763\n", "[[138 93 34]\n", " [ 32 85 12]\n", " [ 43 23 155]]\n", "acc= 0.60487804878 f1= 0.600607908736\n", "[[131 101 33]\n", " [ 35 85 9]\n", " [ 43 22 156]]\n", "acc= 0.590243902439 f1= 0.58466855929\n", "[[127 104 34]\n", " [ 39 80 10]\n", " [ 41 24 156]]\n", "acc= 0.585365853659 f1= 0.578572264727\n", "[[126 103 36]\n", " [ 39 78 12]\n", " [ 39 26 156]]\n", "acc= 0.59674796748 f1= 0.591198207477\n", "[[127 97 41]\n", " [ 38 82 9]\n", " [ 43 20 158]]\n", "acc= 0.59674796748 f1= 0.592373615708\n", "[[125 106 34]\n", " [ 36 84 9]\n", " [ 42 21 158]]\n", "acc= 0.619512195122 f1= 0.611777847779\n", "[[139 98 28]\n", " [ 38 80 11]\n", " [ 40 19 162]]\n", "acc= 0.611382113821 f1= 0.60653026428\n", "[[125 108 32]\n", " [ 34 87 8]\n", " [ 36 21 164]]\n", "acc= 0.60487804878 f1= 0.599652894678\n", "[[125 109 31]\n", " [ 34 85 10]\n", " [ 36 23 162]]\n", "acc= 0.619512195122 f1= 0.613592584096\n", "[[133 101 31]\n", " [ 35 85 9]\n", " [ 37 21 163]]\n", "acc= 0.611382113821 f1= 0.6054889627\n", "[[131 106 28]\n", " [ 36 83 10]\n", " [ 37 22 162]]\n", "acc= 0.613008130081 f1= 0.60732614356\n", "[[129 106 30]\n", " [ 34 85 10]\n", " [ 36 22 163]]\n", "acc= 0.617886178862 f1= 0.612204804148\n", "[[132 104 29]\n", " [ 35 85 9]\n", " [ 36 22 163]]\n", "acc= 0.608130081301 f1= 0.60276681954\n", "[[127 105 33]\n", " [ 35 85 9]\n", " [ 37 22 162]]\n", "acc= 0.616260162602 f1= 0.610703537681\n", "[[132 102 31]\n", " [ 35 85 9]\n", " [ 38 21 162]]\n", "acc= 0.619512195122 f1= 0.614075735647\n", "[[128 106 31]\n", " [ 34 87 8]\n", " [ 35 20 166]]\n", "acc= 0.613008130081 f1= 0.607340856051\n", "[[128 106 31]\n", " [ 35 85 9]\n", " [ 36 21 164]]\n", "acc= 0.606504065041 f1= 0.600442692337\n", "[[125 111 29]\n", " [ 36 83 10]\n", " [ 35 21 165]]\n", "acc= 0.613008130081 f1= 0.607711633099\n", "[[129 108 28]\n", " [ 35 85 9]\n", " [ 35 23 163]]\n", "acc= 0.617886178862 f1= 0.612209995337\n", "[[129 106 30]\n", " [ 34 86 9]\n", " [ 35 21 165]]\n", "acc= 0.614634146341 f1= 0.609109481551\n", "[[129 107 29]\n", " [ 35 85 9]\n", " [ 36 21 164]]\n", "acc= 0.614634146341 f1= 0.609572558737\n", "[[128 108 29]\n", " [ 35 86 8]\n", " [ 35 22 164]]\n", "acc= 0.613008130081 f1= 0.607675789795\n", "[[128 108 29]\n", " [ 35 85 9]\n", " [ 37 20 164]]\n", "acc= 0.619512195122 f1= 0.614101652566\n", "[[128 108 29]\n", " [ 33 87 9]\n", " [ 35 20 166]]\n", "acc= 0.614634146341 f1= 0.60868920084\n", "[[129 107 29]\n", " [ 36 84 9]\n", " [ 36 20 165]]\n", "training race model on 1066 brands\n", "acc= 0.516431924883 f1= 0.480524708167\n", "[[ 83 3]\n", " [100 27]]\n", "acc= 0.50234741784 f1= 0.474539191957\n", "[[78 8]\n", " [98 29]]\n", "acc= 0.50234741784 f1= 0.474539191957\n", "[[78 8]\n", " [98 29]]\n", "acc= 0.50234741784 f1= 0.479097452935\n", "[[76 10]\n", " [96 31]]\n", "acc= 0.516431924883 f1= 0.480524708167\n", "[[ 83 3]\n", " [100 27]]\n", "acc= 0.586854460094 f1= 0.572523262178\n", "[[82 4]\n", " [84 43]]\n", "acc= 0.577464788732 f1= 0.565739398333\n", "[[79 7]\n", " [83 44]]\n", "acc= 0.586854460094 f1= 0.580107526882\n", "[[76 10]\n", " [78 49]]\n", "acc= 0.544600938967 f1= 0.529630051224\n", "[[77 9]\n", " [88 39]]\n", "acc= 0.539906103286 f1= 0.529949558638\n", "[[73 13]\n", " [85 42]]\n", "acc= 0.600938967136 f1= 0.5928624435\n", "[[79 7]\n", " [78 49]]\n", "acc= 0.62441314554 f1= 0.621400639886\n", "[[76 10]\n", " [70 57]]\n", "acc= 0.633802816901 f1= 0.629482604817\n", "[[79 7]\n", " [71 56]]\n", "acc= 0.600938967136 f1= 0.5928624435\n", "[[79 7]\n", " [78 49]]\n", "acc= 0.600938967136 f1= 0.596635847165\n", "[[75 11]\n", " [74 53]]\n", "acc= 0.657276995305 f1= 0.655789963031\n", "[[77 9]\n", " [64 63]]\n", "acc= 0.633802816901 f1= 0.631977671451\n", "[[75 11]\n", " [67 60]]\n", "acc= 0.610328638498 f1= 0.603476505551\n", "[[79 7]\n", " [76 51]]\n", "acc= 0.619718309859 f1= 0.613966392947\n", "[[79 7]\n", " [74 53]]\n", "acc= 0.629107981221 f1= 0.623498086949\n", "[[80 6]\n", " [73 54]]\n", "acc= 0.647887323944 f1= 0.647389912813\n", "[[73 13]\n", " [62 65]]\n", "acc= 0.619718309859 f1= 0.618507462687\n", "[[72 14]\n", " [67 60]]\n", "acc= 0.633802816901 f1= 0.631977671451\n", "[[75 11]\n", " [67 60]]\n", "acc= 0.680751173709 f1= 0.679557522124\n", "[[79 7]\n", " [61 66]]\n", "acc= 0.676056338028 f1= 0.674218074613\n", "[[80 6]\n", " [63 64]]\n", "acc= 0.676056338028 f1= 0.674218074613\n", "[[80 6]\n", " [63 64]]\n", "acc= 0.723004694836 f1= 0.722784726358\n", "[[80 6]\n", " [53 74]]\n", "acc= 0.671361502347 f1= 0.670773714891\n", "[[76 10]\n", " [60 67]]\n", "acc= 0.727699530516 f1= 0.727645502646\n", "[[76 10]\n", " [48 79]]\n", "acc= 0.68544600939 f1= 0.684751154211\n", "[[78 8]\n", " [59 68]]\n", "acc= 0.75117370892 f1= 0.751085925959\n", "[[78 8]\n", " [45 82]]\n", "acc= 0.737089201878 f1= 0.737037037037\n", "[[80 6]\n", " [50 77]]\n", "acc= 0.723004694836 f1= 0.72290697418\n", "[[79 7]\n", " [52 75]]\n", "acc= 0.732394366197 f1= 0.732394366197\n", "[[78 8]\n", " [49 78]]\n", "acc= 0.741784037559 f1= 0.741784037559\n", "[[79 7]\n", " [48 79]]\n", "acc= 0.732394366197 f1= 0.732370770418\n", "[[79 7]\n", " [50 77]]\n", "acc= 0.723004694836 f1= 0.72290697418\n", "[[79 7]\n", " [52 75]]\n", "acc= 0.737089201878 f1= 0.737083406807\n", "[[79 7]\n", " [49 78]]\n", "acc= 0.727699530516 f1= 0.727645502646\n", "[[79 7]\n", " [51 76]]\n", "acc= 0.732394366197 f1= 0.732370770418\n", "[[79 7]\n", " [50 77]]\n", "acc= 0.746478873239 f1= 0.746473285135\n", "[[79 7]\n", " [47 80]]\n", "acc= 0.741784037559 f1= 0.741784037559\n", "[[79 7]\n", " [48 79]]\n", "acc= 0.737089201878 f1= 0.737037037037\n", "[[80 6]\n", " [50 77]]\n", "acc= 0.741784037559 f1= 0.741784037559\n", "[[79 7]\n", " [48 79]]\n", "acc= 0.741784037559 f1= 0.741784037559\n", "[[79 7]\n", " [48 79]]\n", "acc= 0.75117370892 f1= 0.751151768985\n", "[[79 7]\n", " [46 81]]\n", "acc= 0.746478873239 f1= 0.746473285135\n", "[[79 7]\n", " [47 80]]\n", "acc= 0.741784037559 f1= 0.741784037559\n", "[[79 7]\n", " [48 79]]\n", "acc= 0.746478873239 f1= 0.746473285135\n", "[[79 7]\n", " [47 80]]\n", "acc= 0.746478873239 f1= 0.746473285135\n", "[[79 7]\n", " [47 80]]\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/usr/lib64/python3.4/site-packages/matplotlib/axes/_axes.py:475: UserWarning: No labelled objects found. Use label='...' kwarg on individual plots.\n", " warnings.warn(\"No labelled objects found. \"\n" ] }, { "data": { "image/png": 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4vV9VA+Ur4cMPvSVUiVlCGUZ60NOCQSWEiNwa2J3RG3w8xUNEcqDPITDpJDipH1y4HQ5b\nA+8WwGVXuVzXvei8kjYKxXCaWz7NxAl6nJbJmmxnNrso23VDra2EHcth+Uc4cdmWrk7kDKOnIyLT\naOHjPRF6UjCo9bhur+C578Q7sbcHunGT8ooOhxOmwpnZcNFWGFfWlOPeK+G+/dz2LeNh4iKcUHyA\ns3yq3vOq9cDKPGc2uzjDDSlt3gGlC+CTqNlsuZnNGkbvwH9Uz4jui8gtyZzfY4JBAa8At4hIvt8/\nA7itk8vbrRCRIhh+DJw6Cc4VuLAEhgTHFMYCp0Px2KakjSuAe/e8Wj2wuC8s6ufMZhcCpVth07uw\nYQ3ObHZnZz6PYRg9lx4TDEpVN4nI7cB7Pum2WEur3oqzNBs3Gc45DM6vg89shoLo2IIAh+DcS/cH\nXoIL/gX/e7E7/I2H3LpaYEE/WNoX5gssFdi+AdbNg63rcGJRmepnMwyjZ2KTBLspfm7GKDjwBJgw\nHi6ohrNLICf6BwsDR+NEI4IT5Hk0DnJXC8zuD0v7uN6qFQo7zIGgYRhx6dbzPFJBTxcP77J8Xzj0\nJDhqOFy0C07eFpi0lwNMAU4BNuJEY3nTFcoy4Kli+HcGrPoQPloGNRtxllCRlD6MYRg9BhOPHioe\nIpIJGQfAxFNgygC4qByODbrqKABOwgnHEpxoBEyX12XDv4vhv/Ww7F3Y+L6qbk/lMxiG0XMx8ehh\n4iEiudDvUDj4RDitD1y4DQ7aHcgyGDgNOByYhTMc2NZ0eEkfeGIAvFwFi1+H8gWqGjzfMAxjr5h4\n9BDxEJF+MPhIOGAKnJ3hLKdGBccgvOUU44DXgTdo9BkF8HZ/eKIA3toGi1+D6qU2m9swjLZi4tHN\nxUNEBsKoY2H/o+B84LwtUBwdi4i1nHoZN5fFi0I98NIg+FcezF0HC14HVtqsbsMw2ouJRzcVDze3\nZd/jYcIhcH4Ezi2B/GilvxfLqYowPDMInsiCxUthxUxgnU3YMwyjozDx6Ebi4c1tx8JBU+GwcXBR\nFZy51Ydhhb1aTpVkwn8GO5+Ey9+HNbNUdWtqn8IwjHTAxKMbiIczt80YDxNOhklD4IIKmLo9YG4b\nazn1Es3ctHycC08MhOcisOQtKJ1rs70Nw+hMur147C0YlM8zHfi+z7NYVT/r0+txfjQA1qjqeXHO\n7VLxcCa3B34RzhkJF22HIyoCh/diOTU3H54ogtd2ukHw3YtUNY4fKsMwjI6lW4tHIsGgRORQnC+m\nk1R1t4gMUNVt/liFqubHuXTwHl0sHiPOgquPheuCDh+DllMz/OItp+qBN4rgiXyYtRkWvgZ1K1S1\ntfgbhmEYHUpvCAb1BeD30bkKUeHoCYhk7QdnnQkfTIXLgB/MgQOn0GQ5dT+NllPVAs8VwxM5sPBj\nWPwYsMoGwQ3D6Al0x2BQ44F6EbkaZ7r6I1V92h/LEZE5OKeKd6jqY51c3oQRkQKYejHknAR/OdCl\n3rQv/PLvNLOcCroPWTYfVr6tqpu6qtyGYRhtoTsGgwrhghYdg4/ZISJvqWoZMExVS0RkDPCaiCxQ\n1RWxF0h1MCg3QL7/+XCVwkt5TUc2rwTmuO112fBkMTwddR8y2z+TYRhGyumNwaDWATP9xLfVIrIU\n1xqZpaolAKq6SkRewg087yEeqQ8GNWAyXLgvXFgDkwbCVR9DTaVzh97Mfcjz5j7EMIzuQHuDQaV6\nwDwHN2B+HC4Y1DvAV1R1XiDPZ4BPq+oVbjY2C4CJuLGCSlWNiMgA4G1guqoujLlHSgfMRWQkXPBV\nuL8UCr4LvOCey9yHGIbRc+jWA+aJBINS1SdF5HgRWYIz1f2eqm4VkcnAn0WkAcgGfhsrHKlGRPJg\n0iVwQxkUXAEsg4r34MYx8OYaWPAU5j7EMIxeiE0SbPt9BMZOhx8cAF86EtgPInfB90fCAy9D6etm\nOWUYRk8h2boz1JmF6d30OwbOmQhfGAwcC/V/hp+NgMdnmXAYhtHbSfWAea9AJP9MOPZ3UK6wcR8Y\nfjf8oT88uBjWPmPCYRhGb8fEI0lE8o9wwvHUOJdyzTo4LgJ/2ggfP2HjG4ZhpAMmHkkgkn8YnHch\nBK2mSivh7h2w7BFVrWn5bMMwjN6DiUeCiORPhHOnw6/KoDofbtgGm7fCR/+GhQ/Y3A3DMNIJs7ZK\n6Jp5E+C8S+HunVD8DWAJLHgRru0Lr96rqps78n6GYRipxqytOhiRvIPh05fAXbuh+FvAB/DeK3B9\nP3j1ARMOwzDSEeu2agURGQLnXQx3VcPgbwEz4aX34fZMePPP5tDQMIx0JeUtDxE5Q0QWichSEbmh\nhTzTReQDEVkoIo8E0i8XkSV++XznljN3KBz/X8i5DOq+DbwGT8yDH0ZMOAzDSHd6QjCoIlXdLiL7\nAG/h/FwBzAeOU9UtMffokDEPkWnPw/NnuL3vbICj/gK/LYUFD1pIWMMwehvdfcyjMRiUj5QXDQYV\nJDYY1HaffirwvKruUtVdOAeEp3ZeUev7Nm1vrIJfroMFfzXhMAzDSL14xAsGNTwmz3hgoojMEZG5\nInKuTx/m87d2bofg/FbteAVujsDl62DuXbDsIVWt7Iz7GYZh9DR6SjComcncpAOCQY2E7+0H55fC\noT+EDY9YTHHDMHoT6RQMaj1OUILnvhPvJu0PBrXvUXDmBJi7AD58x4TDMIzeRnuDQaW62+p94GAR\nGSYimcB04PmYPM/i1dAHgzoAWAm8CpwhIvkikg+cAbzS0QV0155yDPQfB3fPAVZ39D0MwzB6Oj0m\nGBSAiNwOvOcvd1uspVXH0O9guGYClK6Et9+wVodhGMaemHuS5ueG4Jjr4O1vwwOvwpe+a/M5DMNI\nB7q7qW53Zwx8dX8gC+6dC5jrEcMwjDiYeDRj/0lw7sHw0UJY/I4FdTIMw4iPiYdHRArhiAlQeBD8\nYRHsXtHVZTIMw+iumHg0UnQIXL8/VK6FGXNVdUdXl8gwDKO7YuIBiEgG7H8cHHQwvL0IFr/f1WUy\nDMPozph4OPaFK0ZBeCD8ahnwSVcXyDAMoztj4gHAIcfCBfvD5kWwYo7FIjcMw2idtBcP5yZ+5L5Q\neBj8cxGsWdDVZTIMw+judLtgUCJyhYhs9cGgPhCRLwWO1QfS/9MxJco4BPK/ANdmwP3baO651zAM\nw4hDdwwGdTlwhKp+K875Faqav5d7JDVLUuT4mfDycW7vtHdV35qc6LmGYRi9he4+wzyRYFDilxSR\n1a9pO7Qrdfc1DMPouXTHYFAKnO/jlD8tIqMCx3J8kKh5IjK9vYVxvqwmLYcfVMHpi2D2Fe29pmEY\nRjrQHYNBPQ08rKp1frzjYVw3F8AwVS0RkTHAayKyQFX3mAmeRDCogXDBUMibAxOuUo1sTPxRDMMw\nei69LhiUqpYFtu8XkbsD+yV+vUpEXgIOB/YQjySCQQ2GfUfD/70GdSsTfQjDMIyeTq8LBiUigwLb\n5wAf+e0Cfw4iMgCYCixpX3FOOxj6FsN/3rH45IZhGInT7YJBAdeKyFm4QFBlwOf86QcC94pIA5AN\n/FZVF7avROedAmWbYM689l3HMAwjvUjbYFAi0g9mvwh1NTD54s6JSmgYhtEz6O6mut2JwTBuDMxY\nDpR0dWEMwzB6EmksHmceAPlF8NjzFvTJMAwjOdotHiJypoj0QC+0F50JmzfB/KVdXRLDMIyeRke0\nPPoAozvgOilDRLLgoMNh+ceYLyvDMIykadHaSkSmktikvgM7rjgpYzCMHQf3/llVq7q6MIZhGD2N\n1kx1X0/iOj1szOCCAyC/H9zzDPygqwtjGIbR42hNPHYBLwF/2ss1pgA3dViJUsL5n4L1G2B9Dxyr\nMQzD6HpaE495QD9VfaW1C4hI/44tUufinCHOngxLV2AmuoZhGG2itQHzOcARCVxjN7Am0Ru2IRjU\nFwPHLvfedpeIyOcTvWcMA2DcOFj0nJnoGoZhtI0WZ5iLSF9goKqu7rCbtSMYlIjsA7wFTPRJ84Hj\nYmeG722WpMiXpsEfXoDhh6qW7uFU0TAMIx3psBnmqrqrI4XD055gUKcCz/ty7QJe8GlJ8qlzYO1a\n2LY2+XMNwzAMaEU8RGSsmw/RobQnGNQwms/JiHduAow6AZYuMhNdwzCMttPagPlKYBIwG0BEBHgA\nuElVEx7jiKG9waASoqVgUK4rrmxfePHXcF4ylzQMw+hVpDIYVBi4DLibJAbIY2hPMKj1uG6v4Lnv\nxLtJy8Ggvj8RsrPhrtdtfodhGOlM2gSDAl4FzhCRfBHJB84AWjUj3pOjPwOrV0GpuV83DMNoBz0m\nGJSqbhSR24H3/OVuSz4Gx6ipsHyumegahmG0j9ZMdRuA42iqrDOAalzX0dzY/Kra0EllTIqWzM1E\nDsqEd7fCny9Vvf75eOcahmGkK8ma6u5NPBJFVTWcRP5OI94LEMkdClP/BQcfBX8ar7rL3JIYhmEE\nSFY8Wuu2ui2J+3bzbqBJ98KTx7rtub8Fzu7S4hiGYfRwWhSPli2WDMMwjHSnxW6rnkrL3VbH/BWk\nAWZdqVq1savKZxiG0R3psDGPnkqyL8AwDMPoQN9WhmEYhtESJh6GYRhG0ph4GIZhGEnTJeKxt4BQ\ngXwXiEiDiBzu90eLSFUgUNQfU1fqnod3fGZg7yKIvYsm7F20nYTFQ0SGisivRGSOiHwsIu+LyC9E\nZEgyN/QBoe7B+aaaAFwoIofFyZcPXA3Mijm0UlUP88vXk7l3GjKtqwvQjZjW1QXoRkzr6gJ0I6Z1\ndQF6KgmJh4jsh4vc93VgGy4CYBlwFbBARP4niXsmEhAK4MfAHUAN8YNDGYZhGF1Eoi2PO4ESYF9V\nPV1VL1PV04BxPv3nSdxzrwGhfDfVMFV9zicF7YlHi8h8EXlHRE5K4r6GYRhGR6Gqe12AcuD8Fo59\nBihP5Do+/6XAPYH9S4A/BfZDOB/zo/z+67iY5gBZQD+/fRiwAegfc321xRZbbLEl+SXRelxVE3bJ\nngXsbOHYLn88UfYWECofOAiY4YIXMgR4WkTOUdV5QC2Aqn4gIouB/QmMi9gEQcMwjM4n0W6rBcA3\nfSjaRvz+13DjIYnSakAoVd2hqoNUdYyqjsEJwzk+7keRiIT8vUcDB+PC5RqGYRgpJNGWx4+AZ4H5\nIvIYbpyjGLgIV4HHG/COS4IBoVriROBH3l28AN9S1dJE720YhmF0DAn7thKRM4Cf4MYaBNdHNhe4\nSVVf7LQSGkY7EZErgL+2cLhcVYu8vf9UXIRKDZw7GvgE+F9Vvb+DyvM3YKpvWSd6zhW4Zxitqmt9\n2q3AG6r6ekeUyzCSYa8tD9+1dBawUFWPFJE+QCFQpqq7O7uAhtGBXIgbcwtS59fTgJtxJuLxvqgS\n+8pKjNtwY3vJ8AwwCdgcSLsZ90Fn4mGknES6reqAx4FTgFVeMEw0jJ7IfFXdWxTJTje4SKAM8c4p\nBeJ10ZqBiNEl7HXA3DfhP8G1Ngyj1+G7f272uxHvEic2DHOGiNwmIhu9i5xXRGRMzHVWi8hDInKJ\niCwTkWoRWSwip8bk+5uIrIpJ6yMid3jvDTUiUioi/xWRYn/8Cl+ukX4/Wr4bo+UVkVtE5Fp/34Ex\n1xcR+UREHm3XyzIMT6LWVj8HfigiJiBGTyZDRGKXEHAfEB3POA7XPTQp5tzvA0OBzwJXAIfgvCME\nUWAKzhPDdcC5OFP2f0dFICYvACKSBbwMfAX4I3Cyv8cqoKCFZ/Fhlfm/QHnvw42LNABfiMl/GjAa\n5xrIMNpNotZWJwL7AKtF5C1ge2wGVf18RxbMMDqB5XHSnlHVc0Vkg99/T1VjWx0AK1T1yuiOF4Pf\niMgoVV0TTQbygDOj44Eisgln6n4W8LfA9YLdTZfhKv9TVfXVYNlaehBVfc9bzm9Q1dnBYyLyT+DL\nwC8CyV8Blqnqmy1d0zCSIVHxmAJEcP6sDqb54KHQsYOJhtFZnMeeA+blCZ77bMz+Ur8eBqwJpL8V\nY0gSzTe0lWufBqyOEY728EfgchE5WVVfFZF9gLOB6zvo+oaRmHio6uhOLodhpILFbRms9sQaidT7\ndfA3pLH5VLXetxBa+60NoLkVVbtQ1fdFZC7wVeBV4Ercx98DHXUPw7BgUIbR9ZTiuoU7knuAT4vI\nUJx4PK4GdzQ/AAAgAElEQVSqibayDGOvJOqS/csicmMLx34oIl/q2GIZRsqp8evsFN0v2NX7IjCq\nDV6ia2nZr9yjuMH6R3H+4/6UdAkNoxUSbXlcTZxBcs9Wf9wwujuHicikOEsYWOLzXCMiR4nIkW24\nfjJzLoJ5/46LkfMvEfmOiEwRkU+JyG98LJ2WWAqcLSLTRORIP7YBgKpW4Qbop+Am+MYGVTOMdpHo\ngPm+wKIWji0FWvsHN4yuJvqV/3gLxwbhLJv+iPsQ+rE/Fk7wui3tt3ZeY15VrROR04BbgG/hBtd3\nADNp/tEWe/2rgN/iHItmA7fiZq9H+RfwbeDPCZbLMBImId9WIlIOfC6e00IRORt4VFUTdrfg/WT9\nAvfjfEBV74yTZzrOtj6MG+j8rA9X+ycgF8gEfqaqDyZ6X8NIJ0TkxzgxHKqqu7q6PEbvIlHxeBmo\nVdU9vOeKyDNAnqom1F/rY5gvB44HtuCa619W1Q8CeQ4F7gVOUtXdIlKkqttFZF8goqprfBN9PnCg\nqm5L5N6GkQ74j6zxuBbHfap6XRcXyeiFJNpt9RPgVRF5AzcTdzPOOuQLOBE4tZVzY2mMYQ6NE5o+\nBXwQyPMF4PdRe3lV3e7XjbE7VHWTiKzDuYY38TCMJv4NDAZewHWFGUaHk+g8jzdE5ALgNzSfJbsa\nF542Ga+e8WKYT4vJMx6oF5GrcQOLP1LVp4MZRORoXItnWRL3NoxeTzKu3g2jrSTa8kBVnxKRp3EV\n+wCcbfqHmki/V8ylEsgTwvnhOQZnZviOiMyMtkB8l9WDwB4uUUTEZrsbhmG0gWTCeCcsHv7CSnz/\nQMmwtxjm+P2ZqlqP86cVteiaJSL9cJYxN8b69AmU09xU47zFquqtXV2O7oC9iybsXTRh76KJZD+8\nkxIPEZmIq8RzYo8lYfXUGMMcF852Os5pW5BngU8Df/OupQ8APvbeR58EHlTVJ5Ipu2EYhtFxJCQe\nvgJ/mj3dVAdJSDwSiWGuqk+KyPEisgRnqvs9Vd0qIpfhJj0ViQvLCXC5qi5M5N6GYRhGx5Coqe4D\nwJHAl4B3cN5JtwGX49y1X6qqczqxnAkjImrdVg4RmaaqM7q6HN0BexdN2Ltowt5FE8nWnYmKxxbg\nGuAxnD+do1R1rj92FzBQVT/XtiJ3LCYehtGzEeeGOLqEAtudlUacNa2k7207kWu09dpJ3DMc2M4I\n5AvHbDcMgsO+CzMnd8aAeSEuqlk9LkpZcDb5Uzi7csPocfiKCvasUOJVMKG95E0kT2yFlaJ7hoGM\nYjjyByAC838OWWUQDkFmCEJ+kTCEBMJ+LT5NfJr4NEJuHfJrBPDHQ2G3LyFQf1xC7hihpiWYpqGm\nc46nqY4PqSt7KHaJSRcgrK4yDOZrKW17PpSc7V7b0Gdg2G73LjL8+wiHXPUYDkFGuOlYSNw67JeQ\n7LkdCjW9v1DI3z8UswTSJJAmwXXwuDT9HaJp0b+FhJqfF12i7zP6dyF4LHD+zXlwW9jFMUucRMVj\nC1Coqioia3EhMGf4YweQOk+khtEMX/nn4P7z+/h1HgztDwVFkNsfMvtDOJfmX51++3hA1P+QcJVS\nsEJq3PZ5Qto8PZgvmicczcuei/jKTFrJE3vPnLBfMiA7DNmZkBV2S2YYMjPckuG3M/x2RoarxMJ+\n/45D4G4fSvo7f4NbPvKvQwLrwDZx0gT3wM22o/ljtsFXVgT2pel8AtcK5o+mt2sh8MeJbkevG4Lv\nheEef+y2a+BHDbgP4wbcR7LS9LHcwjFVUJ+u0cWnNWhTWoO69Aa/3bgE9usV6hvc0qAQqXPbdQ1N\n67oGqFOI+O1IA0T8fnSpVb/4Y/URaIhAfR3U+e26Wqirg9pat//x5cBBJEmi4vEOcDTwHM7F803e\nWiqEG/d4KdkbG0ZrxIhCdOkDg/vDgELI6Q+ZhTA5HwpCMEBhIG4pFuhfB4W1sCUHnrnAVfr/+3eY\nVO6/WLUFv4eC+11El8w4+7FpwXzx8reUt6W02OP1QB0uoFNd80UjoPXQUA8NdW5dVw/19a7SidQ3\nVTQNgfC61RHYuA1Q76fRV3D4dWNaQ/PjjfnipMXLp7jKMPY+DXGu0aCufo5Ng6YKOJhW76/bEJMW\nzKdxzlVgyUU4h6/Awo/g2n+4V1pL0zqiUCf+1UtgX9yfIvp30XrQ6Dri/gbU+b9Hnau41W/XRSAS\ncX+fujqoiUBVBGq8WDQKVrx1UMz2ut9COOU9EMl9GM66F+fpI2ESHfP4H2Cwqs70vql+C1yM+yd/\nEfiKqm5NrKBtc4ro0y8Hvuuz3RnPPNjGPLo3XhSyadZKIA8GF0JhIeRFWwr9oF/IzUcdFBWGEBRG\noH8tDKqFgbUwpBYyg//E+bhu1iK3/ubJ8PNB7tAPd8OvSmi98g7hfoRxKupmabHH95a/zlXkkQao\nrXdfhtUNUKNuXaVQGV3qYWc9VERgR70LTljpl2qgCqgSt10LaA1oNdTXuu26ardEaqCmGnZXwc4q\nqOsPk250LZp3b4b6hH6zJBdmuiMm6abgfuFiOPYnbvvd70H9JlqutOOtG9owQbpb0ykD5h1FO50i\n7gO8BUz0WecDx6nqlph7mHh0ESISbCl4cRhUAAOKILcQMgvckh+CoqggiHNPVljnRGFALRR7cciJ\n/efMo5kwNK6j2/1xQZ3K/LIdvrE//HKIO/2bn8BfHqP1ir7efWVWhmB32C2VYagOQ5VfakJuvzrs\nKvGqBlehByv4SppX8tXiugi0FhqqoaEG6n0FX1/tKvmqKqisgfJqX55IoGyx2xGck9BoOFzDaBfJ\n1p1JTRLsANrsFBHnfPH5qGtpEXnBp/09RWVPW7zoB8cU+sCgflBYBH29KIQL4LQwDGiAQdLUUhgQ\naRKFgbUweGMcUQDXGinEOfSLJwyFuC++gDBQhvsYie6X4z7FcZX/hmw4bBBcdhE0hGD8M3Bnna/Y\nw1CVEajwfSVfJa5VQK37mm+ocZV99Gu+tgqqaqC62n3N1zSrzGmlwu9tX6pGetOiePjQsgn/s6vq\nXxPI1h6niMN8/uC5wxMtn7EnAVGIaSkURbuPCiHDi0KRuu6jQeJaC4X1bkxhYI0XhU0tiAK4/7NC\nXJCjWEGIrjPYUxg+idmvbrpktcCGHNiYDSU5btlYDJuAzQJl9RDZDlVLYNvrsKmcVr7gaV7J29e8\nYeyF1loe9yV5rUTEo81OEZMpiIjcGtidkY6TgEQkA/cV78WhqAAGFTlRyOrvWgqnZrqWQnCgOSoK\nRbVQXLMXUQA3LlWA+1u1JAy5uFZBUAjW46JTRvd3N79sVBw2R8VhEGwENqoXhwao3Q7VG2B7CWwo\nBSoCS5V96RtGy4jINPb8eE+YvXVbVQBPAA/hvgLbO5bQVqeI4/25x8Sc+068m6SzozPn/6vvITDp\nFJjYB4bgWgpFDa77qLGlsAXy9maNIUA/4nchRdf5wE6aC0MJsCKwX8EeHw4RgY1ZsDEHtvSFrUVO\nGDbiWg/bgUgZVG+Esq2waSvUBcWh0sTBMNqO/6ieEd0XkVuSOb/FAXMRGY1zef45YCwunvKDwGOq\nWtGWwvoB1eXAcbgK5h2cpda8QJ7PAJ9W1Su8T60FuEHyTOBN4DCfdT4w2QbMHa4Lqs+hMPEUmFgM\npadARgN84yE4dkcLp/WldWEowA0IBIUhdr0DNxYRQz2wPhs258CWbCjJhk1eHDaL8+hfWwY1pVC+\nFdaXQH1QHHabOBhG6ugs9ySTcUIyHWd7/xROSF5M1JY4cK0zcaa6IZxTxJ8FnSL6PL8CzsB1idyu\nqg/59C8A1/tL3amqD8S5flqJh4jkQv/DYMJJ8KlsuGgr3HQl3HeIy/Gt1XDfTJpEISgWtbQuDOW4\nsYA41ANbslzX0pac5uKwCSgVqN0B1aWwswTWxhOHpP53DMPoPDrVVNcPsJ6DE5KzgMdV9dKkS9mJ\npIt4iEgfKDoCJpwI54SdaIyoAcLw1R/AXd6Y4MYK+PUC9hSGMhotk+IRFYdNvvWwNduJQrTlUKJQ\nU+FaDju3woYSqNlJc3GwgWfD6CF0tqluIW4wexSu5VCa5PlGOxGRfBh8NJw8Bc4LwYUlbqIcYdz8\nmTPh++VuTkP1btdtRQvdViWZflA6Kg7ixh02ASUhJwY126BiK2wsgcodNInDLhMHw0hf9tryEJE8\n4Hzc2MfJwAbc3IoHVXVFp5cwSXpry0NECmDoJDhoMlwocP5mGFiH+wCYDJyJq/WfBT52Z5VkBloO\nOQFxEDdHs3o31JY6cdgQTxxa6LIyDKO30WHdViJyKk4wPoOzlHkCJxivd0RBO4veJh4iUgQjjoWD\nJsGFDXDhZiioxxkQHA+cjrNEexbn+Rh4uz88UgBzd0OkFHZthU0lUFFOc3GIdMlDGYbR7ehI8WjA\nmWA+iXO5Xkkr8zRU9bUEC9iqbysfIfAXNE0I/L2q3i8iYeCPOLtkAV4Dvh476NpbxENEBsHo4+Dg\nI+CievjMFsivB7Jw0RRPx4nFs8Bad9Zb/eHR/vD2Olj4MvCxWSwZhpEIHS0eiaKqGtdFacw1E/Ft\ndTlwhKp+K+bcU4BbcRWn4EyHb1LVV2Py9WjxEJHBsO8JMOFQmF4Ln97iJ+llA1NxLlk+wnk49gL7\nZiE82g/eXQcLXgY+MdEwDCMZOnLA/KQOKE8sifi2CvrjD7IB99WdjWu1ZNLcXUmPRkSGwn5T4aKD\nYHoNnL3Oi0YOLtTvyTjhvQtn8oQTjUcK4J01sOhfmGgYhpEiWhSPTnLpkYhvKwXOF5GTcAO/31TV\nNaq6TERewg0KC/C77jhgnywiMgIOOBH+33i4pApOX+ddjOfhBPxEYDHwS2CzO2tGETyaD++ugUWP\nA6tMNAzDSCWp9qqbSAX3NPCwqtZ554wPA8eLyAm4inQYTjxeFpEXVXUPv1fd3beVj2kxCg46CT4/\nDi6phNPW+OBEfXCtjKnAQuAOwMddmFEEj/SDWath0WOYaBiG0Uba69sq1fE8pgA3qOrZfv96IEtV\nb2/lnApVzReR7wNhVf2JT78JqI0z4N5txzy8aIyFCSfD0aPg4l1w4jYvGn1x4xlTgHnA88A2d+Zr\n0ZbGaljyCrDaRMMwjI6ku8fzeB842IewLcG5O/lKMIOIDFIflVBEzsENDgOsBL4sIj/DTVCcCtyT\nqoK3BxEJAfvCxFNh8lC4eCecsMYf7gechvP3NRv4CW4WOE40Hs6H2atg8T8x0TAMo5uQUvFQ1WoR\n+RoudG3Ut9W8GN9W14rIWbjP8TLcXBNw80xOwg0ag/Or9UQqy58szrw4cz84/DSYUgwXl8OxUdHo\njzO3nQTMAn6E8yUFvDIAHu0L730MS/4BrDHRMAyjO5HSbqtU0B26rVwsjYz9YeJpcOIAuHg7HBH1\nRFyEE42jgbeBl4CdzpfUqwPgH/kweyUseVVV17RwC8MwjA6lW8cwTwVdLR7Olf0R58PpA+CSbXDI\nLn9oAM6FyOG4WOyvABVNovFoX5j9MSw10TAMI+WYeHSReDgfYCNPgSmT4OrtcNROf2gQzgPxBOAN\n4FVgtxONVwbCI33g/Y9g2WuqujbV5TYMwwATjy4RD5Gs/eHo8+Fz2bD/brjvMsjMhpsrYMx44HWc\nO5XK5qIx50NY+pqqxkZTNAzDSCkmHh0oHt6f1kigBhdjuzLoTNB5ut33TDj5ULh6CxxQCV/4Dvxx\nvMtx3Wb4wx1AlRONlwbBI3lONJabaBiG0W3o7qa6bXGM+DtV/as/NhK4DxiMc1VyZueOD/Q7Ei48\nH7KrXWS8UhGZXAP1O6C6DE4aC18UuGQVhPOBS6F4XNP5O7ZCfVWTaMxd4buneo1bFcMw0pNUTxJs\ns2NEf2wWcJ2qzvTXCqlqVUyeDml5iEg/OPkaeHAbDA1E3NsRhpcHwWOXQrgernkUjp6Em/0+C+bM\nhLvPd5Ppj3kOZtfD3GWwfIaJhmEY3ZXu3vJos2NEEZmI6zaaCaCqNZ1b1MHnQ/7/g+9Wu2h8x+4E\nwlAQgqenwwP7u3y33ApHzwFuB7bBoQKXPAb/yIV7lsHy16PPaxiG0VtItXi02TEisD9QKSLPAyNw\nVkvf6YxQqCIyHE65ER7Z16Xc9nM4VnEDFw2wT8D9fOkq4P9c1L7/DoOnwrBiMXz4lomGYRi9lR7j\nGBE3I/14YCJOgP4JfJk4Lkra4xjRuRI55GwoDIjSukXA75v2zyuA//Uz3895An46El6qhQ/fgk3z\nVHV7ovczDMPoCtrrGDHV4rEe12qIMoLmLRFUtSywfb+I3O131wHzVXU1gIj8B+dEcA9U9da2FzHn\nEDhjBFy5DG4cBiWrXLcVQLXAhhyIhODcJ+DtLPhlBSyeAdVLVbW67fc1DMNIHf6jekZ0X0RuSeb8\nnuQYcTZQLCIDVbUU57Z8QUcWTkRy4fiz4RsVMOpkuOV38Kd6+Hs+/LwflDZAzXaoWQelm2HjGpxb\n9GSiLhqGYfR4eoxjRFWtEZFvAa96S6s5uJjmHciQ4+HibBh1LDAf7mmAn74BFctw8dx3mYNCwzAM\nmyQYPK8Yzr0aHq2FvOtg9Z1waQRm3aWqtXu/gmEYRs8l2boz1JmF6Sm4IE37nwlXVkLeZ4CX4I+5\nMOc5Ew7DMIw9MfFw7AcnjodPDQCGway58MpmqFvS1QUzDMPojph4AHDEmfDVbRCaDg1PwF/6wgfP\n2kC4YRhGfNJePESkDwwZABMmApXw7DqYuUxVP+nqshmGYXRXUi4eInKGiCwSkaUickOc41eIyFYR\n+cAvX4w53k9E1ovI7zqmROEDgc/Cdy+Bec/DA3mw4qWOubZhGEbvJKWmut7E9h4CjhFF5KWgY0Tc\nLPRH4zlG9PwYF1Spg5j0a3h8rNv+7Jkw7zpV3dJx1zcMw+h9pLrl0egYUVXrcC5GPhWTJ65jRAAR\nOQIoxsX97iDCeU3bO4C1HShMhmEYvZNUi0c8x4jDY/JEHSMuEZGnRWQURH1O8Uvg2o4t0pCZcHME\nLl4JH3xPVXd07PUNwzB6Hz3JMeLXgedUdaObl9EyiTpGdO5I7h0Ml6+Ekx+G8ucSegrDMIweTnsd\nI6Y6GNQU4AZVPdvvXw9kqertrZxToar5IvJ3nCPEBqAvLpLgH1T1BzH5E54l6Vyvz34Q8nPhqG+o\nVsxr46MZhmH0aLp7MKg2O0ZU1csCeS4HjowVjuTJGAjDi+H1lbBrUfuuZRiGkT70GMeI8S7X/hKN\nGQUFxbD8BVWNtP96hmEY6UFaO0YUmfYdeO1OOOmLqjMe6uyyGYZhdFfMMWKCuDknk/eD2h2wYFVX\nl8cwDKMnkbbiAQyAyYOgfCuUb+vqwhiGYfQk0lk8BsL4wbC+BCjv6sIYhmH0JLpEPNrq30pEDhOR\n90RkoYgsE5HPt70UY0fC4AGwZCsmHoZhGEmRalPd9vq3qgCmq+oaEdkHmC8iz6pqG7qdBoyGvGKY\n97yqVrXlWQzDMNKVrmh5tNm/laquVNU1fnsTztVJcbIFEJFMGDYcQvkw2wI+GYZhJElXiEeb/VsF\nEZGjgTxVXdaGMhTBmYOgphQ2rG/D+YZhGGlNV4hHov6tRqnqQcBTOP9WjfguqweBK9pYhoFwWDGU\nl8K6zW28hmEYRtqS8jEPXEtjRGB/BM1bIqhqWWD7fhG5O7ovIv2AZ4AbVXV2vBvs3THiiOEwciCs\n2YINlhuGkYa01zFiV4hHm/1biUgW8CTwoKo+0dINVPXW1otQPBr6D4DnVmHiYRhGGuI/qmdE90Xk\nlmTOT7l4tNO/1XScZ90iEbnCp12uqgsTvb+IhGHKUMgaAjM34yy4DMMwjCRIO99WIjIIbrgBfvoN\nOPY61ff+kMryGYZhdEfMt9XeGQjTiqF6C+zc1NWFMQzD6ImkoXjsMxT+Z6CztFq7oatLYxiG0RNJ\nR/EYA4OLYF0JVG7v6tIYhmH0RNJKPEQkBHnDnVuSxeYQ0TAMo42kXDza6hTRH7vczzpf0kaniIUw\nKgwyFF4rBXa051kMwzDSlZSa6rbHKaKfVX4TMNEnzReRF1V1SxJFGAjTCkCr4eMtqlrb9qcxDMNI\nX1Ld8mizU0TgVOB5Vd2lqruAF3xaEgwaAkcMcpZWVWZpZRiG0UZSLR7tcYo4zOdv7dy93X4MjCxw\nkQO3bEzuXMMwDCNKqmeYJ+oU8WFVrRORL+GcIh6fzE3i+bYSEYHJI6H/QJi7CbaUJHNNwzCM3kRP\n823VHqeI63HdXsFz34l3kxZ8WxXAsAwID4UFCzBLK8Mw0pj2+rZKdbdVo1NEF5CJ6cDzwQzOfUjj\ndqNTROBV4AwRyReRfOAM4JUk7j0QDgoBxfB6KSYehmEYbSalLY/2OEVU1Y0icjvwnr/cbclZWvUf\nDMcNgIYyWF0F7O6wBzMMw0gz0sYxosio0+DFK2HU/nD871Xn3tsV5TMMw+iOmGPEVuk32Pm0KjdL\nK8MwjHaQZuLRpxjWb4e1Jh6GYRjtIM3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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Plot F1 as the number of friends per user increases.\n", "import random\n", "\n", "def sample_friends(X, n):\n", " X_sample = X.copy()\n", " for i, xi in enumerate(X_sample):\n", " nnz = xi.getnnz()\n", " if n < nnz:\n", " nzcols = xi.nonzero()[1]\n", " indices = random.sample(range(nnz), nnz - n)\n", " X_sample[i, nzcols[indices]] = 0.\n", " X_sample.eliminate_zeros()\n", " return X_sample\n", "\n", "def _do_nfriends_expt(XX, y, m, labels):\n", " ys = []\n", " stderrs = []\n", " xs = [1,2,3,4,5,10,20,30,40,50] # range(1, 50)[::5] # [::50]\n", " for nfriends in xs:\n", " f1s = []\n", " for sample in range(5):\n", " X_sample = sample_friends(XX, nfriends)\n", " pred_reg = label_by_reg(X_sample, m)\n", " reg_f1 = eval_labeled(y, pred_reg, labels)\n", " f1s.append(reg_f1)\n", " ys.append(np.mean(f1s))\n", " stderrs.append(np.std(f1s) / math.sqrt(len(f1s)))\n", " return npa(xs), npa(ys), npa(stderrs)\n", "\n", "def do_nfriends_expt():\n", " random.seed(1234)\n", " labels = ['Caucasian', 'Hispanic', 'African American', 'Asian']\n", " users_race, y_race, X_race = read_labeled_data('../data/race.txt', map_race_label)\n", " labels = labels[:3]\n", " m = train_demo_model(labels)\n", " xs_r, ys_r, stderrs_r = _do_nfriends_expt(X_race, y_race, m, labels)\n", "\n", " labels = ['Male', 'Female']\n", " users_race, y_gender, X_gender = read_labeled_data('../data/gender.txt', map_gender_label)\n", " m = train_demo_model(labels)\n", " xs_g, ys_g, stderrs_g = _do_nfriends_expt(X_gender, y_gender, m, labels)\n", " \n", " figure, axes = plt.subplots(2, 1, sharex=True)\n", " axes[0].plot(xs_g, ys_g, 'bo-', ms=3)\n", " axes[0].fill_between(xs_g, ys_g - stderrs_g, ys_g + stderrs_g, alpha=0.4, facecolor='b')\n", " axes[0].set_title('Gender', size=16)\n", " axes[1].plot(xs_r, ys_r, 'bo-', ms=3)\n", " axes[1].fill_between(xs_r, ys_r - stderrs_r, ys_r + stderrs_r, alpha=0.4, facecolor='b')\n", " axes[1].set_title('Ethnicity', size=16)\n", " \n", " axes[1].set_xlabel('# of friends per user', size=16)\n", " axes[1].set_ylabel((' ' * 25) + 'Macro F1', size=16)\n", " axes[1].legend(loc='lower right')\n", " plt.savefig('friends.pdf', bbox_inches='tight')\n", "\n", "do_nfriends_expt()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.4.3" } }, "nbformat": 4, "nbformat_minor": 0 }