{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# PyCaret 2 Clustering Example\n", "This notebook is created using PyCaret 2.0. Last updated : 28-07-2020" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pycaret-nightly-0.39\n" ] } ], "source": [ "# check version\n", "from pycaret.utils import version\n", "version()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1. Loading Dataset" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Country Name199519961997199819992000200120022003...2005200620072008200920102011201220132014
0Arab World2.0048682.0146022.0713092.1777122.3310002.3335962.5887512.5402382.450415...2.1342812.1330382.1668722.1012332.8300672.4896312.5395702.7112622.8954273.073161
1Caribbean small states2.8015182.8566842.9971572.9894512.7678582.8267522.6799692.8886932.740593...2.6295802.6509002.7906652.8229133.4086513.2640643.0876533.3143033.3184323.260012
2Central Europe and the Baltics4.6785284.7532094.6045744.4999884.6790824.5397114.6662724.9001965.100249...4.9708614.8414504.8090575.0547855.3949215.2843805.0962125.0413175.0292665.017717
3Early-demographic dividend2.2031642.1566322.2273112.3641002.4543942.4505552.5270812.3477022.363263...2.3373472.3698842.3852512.4051262.7012602.5071312.4954912.4973402.5867012.665603
4East Asia & Pacific4.4290904.2031524.2443514.4539844.6269204.6888494.6847904.6135374.635098...4.5662154.3671464.2973944.4348484.8652414.7758174.8717274.8668694.6432214.571448
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5 rows × 21 columns

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" ], "text/plain": [ " Country Name 1995 1996 1997 1998 \\\n", "0 Arab World 2.004868 2.014602 2.071309 2.177712 \n", "1 Caribbean small states 2.801518 2.856684 2.997157 2.989451 \n", "2 Central Europe and the Baltics 4.678528 4.753209 4.604574 4.499988 \n", "3 Early-demographic dividend 2.203164 2.156632 2.227311 2.364100 \n", "4 East Asia & Pacific 4.429090 4.203152 4.244351 4.453984 \n", "\n", " 1999 2000 2001 2002 2003 ... 2005 2006 \\\n", "0 2.331000 2.333596 2.588751 2.540238 2.450415 ... 2.134281 2.133038 \n", "1 2.767858 2.826752 2.679969 2.888693 2.740593 ... 2.629580 2.650900 \n", "2 4.679082 4.539711 4.666272 4.900196 5.100249 ... 4.970861 4.841450 \n", "3 2.454394 2.450555 2.527081 2.347702 2.363263 ... 2.337347 2.369884 \n", "4 4.626920 4.688849 4.684790 4.613537 4.635098 ... 4.566215 4.367146 \n", "\n", " 2007 2008 2009 2010 2011 2012 2013 \\\n", "0 2.166872 2.101233 2.830067 2.489631 2.539570 2.711262 2.895427 \n", "1 2.790665 2.822913 3.408651 3.264064 3.087653 3.314303 3.318432 \n", "2 4.809057 5.054785 5.394921 5.284380 5.096212 5.041317 5.029266 \n", "3 2.385251 2.405126 2.701260 2.507131 2.495491 2.497340 2.586701 \n", "4 4.297394 4.434848 4.865241 4.775817 4.871727 4.866869 4.643221 \n", "\n", " 2014 \n", "0 3.073161 \n", "1 3.260012 \n", "2 5.017717 \n", "3 2.665603 \n", "4 4.571448 \n", "\n", "[5 rows x 21 columns]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pycaret.datasets import get_data\n", "data = get_data('public_health')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 2. Initialize Setup" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Setup Succesfully Completed!\n" ] }, { "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", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Description Value
0session_id 123
1Original Data (224, 21)
2Missing Values False
3Numeric Features 20
4Categorical Features 1
5Ordinal Features False
6High Cardinality Features False
7Transformed Data (224, 20)
8Numeric Imputer mean
9Categorical Imputer constant
10Normalize False
11Normalize Method None
12Transformation False
13Transformation Method None
14PCA False
15PCA Method None
16PCA components None
17Ignore Low Variance False
18Combine Rare Levels False
19Rare Level Threshold None
20Numeric Binning False
21Remove Multicollinearity False
22Multicollinearity Threshold None
23Group Features False
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pycaret.clustering import *\n", "clu1 = setup(data, ignore_features = ['Country Name'], session_id=123, log_experiment=True, log_plots = True, experiment_name='health1')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 3. Create Model" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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NameReference
ID
kmeansK-Means Clusteringsklearn.cluster.KMeans
apAffinity Propagationsklearn.cluster.AffinityPropagation
meanshiftMean shift Clusteringsklearn.cluster.MeanShift
scSpectral Clusteringsklearn.cluster.SpectralClustering
hclustAgglomerative Clusteringsklearn.cluster.AgglomerativeClustering
dbscanDensity-Based Spatial Clusteringsklearn.cluster.DBSCAN
opticsOPTICS Clusteringsklearn.cluster.OPTICS
birchBirch Clusteringsklearn.cluster.Birch
kmodesK-Modes Clusteringgit/nicodv/kmodes
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" ], "text/plain": [ " Name \\\n", "ID \n", "kmeans K-Means Clustering \n", "ap Affinity Propagation \n", "meanshift Mean shift Clustering \n", "sc Spectral Clustering \n", "hclust Agglomerative Clustering \n", "dbscan Density-Based Spatial Clustering \n", "optics OPTICS Clustering \n", "birch Birch Clustering \n", "kmodes K-Modes Clustering \n", "\n", " Reference \n", "ID \n", "kmeans sklearn.cluster.KMeans \n", "ap sklearn.cluster.AffinityPropagation \n", "meanshift sklearn.cluster.MeanShift \n", "sc sklearn.cluster.SpectralClustering \n", "hclust sklearn.cluster.AgglomerativeClustering \n", "dbscan sklearn.cluster.DBSCAN \n", "optics sklearn.cluster.OPTICS \n", "birch sklearn.cluster.Birch \n", "kmodes git/nicodv/kmodes " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "models()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Metric
Silhouette0.4335
Calinski-Harabasz322.9575
Davies-Bouldin0.7471
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" ], "text/plain": [ " Metric\n", "Silhouette 0.4335\n", "Calinski-Harabasz 322.9575\n", "Davies-Bouldin 0.7471" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "kmeans = create_model('kmeans', num_clusters = 4)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Metric
Silhouette-0.3632
Calinski-Harabasz1.2468
Davies-Bouldin1.2297
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" ], "text/plain": [ " Metric\n", "Silhouette -0.3632\n", "Calinski-Harabasz 1.2468\n", "Davies-Bouldin 1.2297" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "kmodes = create_model('kmodes', num_clusters = 4)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 4. Assign Labels" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Country Name199519961997199819992000200120022003...200620072008200920102011201220132014Cluster
0Arab World2.0048682.0146022.0713092.1777122.3310002.3335962.5887512.5402382.450415...2.1330382.1668722.1012332.8300672.4896312.5395702.7112622.8954273.073161Cluster 2
1Caribbean small states2.8015182.8566842.9971572.9894512.7678582.8267522.6799692.8886932.740593...2.6509002.7906652.8229133.4086513.2640643.0876533.3143033.3184323.260012Cluster 2
2Central Europe and the Baltics4.6785284.7532094.6045744.4999884.6790824.5397114.6662724.9001965.100249...4.8414504.8090575.0547855.3949215.2843805.0962125.0413175.0292665.017717Cluster 0
3Early-demographic dividend2.2031642.1566322.2273112.3641002.4543942.4505552.5270812.3477022.363263...2.3698842.3852512.4051262.7012602.5071312.4954912.4973402.5867012.665603Cluster 2
4East Asia & Pacific4.4290904.2031524.2443514.4539844.6269204.6888494.6847904.6135374.635098...4.3671464.2973944.4348484.8652414.7758174.8717274.8668694.6432214.571448Cluster 0
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5 rows × 22 columns

\n", "
" ], "text/plain": [ " Country Name 1995 1996 1997 1998 \\\n", "0 Arab World 2.004868 2.014602 2.071309 2.177712 \n", "1 Caribbean small states 2.801518 2.856684 2.997157 2.989451 \n", "2 Central Europe and the Baltics 4.678528 4.753209 4.604574 4.499988 \n", "3 Early-demographic dividend 2.203164 2.156632 2.227311 2.364100 \n", "4 East Asia & Pacific 4.429090 4.203152 4.244351 4.453984 \n", "\n", " 1999 2000 2001 2002 2003 ... 2006 2007 \\\n", "0 2.331000 2.333596 2.588751 2.540238 2.450415 ... 2.133038 2.166872 \n", "1 2.767858 2.826752 2.679969 2.888693 2.740593 ... 2.650900 2.790665 \n", "2 4.679082 4.539711 4.666272 4.900196 5.100249 ... 4.841450 4.809057 \n", "3 2.454394 2.450555 2.527081 2.347702 2.363263 ... 2.369884 2.385251 \n", "4 4.626920 4.688849 4.684790 4.613537 4.635098 ... 4.367146 4.297394 \n", "\n", " 2008 2009 2010 2011 2012 2013 2014 \\\n", "0 2.101233 2.830067 2.489631 2.539570 2.711262 2.895427 3.073161 \n", "1 2.822913 3.408651 3.264064 3.087653 3.314303 3.318432 3.260012 \n", "2 5.054785 5.394921 5.284380 5.096212 5.041317 5.029266 5.017717 \n", "3 2.405126 2.701260 2.507131 2.495491 2.497340 2.586701 2.665603 \n", "4 4.434848 4.865241 4.775817 4.871727 4.866869 4.643221 4.571448 \n", "\n", " Cluster \n", "0 Cluster 2 \n", "1 Cluster 2 \n", "2 Cluster 0 \n", "3 Cluster 2 \n", "4 Cluster 0 \n", "\n", "[5 rows x 22 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "kmeans_results = assign_model(kmeans)\n", "kmeans_results.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 5. Analyze Model" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "customdata": [ [ "Honduras" ], [ "Dominica" ], [ "Djibouti" ], [ "Samoa" ], [ "San Marino" ], [ "Sao Tome and Principe" ], [ "Colombia" ], [ "Chile" ], [ "Cabo Verde" ], [ "Solomon Islands" ], [ "Bulgaria" ], [ "South Africa" ], [ "Brazil" ], [ "Botswana" ], [ "Bolivia" ], [ "Bhutan" ], [ "Belarus" ], [ "Barbados" ], [ "St. Lucia" ], [ "St. Vincent and the Grenadines" ], [ "Russian Federation" ], [ "Suriname" ], [ "Romania" ], [ "Estonia" ], [ "Moldova" ], [ "Malawi" ], [ "Monaco" ], [ "Macedonia, FYR" ], [ "Lithuania" ], [ "Lebanon" ], [ "Latvia" ], [ "Montenegro" ], [ "Mozambique" ], [ "Namibia" ], [ "Jordan" ], [ "Israel" ], [ "Nicaragua" ], [ "Hungary" ], [ "Guyana" ], [ "Grenada" ], [ "Panama" ], [ "Papua New Guinea" ], [ "Poland" ], [ "El Salvador" ], [ "Argentina" ], [ "Seychelles" ], [ "Swaziland" ], [ "Small states" ], [ "Tonga" ], [ "Vanuatu" ], [ "Pacific island small states" ], [ "Other small states" ], [ "Tunisia" ], [ "East Asia & Pacific" ], [ "Turkey" ], [ "Ukraine" ], [ "Antigua and Barbuda" ], [ "Europe & Central Asia (IDA & IBRD countries)" ], [ "Latin America & the Caribbean (IDA & IBRD countries)" ], [ "Latin America & Caribbean (excluding high income)" ], [ "Latin America & Caribbean" ], [ "Europe & Central Asia (excluding high income)" ], [ "Thailand" ], [ "Uruguay" ], [ "Central Europe and the Baltics" ], [ "Algeria" ], [ "Andorra" ] ], "hovertemplate": "Cluster=Cluster 0
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\n", 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\n", 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\n", 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1Caribbean small states2.8015182.8566842.9971572.9894512.7678582.8267522.6799692.8886932.740593...2.6509002.7906652.8229133.4086513.2640643.0876533.3143033.3184323.260012Cluster 2
2Central Europe and the Baltics4.6785284.7532094.6045744.4999884.6790824.5397114.6662724.9001965.100249...4.8414504.8090575.0547855.3949215.2843805.0962125.0413175.0292665.017717Cluster 0
3Early-demographic dividend2.2031642.1566322.2273112.3641002.4543942.4505552.5270812.3477022.363263...2.3698842.3852512.4051262.7012602.5071312.4954912.4973402.5867012.665603Cluster 2
4East Asia & Pacific4.4290904.2031524.2443514.4539844.6269204.6888494.6847904.6135374.635098...4.3671464.2973944.4348484.8652414.7758174.8717274.8668694.6432214.571448Cluster 0
\n", "

5 rows × 22 columns

\n", "
" ], "text/plain": [ " Country Name 1995 1996 1997 1998 \\\n", "0 Arab World 2.004868 2.014602 2.071309 2.177712 \n", "1 Caribbean small states 2.801518 2.856684 2.997157 2.989451 \n", "2 Central Europe and the Baltics 4.678528 4.753209 4.604574 4.499988 \n", "3 Early-demographic dividend 2.203164 2.156632 2.227311 2.364100 \n", "4 East Asia & Pacific 4.429090 4.203152 4.244351 4.453984 \n", "\n", " 1999 2000 2001 2002 2003 ... 2006 2007 \\\n", "0 2.331000 2.333596 2.588751 2.540238 2.450415 ... 2.133038 2.166872 \n", "1 2.767858 2.826752 2.679969 2.888693 2.740593 ... 2.650900 2.790665 \n", "2 4.679082 4.539711 4.666272 4.900196 5.100249 ... 4.841450 4.809057 \n", "3 2.454394 2.450555 2.527081 2.347702 2.363263 ... 2.369884 2.385251 \n", "4 4.626920 4.688849 4.684790 4.613537 4.635098 ... 4.367146 4.297394 \n", "\n", " 2008 2009 2010 2011 2012 2013 2014 \\\n", "0 2.101233 2.830067 2.489631 2.539570 2.711262 2.895427 3.073161 \n", "1 2.822913 3.408651 3.264064 3.087653 3.314303 3.318432 3.260012 \n", "2 5.054785 5.394921 5.284380 5.096212 5.041317 5.029266 5.017717 \n", "3 2.405126 2.701260 2.507131 2.495491 2.497340 2.586701 2.665603 \n", "4 4.434848 4.865241 4.775817 4.871727 4.866869 4.643221 4.571448 \n", "\n", " Cluster \n", "0 Cluster 2 \n", "1 Cluster 2 \n", "2 Cluster 0 \n", "3 Cluster 2 \n", "4 Cluster 0 \n", "\n", "[5 rows x 22 columns]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pred_new = predict_model(kmeans, data=data)\n", "pred_new.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 7. Save / Load Model" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Transformation Pipeline and Model Succesfully Saved\n" ] } ], "source": [ "save_model(kmeans, model_name='kmeans')" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Transformation Pipeline and Model Sucessfully Loaded\n", "[Pipeline(memory=None,\n", " steps=[('dtypes',\n", " DataTypes_Auto_infer(categorical_features=[],\n", " display_types=True,\n", " features_todrop=['Country Name'],\n", " ml_usecase='regression',\n", " numerical_features=[],\n", " target='dummy_target',\n", " time_features=[])),\n", " ('imputer',\n", " Simple_Imputer(categorical_strategy='not_available',\n", " numeric_strategy='mean',\n", " target_variable=None)),\n", " ('new_levels1',\n", " New_...\n", " target='dummy_target')),\n", " ('feature_time',\n", " Make_Time_Features(list_of_features=None, time_feature=[])),\n", " ('group', Empty()), ('scaling', Empty()),\n", " ('P_transform', Empty()), ('binn', Empty()),\n", " ('fix_perfect', Empty()), ('rem_outliers', Empty()),\n", " ('dummy', Dummify(target='dummy_target')),\n", " ('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\n", " ('pca', Empty())],\n", " verbose=False), KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n", " n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\n", " random_state=123, tol=0.0001, verbose=0)]\n" ] } ], "source": [ "loaded_kmeans = load_model('kmeans')\n", "print(loaded_kmeans)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Pipeline(memory=None,\n",
       "         steps=[('dtypes',\n",
       "                 DataTypes_Auto_infer(categorical_features=[],\n",
       "                                      display_types=True,\n",
       "                                      features_todrop=['Country Name'],\n",
       "                                      ml_usecase='regression',\n",
       "                                      numerical_features=[],\n",
       "                                      target='dummy_target',\n",
       "                                      time_features=[])),\n",
       "                ('imputer',\n",
       "                 Simple_Imputer(categorical_strategy='not_available',\n",
       "                                numeric_strategy='mean',\n",
       "                                target_variable=None)),\n",
       "                ('new_levels1',\n",
       "                 New_...\n",
       "                                                    target='dummy_target')),\n",
       "                ('feature_time',\n",
       "                 Make_Time_Features(list_of_features=None, time_feature=[])),\n",
       "                ('group', Empty()), ('scaling', Empty()),\n",
       "                ('P_transform', Empty()), ('binn', Empty()),\n",
       "                ('fix_perfect', Empty()), ('rem_outliers', Empty()),\n",
       "                ('dummy', Dummify(target='dummy_target')),\n",
       "                ('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\n",
       "                ('pca', Empty())],\n",
       "         verbose=False)
DataTypes_Auto_infer(features_todrop=['Country Name'], ml_usecase='regression',\n",
       "                     target='dummy_target')
Simple_Imputer(categorical_strategy='not_available', numeric_strategy='mean',\n",
       "               target_variable=None)
New_Catagorical_Levels_in_TestData(replacement_strategy='least frequent',\n",
       "                                   target='dummy_target')
Empty()
Empty()
Empty()
Empty()
New_Catagorical_Levels_in_TestData(replacement_strategy='least frequent',\n",
       "                                   target='dummy_target')
Make_Time_Features(list_of_features=None)
Empty()
Empty()
Empty()
Empty()
Empty()
Empty()
Dummify(target='dummy_target')
Clean_Colum_Names()
Empty()
Empty()
" ], "text/plain": [ "Pipeline(memory=None,\n", " steps=[('dtypes',\n", " DataTypes_Auto_infer(categorical_features=[],\n", " display_types=True,\n", " features_todrop=['Country Name'],\n", " ml_usecase='regression',\n", " numerical_features=[],\n", " target='dummy_target',\n", " time_features=[])),\n", " ('imputer',\n", " Simple_Imputer(categorical_strategy='not_available',\n", " numeric_strategy='mean',\n", " target_variable=None)),\n", " ('new_levels1',\n", " New_...\n", " target='dummy_target')),\n", " ('feature_time',\n", " Make_Time_Features(list_of_features=None, time_feature=[])),\n", " ('group', Empty()), ('scaling', Empty()),\n", " ('P_transform', Empty()), ('binn', Empty()),\n", " ('fix_perfect', Empty()), ('rem_outliers', Empty()),\n", " ('dummy', Dummify(target='dummy_target')),\n", " ('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\n", " ('pca', Empty())],\n", " verbose=False)" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn import set_config\n", "set_config(display='diagram')\n", "loaded_kmeans[0]" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "from sklearn import set_config\n", "set_config(display='text')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 8. Deploy Model" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model Succesfully Deployed on AWS S3\n" ] } ], "source": [ "deploy_model(kmeans, model_name = 'kmeans-aws', authentication = {'bucket' : 'pycaret-test'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 9. Get Config / Set Config" ] }, { "cell_type": "code", "execution_count": 21, "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", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
19951996199719981999200020012002200320042005200620072008200920102011201220132014
02.0048682.0146022.0713092.1777122.3310002.3335962.5887512.5402382.4504152.3149142.1342812.1330382.1668722.1012332.8300672.4896312.5395702.7112622.8954273.073161
12.8015182.8566842.9971572.9894512.7678582.8267522.6799692.8886932.7405932.8459712.6295802.6509002.7906652.8229133.4086513.2640643.0876533.3143033.3184323.260012
24.6785284.7532094.6045744.4999884.6790824.5397114.6662724.9001965.1002494.9136294.9708614.8414504.8090575.0547855.3949215.2843805.0962125.0413175.0292665.017717
32.2031642.1566322.2273112.3641002.4543942.4505552.5270812.3477022.3632632.3468242.3373472.3698842.3852512.4051262.7012602.5071312.4954912.4973402.5867012.665603
44.4290904.2031524.2443514.4539844.6269204.6888494.6847904.6135374.6350984.6266964.5662154.3671464.2973944.4348484.8652414.7758174.8717274.8668694.6432214.571448
\n", "
" ], "text/plain": [ " 1995 1996 1997 1998 1999 2000 2001 \\\n", "0 2.004868 2.014602 2.071309 2.177712 2.331000 2.333596 2.588751 \n", "1 2.801518 2.856684 2.997157 2.989451 2.767858 2.826752 2.679969 \n", "2 4.678528 4.753209 4.604574 4.499988 4.679082 4.539711 4.666272 \n", "3 2.203164 2.156632 2.227311 2.364100 2.454394 2.450555 2.527081 \n", "4 4.429090 4.203152 4.244351 4.453984 4.626920 4.688849 4.684790 \n", "\n", " 2002 2003 2004 2005 2006 2007 2008 \\\n", "0 2.540238 2.450415 2.314914 2.134281 2.133038 2.166872 2.101233 \n", "1 2.888693 2.740593 2.845971 2.629580 2.650900 2.790665 2.822913 \n", "2 4.900196 5.100249 4.913629 4.970861 4.841450 4.809057 5.054785 \n", "3 2.347702 2.363263 2.346824 2.337347 2.369884 2.385251 2.405126 \n", "4 4.613537 4.635098 4.626696 4.566215 4.367146 4.297394 4.434848 \n", "\n", " 2009 2010 2011 2012 2013 2014 \n", "0 2.830067 2.489631 2.539570 2.711262 2.895427 3.073161 \n", "1 3.408651 3.264064 3.087653 3.314303 3.318432 3.260012 \n", "2 5.394921 5.284380 5.096212 5.041317 5.029266 5.017717 \n", "3 2.701260 2.507131 2.495491 2.497340 2.586701 2.665603 \n", "4 4.865241 4.775817 4.871727 4.866869 4.643221 4.571448 " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X = get_config('X')\n", "X.head()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "123" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_config('seed')" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [], "source": [ "from pycaret.clustering import set_config\n", "set_config('seed', 999)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "999" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_config('seed')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 10. Get System Logs" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '47', '14,652', 'INFO', 'PyCaret Regression Module']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'USI', 'e640']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'setup(data=(1338, 7), target=charges, train_size=0.7, sampling=True, sample_estimator=None, categorical_features=None, categorical_imputation=constant, ordinal_features=None,']\n", "['high_cardinality_features=None, high_cardinality_method=frequency, numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=None, normalize=False,']\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None, remove_outliers=False, outliers_threshold=0.05,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, remove_perfect_collinearity=False, create_clusters=False, cluster_iter=20,']\n", "['polynomial_features=False, polynomial_degree=2, trigonometry_features=False, polynomial_threshold=0.1, group_features=None,']\n", "['group_names=None, feature_selection=False, feature_selection_threshold=0.8, feature_interaction=False, feature_ratio=False, interaction_threshold=0.01, transform_target=False,']\n", "['transform_target_method=box-cox, data_split_shuffle=True, folds_shuffle=False, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=insurance1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Memory', 'svmem(total=17032478720, available=5530103808, percent=67.5, used=11502374912, free=5530103808)']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '15,120', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '47', '15,204', 'INFO', 'xgboost==1.1.1']\n", "['2020-07-29 09', '47', '15,259', 'INFO', 'lightgbm==2.3.1']\n", "['2020-07-29 09', '47', '15,310', 'INFO', 'catboost==0.23.2']\n", "['2020-07-29 09', '47', '15,876', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '15,877', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '15,877', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '15,877', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '15,900', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '18,284', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '47', '18,285', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '18,296', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '47', '18,296', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '47', '19,149', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '47', '20,310', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '47', '20,310', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '20,310', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '47', '20,311', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '47', '20,410', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '47', '20,692', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '20,693', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '20,702', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '47', '20,702', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '20,710', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '20,721', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), None]']\n", "['2020-07-29 09', '47', '20,721', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '20,722', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'create_model_container', '0']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'master_model_container', '0']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'display_container', '0']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Initializing compare_models()']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'compare_models(blacklist=None, whitelist=None, fold=5, round=4, sort=R2, n_select=1, turbo=True, verbose=True)']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '32,174', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '47', '32,176', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '32,186', 'INFO', 'Importing untrained models']\n", "['2020-07-29 09', '47', '32,187', 'INFO', 'Import successful']\n", "['2020-07-29 09', '47', '32,191', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '47', '32,192', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '47', '32,192', 'INFO', 'Initializing Linear Regression']\n", "['2020-07-29 09', '47', '32,198', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '32,206', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,210', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,212', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,212', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,229', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '32,235', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,239', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,240', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,241', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,248', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '32,254', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,257', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,259', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,260', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,266', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '32,271', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,275', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,276', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,277', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,282', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '32,288', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,291', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,293', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,293', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,302', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '32,302', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '32,313', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '32,365', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '32,366', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '32,366', 'INFO', 'save_model(model=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '32,366', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '32,371', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '32,376', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), None]']\n", "['2020-07-29 09', '47', '32,376', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '32,376', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '32,731', 'INFO', 'Initializing Lasso Regression']\n", "['2020-07-29 09', '47', '32,736', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '32,742', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,747', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,749', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,749', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,756', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '32,762', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,766', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,768', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,768', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,775', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '32,781', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,786', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,788', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,788', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,795', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '32,801', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,804', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,805', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,805', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,812', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '32,818', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,820', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,822', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,822', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,829', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '32,829', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '32,841', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'save_model(model=Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '32,907', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '32,912', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '47', '32,912', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '32,912', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '32,961', 'INFO', 'Initializing Ridge Regression']\n", "['2020-07-29 09', '47', '32,967', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '32,972', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,974', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,976', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,976', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,983', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '32,988', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,991', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,993', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,993', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,001', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,006', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,008', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,010', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,010', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,017', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,022', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,025', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,027', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,027', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,035', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,041', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,043', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,045', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,045', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,051', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,051', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,062', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'save_model(model=Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,134', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,139', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), None]\"]\n", "['2020-07-29 09', '47', '33,139', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,139', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,188', 'INFO', 'Initializing Elastic Net']\n", "['2020-07-29 09', '47', '33,194', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,200', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,203', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,205', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,205', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,212', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,219', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,222', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,225', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,225', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,232', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,237', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,241', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,243', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,243', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,251', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,255', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,260', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,262', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,262', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,270', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,277', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,280', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,283', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,283', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,291', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,291', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,302', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,367', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,368', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,368', 'INFO', 'save_model(model=ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,']\n", "['max_iter=1000, normalize=False, positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '33,368', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,373', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,379', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,']\n", "['max_iter=1000, normalize=False, positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '47', '33,379', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,379', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,465', 'INFO', 'Initializing Least Angle Regression']\n", "['2020-07-29 09', '47', '33,470', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,476', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,482', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,483', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,484', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,490', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,496', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,502', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,504', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,504', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,510', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,517', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,522', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,523', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,523', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,531', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,536', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,542', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,543', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,544', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,552', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,564', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,572', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,574', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,574', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,580', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,581', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,593', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,653', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,654', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,654', 'INFO', 'save_model(model=Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '33,654', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,658', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,664', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), None]']\n", "['2020-07-29 09', '47', '33,664', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,664', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,714', 'INFO', 'Initializing Lasso Least Angle Regression']\n", "['2020-07-29 09', '47', '33,720', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,728', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,733', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,734', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,734', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,739', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,745', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,750', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,752', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,752', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,758', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,764', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,768', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,770', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,770', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,775', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,780', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,784', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,786', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,786', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,792', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,798', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,802', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,803', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,803', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,809', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,810', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,821', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'save_model(model=LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,884', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,889', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), None]\"]\n", "['2020-07-29 09', '47', '33,889', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,890', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,946', 'INFO', 'Initializing Orthogonal Matching Pursuit']\n", "['2020-07-29 09', '47', '33,952', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,961', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,964', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,966', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,966', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,974', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,983', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,985', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,987', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,988', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,997', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '34,002', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,006', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,008', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,008', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,017', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '34,023', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,026', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,029', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,029', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,037', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '34,044', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,048', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,051', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,051', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,058', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '34,058', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '34,073', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '34,193', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '34,193', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '34,194', 'INFO', 'save_model(model=OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,']\n", "[\"normalize=True, precompute='auto', tol=None), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '34,194', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '34,202', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '34,211', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,']\n", "[\"normalize=True, precompute='auto', tol=None), None]\"]\n", "['2020-07-29 09', '47', '34,211', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '34,211', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '34,263', 'INFO', 'Initializing Bayesian Ridge']\n", "['2020-07-29 09', '47', '34,269', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '34,277', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,284', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,286', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,287', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,295', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '34,304', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,311', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,314', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,314', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,323', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '34,331', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,339', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,341', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,342', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,350', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '34,357', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,364', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,367', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,367', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,375', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '34,383', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,391', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,393', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,393', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,402', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '34,402', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '34,420', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '34,507', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '34,507', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '34,508', 'INFO', 'save_model(model=BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,']\n", "['compute_score=False, copy_X=True, fit_intercept=True,']\n", "['lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,']\n", "['normalize=False, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '34,508', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '34,516', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '34,523', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,']\n", "['compute_score=False, copy_X=True, fit_intercept=True,']\n", "['lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,']\n", "['normalize=False, tol=0.001, verbose=False), None]']\n", "['2020-07-29 09', '47', '34,524', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '34,524', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '34,625', 'INFO', 'Initializing Passive Aggressive Regressor']\n", "['2020-07-29 09', '47', '34,633', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '34,640', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,651', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,654', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,654', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,664', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '34,672', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,683', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,685', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,686', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,696', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '34,705', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,715', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,717', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,717', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,726', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '34,735', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,746', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,749', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,749', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,759', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '34,767', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,777', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,779', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,779', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,790', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '34,790', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '34,808', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '34,904', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '34,904', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '34,905', 'INFO', 'save_model(model=PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,']\n", "['epsilon=0.1, fit_intercept=True,']\n", "[\"loss='epsilon_insensitive', max_iter=1000,\"]\n", "['n_iter_no_change=5, random_state=123, shuffle=True,']\n", "['tol=0.001, validation_fraction=0.1, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '34,905', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '34,914', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '34,922', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,']\n", "['epsilon=0.1, fit_intercept=True,']\n", "[\"loss='epsilon_insensitive', max_iter=1000,\"]\n", "['n_iter_no_change=5, random_state=123, shuffle=True,']\n", "['tol=0.001, validation_fraction=0.1, verbose=0,']\n", "['warm_start=False), None]']\n", "['2020-07-29 09', '47', '34,922', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '34,922', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '35,002', 'INFO', 'Initializing Random Sample Consensus']\n", "['2020-07-29 09', '47', '35,011', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '35,023', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,179', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,182', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,183', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,194', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '35,203', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,358', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,361', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,361', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,371', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '35,381', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,533', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,535', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,535', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,547', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '35,556', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,711', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,714', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,715', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,727', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '35,737', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,875', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,878', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,878', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,889', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '35,889', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '35,911', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'save_model(model=RANSACRegressor(base_estimator=None, is_data_valid=None, is_model_valid=None,']\n", "[\"loss='absolute_loss', max_skips=inf, max_trials=100,\"]\n", "['min_samples=0.5, random_state=123, residual_threshold=None,']\n", "['stop_n_inliers=inf, stop_probability=0.99, stop_score=inf), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '36,029', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '36,039', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RANSACRegressor(base_estimator=None, is_data_valid=None, is_model_valid=None,']\n", "[\"loss='absolute_loss', max_skips=inf, max_trials=100,\"]\n", "['min_samples=0.5, random_state=123, residual_threshold=None,']\n", "['stop_n_inliers=inf, stop_probability=0.99, stop_score=inf), None]']\n", "['2020-07-29 09', '47', '36,039', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '36,039', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '36,159', 'INFO', 'Initializing TheilSen Regressor']\n", "['2020-07-29 09', '47', '36,168', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '36,178', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '42,054', 'INFO', 'PyCaret Clustering Module']\n", "['2020-07-29 09', '47', '42,054', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '42,055', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '42,055', 'INFO', 'USI', 'e74c']\n", "['2020-07-29 09', '47', '42,056', 'INFO', 'setup(data=(224, 21), categorical_features=None, categorical_imputation=constant, ordinal_features=None, high_cardinality_features=None,']\n", "[\"numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=['Country Name'], normalize=False,\"]\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, group_features=None,']\n", "['group_names=None, supervised=False, supervised_target=None, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=health1, log_plots=True, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '47', '42,057', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '42,058', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '42,058', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '42,059', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '42,060', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '42,272', 'INFO', 'Memory', 'svmem(total=17032478720, available=5177511936, percent=69.6, used=11854966784, free=5177511936)']\n", "['2020-07-29 09', '47', '42,272', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '42,273', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '42,273', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '42,273', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '42,283', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '43,243', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '43,252', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '43,252', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '43,276', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '43,295', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '43,989', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '47', '43,991', 'INFO', 'kmodes==0.10.2']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'PyCaret Anomaly Detection Module']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'USI', '9b51']\n", "['2020-07-29 09', '47', '45,077', 'INFO', 'setup(data=(1000, 10), categorical_features=None, categorical_imputation=constant, ordinal_features=None, high_cardinality_features=None,']\n", "['numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=None, normalize=False,']\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, group_features=None,']\n", "['group_names=None, supervised=False, supervised_target=None, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=anomaly1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '47', '45,077', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '45,078', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '45,078', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '45,078', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '45,079', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '45,083', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '45,089', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '45,090', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '45,113', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '45,133', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '45,136', 'INFO', 'Memory', 'svmem(total=17032478720, available=5155127296, percent=69.7, used=11877351424, free=5155127296)']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '45,138', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '45,767', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '45,768', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '45,769', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '45,850', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '45,903', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '45,903', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '45,904', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '47', '45,920', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '47', '45,921', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '47', '47,044', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '47,054', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '47,055', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '47,083', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '47,108', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '48,011', 'WARNING', 'pyod not found']\n", "['2020-07-29 09', '47', '48,500', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '47', '49,140', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '49,146', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '49,146', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '49,170', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '49,194', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '49,891', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '47', '49,892', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '47', '49,896', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '47', '49,930', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '49,931', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '49,931', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '50,035', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '50,094', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '50,094', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '50,094', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '47', '50,112', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '47', '50,112', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '47', '51,064', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '51,070', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '47', '51,071', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '51,071', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '51,100', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '51,101', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '51,167', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '51,238', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '47', '51,321', 'INFO', 'PyCaret NLP Module']\n", "['2020-07-29 09', '47', '51,321', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '51,322', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '51,322', 'INFO', 'USI', 'ab65']\n", "['2020-07-29 09', '47', '51,322', 'INFO', 'setup(data=(6818, 7), target=en, custom_stopwords=None, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=kiva1, log_plots=True, log_data=False, verbose=True)']\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '51,324', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '51,402', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '51,402', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '51,404', 'INFO', 'save_model(model=TheilSenRegressor(copy_X=True, fit_intercept=True, max_iter=300,']\n", "['max_subpopulation=10000, n_jobs=-1, n_subsamples=None,']\n", "['random_state=123, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '51,404', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '51,411', 'INFO', 'Memory', 'svmem(total=17032478720, available=5093425152, percent=70.1, used=11939053568, free=5093425152)']\n", "['2020-07-29 09', '47', '51,412', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '51,412', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '51,412', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '51,412', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '51,413', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '51,431', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '51,463', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), TheilSenRegressor(copy_X=True, fit_intercept=True, max_iter=300,']\n", "['max_subpopulation=10000, n_jobs=-1, n_subsamples=None,']\n", "['random_state=123, tol=0.001, verbose=False), None]']\n", "['2020-07-29 09', '47', '51,463', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '51,463', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '51,703', 'INFO', 'Initializing Huber Regressor']\n", "['2020-07-29 09', '47', '51,722', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '51,746', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '51,869', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '51,870', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '51,897', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '47', '51,897', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '51,912', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '51,922', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '51,926', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '51,926', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '51,942', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)]']\n", "['2020-07-29 09', '47', '51,942', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '51,943', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '51,951', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '51,969', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,110', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,118', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,118', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,131', 'INFO', 'Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)']\n", "['2020-07-29 09', '47', '52,132', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '47', '52,142', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '52,165', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,296', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,301', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,302', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,321', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '52,340', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,469', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,473', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,473', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,491', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '52,507', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,632', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,638', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,638', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,653', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '52,654', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '52,688', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '52,825', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '52,825', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '52,826', 'INFO', 'save_model(model=HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,']\n", "['tol=1e-05, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '52,826', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '52,841', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '52,854', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,']\n", "['tol=1e-05, warm_start=False), None]']\n", "['2020-07-29 09', '47', '52,854', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '52,854', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '53,009', 'INFO', 'Initializing Support Vector Machine']\n", "['2020-07-29 09', '47', '53,023', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '53,040', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,106', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,120', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,120', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,135', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '53,149', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,211', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,223', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,223', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,237', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '53,250', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,304', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,313', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,314', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,326', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '53,341', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,367', 'INFO', 'gensim==3.8.3']\n", "['2020-07-29 09', '47', '53,398', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,410', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,410', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,424', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '53,436', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,489', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,500', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,500', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,513', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '53,513', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '53,544', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '53,668', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '53,668', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '53,669', 'INFO', \"save_model(model=SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\"]\n", "[\"kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '53,669', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '53,680', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '53,690', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\"]\n", "[\"kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False), None]\"]\n", "['2020-07-29 09', '47', '53,690', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '53,690', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '53,805', 'INFO', 'Initializing K Neighbors Regressor']\n", "['2020-07-29 09', '47', '53,817', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '53,831', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,838', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,953', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,953', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,968', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '53,981', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,989', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,057', 'INFO', 'spacy==2.2.4']\n", "['2020-07-29 09', '47', '54,099', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,100', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,115', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '54,126', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,134', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,243', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,243', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,256', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '54,266', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,275', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,384', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,384', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,395', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '54,405', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,414', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,524', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,525', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,538', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '54,539', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '54,572', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '54,705', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '54,705', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '54,706', 'INFO', \"save_model(model=KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform'), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '54,707', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '54,723', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '54,740', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform'), None]\"]\n", "['2020-07-29 09', '47', '54,740', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '54,740', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '54,857', 'INFO', 'nltk==3.5']\n", "['2020-07-29 09', '47', '54,892', 'INFO', 'Initializing Decision Tree']\n", "['2020-07-29 09', '47', '54,902', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '54,921', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,924', 'INFO', 'textblob==0.15.3']\n", "['2020-07-29 09', '47', '54,932', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,935', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,935', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,949', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '54,965', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,978', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,983', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,984', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,005', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '55,021', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,032', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,036', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '47', '55,036', 'INFO', 'create_model(model=kmeans, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-29 09', '47', '55,036', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '55,037', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '55,037', 'INFO', 'Setting num_cluster param']\n", "['2020-07-29 09', '47', '55,037', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '55,038', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '55,038', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,057', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '55,077', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,078', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '47', '55,078', 'INFO', 'K-Means Clustering Imported succesfully']\n", "['2020-07-29 09', '47', '55,094', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,098', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,102', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '55,102', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,122', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '55,141', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,158', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,163', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '55,163', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,189', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '55,190', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '55,214', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,232', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '55,236', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-29 09', '47', '55,245', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '55,417', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '55,417', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '55,419', 'INFO', \"save_model(model=DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "[\"min_weight_fraction_leaf=0.0, presort='deprecated',\"]\n", "[\"random_state=123, splitter='best'), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '55,419', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '55,437', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-29 09', '47', '55,437', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '47', '55,438', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '47', '55,439', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '55,439', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '55,439', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '55,465', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "[\"min_weight_fraction_leaf=0.0, presort='deprecated',\"]\n", "[\"random_state=123, splitter='best'), None]\"]\n", "['2020-07-29 09', '47', '55,466', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '55,466', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '55,656', 'INFO', 'Initializing Random Forest']\n", "['2020-07-29 09', '47', '55,675', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '55,694', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '56,059', 'INFO', 'pyLDAvis==2.1.2']\n", "['2020-07-29 09', '47', '56,271', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '56,275', 'INFO', 'wordcloud==1.7.0']\n", "['2020-07-29 09', '47', '56,383', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '56,384', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '56,401', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '56,417', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '56,825', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '47', '56,826', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '47', '56,829', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '47', '56,945', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '57,059', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '57,060', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '57,086', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '57,104', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '57,516', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '57,516', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '57,718', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '57,739', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '47', '57,833', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '57,834', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '57,859', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '57,881', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '58,479', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '58,479', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '58,508', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '47', '58,508', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '58,521', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '58,552', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)]']\n", "['2020-07-29 09', '47', '58,552', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '58,552', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '58,578', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '58,692', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '58,693', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '58,708', 'INFO', 'Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)']\n", "['2020-07-29 09', '47', '58,708', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '47', '58,714', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '58,735', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '59,302', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '59,421', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '59,422', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '59,443', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '59,444', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '59,489', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '59,672', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '59,672', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '59,674', 'INFO', \"save_model(model=RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '59,674', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '59,703', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '59,789', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '59,796', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '59,811', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '47', '59,812', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '59,812', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '59,813', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '59,813', 'INFO', 'Copying data']\n", "['2020-07-29 09', '47', '59,813', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '47', '59,814', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '59,849', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '47', '59,850', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '47', '59,850', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '47', '59,851', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '59,851', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '47', '59,858', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '59,859', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '59,860', 'INFO', 'Input provided', 'dataframe']\n", "['2020-07-29 09', '47', '59,860', 'INFO', 'session_id set to', '123']\n", "['2020-07-29 09', '47', '59,860', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '47', '59,864', 'INFO', 'Importing stopwords from nltk']\n", "['2020-07-29 09', '47', '59,876', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '47', '59,891', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '47', '59,897', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '47', '59,977', 'INFO', 'Initializing Extra Trees Regressor']\n", "['2020-07-29 09', '47', '59,992', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '48', '00,014', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '00,280', 'INFO', 'No custom stopwords defined']\n", "['2020-07-29 09', '48', '00,282', 'INFO', 'Removing numeric characters from the text']\n", "['2020-07-29 09', '48', '00,441', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '00,553', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '00,554', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '00,576', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '48', '00,594', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '00,820', 'INFO', 'Removing special characters from the text']\n", "['2020-07-29 09', '48', '01,075', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '01,191', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '01,192', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '01,219', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '48', '01,241', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '01,696', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '01,807', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '01,807', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '01,823', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '48', '01,836', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '02,159', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '02,269', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '02,270', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '02,285', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '48', '02,305', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '02,353', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '48', '02,353', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '02,353', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '02,354', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '02,421', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '48', '02,422', 'INFO', 'Isolation Forest Imported succesfully']\n", "['2020-07-29 09', '48', '02,449', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '02,813', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '02,928', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '02,929', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '02,953', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '48', '02,954', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '48', '03,011', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '03,241', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '03,242', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '03,244', 'INFO', \"save_model(model=ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '03,244', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '03,413', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '03,441', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '48', '03,441', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '03,442', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '03,744', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '03,753', 'INFO', 'Initializing AdaBoost Regressor']\n", "['2020-07-29 09', '48', '03,780', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '48', '03,810', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '03,946', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '03,960', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '03,961', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '03,961', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '03,961', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '03,962', 'INFO', \"save_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '03,962', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '03,999', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '48', '04,028', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,118', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,126', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,127', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,146', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '48', '04,165', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,169', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '04,188', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)]']\n", "['2020-07-29 09', '48', '04,188', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,189', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '04,228', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,238', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,238', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,265', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '48', '04,290', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,301', 'INFO', \"IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)']\n", "['2020-07-29 09', '48', '04,301', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,317', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '48', '04,318', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '04,318', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '04,318', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '04,350', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,360', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,360', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,389', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '48', '04,395', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '48', '04,396', 'INFO', 'k-Nearest Neighbors Detector Imported succesfully']\n", "['2020-07-29 09', '48', '04,412', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,415', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,484', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '04,484', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,494', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,494', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,518', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '48', '04,519', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '48', '04,583', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '04,697', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '04,698', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '04,699', 'INFO', \"save_model(model=KNN(algorithm='auto', contamination=0.1, leaf_size=30, method='largest',\"]\n", "[\"metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2,\"]\n", "['radius=1.0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '04,700', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '04,725', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '04,747', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KNN(algorithm='auto', contamination=0.1, leaf_size=30, method='largest',\"]\n", "[\"metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2,\"]\n", "['radius=1.0)]']\n", "['2020-07-29 09', '48', '04,747', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,748', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '04,794', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '04,794', 'INFO', 'Initializing save_model()']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '48', '04,795', 'INFO', \"save_model(model=AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',\"]\n", "['n_estimators=50, random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '04,796', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '04,831', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '04,855', 'INFO', \"KNN(algorithm='auto', contamination=0.1, leaf_size=30, method='largest',\"]\n", "[\"metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2,\"]\n", "['radius=1.0)']\n", "['2020-07-29 09', '48', '04,855', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,856', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',\"]\n", "['n_estimators=50, random_state=123), None]']\n", "['2020-07-29 09', '48', '04,856', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,856', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '04,871', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '04,873', 'INFO', \"assign_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), transformation=False, score=True, verbose=True)']\n", "['2020-07-29 09', '48', '04,873', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '04,874', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '04,876', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '04,952', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '04,953', 'INFO', 'Trained Model', 'Assigned Isolation Forest']\n", "['2020-07-29 09', '48', '04,956', 'INFO', '(1000, 12)']\n", "['2020-07-29 09', '48', '04,957', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '05,009', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '05,010', 'INFO', \"plot_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), plot=tsne, feature=None, save=False, system=True)']\n", "['2020-07-29 09', '48', '05,011', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '05,011', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '05,796', 'INFO', 'Tokenizing Words']\n", "['2020-07-29 09', '48', '06,772', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-29 09', '48', '06,773', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '06,773', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '07,650', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '07,651', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=distribution, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '07,652', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '07,652', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '07,672', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '48', '07,672', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '07,672', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '07,674', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '48', '07,674', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '07,675', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '07,675', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '07,676', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '07,711', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '07,713', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '07,714', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '48', '07,714', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '07,715', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '07,715', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '07,732', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '08,329', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-29 09', '48', '08,329', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '08,329', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '08,812', 'INFO', 'plot type', 'tsne']\n", "['2020-07-29 09', '48', '08,813', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '08,813', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '08,814', 'INFO', \"assign_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), transformation=True, score=False, verbose=False)']\n", "['2020-07-29 09', '48', '08,814', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '08,815', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '08,815', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '08,849', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '08,850', 'INFO', 'Trained Model', 'Assigned Isolation Forest']\n", "['2020-07-29 09', '48', '08,851', 'INFO', '(1000, 11)']\n", "['2020-07-29 09', '48', '08,851', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '08,852', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '08,870', 'INFO', 'Getting dummies to cast categorical variables']\n", "['2020-07-29 09', '48', '08,885', 'INFO', 'Fitting TSNE()']\n", "['2020-07-29 09', '48', '09,534', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '09,535', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=elbow, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '09,535', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '09,536', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '09,562', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '48', '09,834', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '48', '11,999', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '13,890', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-29 09', '48', '13,890', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '13,891', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '13,931', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-29 09', '48', '13,932', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '13,932', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '13,934', 'INFO', \"save_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '13,934', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '13,953', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '13,975', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)]']\n", "['2020-07-29 09', '48', '13,975', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '13,976', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '14,077', 'INFO', \"KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)']\n", "['2020-07-29 09', '48', '14,078', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '14,099', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '48', '14,100', 'INFO', 'create_model(model=kmodes, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-29 09', '48', '14,100', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '14,101', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '14,102', 'INFO', 'Setting num_cluster param']\n", "['2020-07-29 09', '48', '14,102', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '14,162', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '48', '14,178', 'INFO', 'K-Modes Clustering Imported succesfully']\n", "['2020-07-29 09', '48', '14,201', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '20,873', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '20,911', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-29 09', '48', '20,919', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '21,190', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-29 09', '48', '21,190', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '21,192', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=cluster, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '21,192', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '21,192', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '21,221', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '48', '21,221', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '21,221', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '21,223', 'INFO', \"assign_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '21,223', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '21,223', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '21,224', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '21,224', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '21,225', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '21,271', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '21,273', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-29 09', '48', '21,274', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '21,274', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '21,275', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '21,292', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '48', '21,315', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '21,323', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '21,784', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-29 09', '48', '21,784', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '21,785', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '21,905', 'INFO', 'Removing stopwords']\n", "['2020-07-29 09', '48', '23,356', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '23,357', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=distribution, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '23,357', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '23,357', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '23,386', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '48', '23,387', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '23,387', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '23,388', 'INFO', \"assign_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '48', '23,388', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '23,388', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '23,388', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '23,391', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '23,427', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '23,428', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-29 09', '48', '23,429', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '48', '23,429', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '23,429', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '23,430', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '23,439', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '24,069', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-29 09', '48', '24,069', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '24,070', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '25,580', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '25,582', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=elbow, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '25,582', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '25,582', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '25,604', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '48', '25,658', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '48', '32,253', 'INFO', 'Extracting Bigrams']\n", "['2020-07-29 09', '48', '41,062', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '41,646', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-29 09', '48', '41,646', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '41,646', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '41,692', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-29 09', '48', '41,692', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '41,693', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '41,694', 'INFO', \"save_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '41,694', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '42,305', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '42,330', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0)]']\n", "['2020-07-29 09', '48', '42,330', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,330', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '42,451', 'INFO', \"KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0)']\n", "['2020-07-29 09', '48', '42,451', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,468', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '42,469', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=True)']\n", "['2020-07-29 09', '48', '42,470', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '42,470', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '42,470', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '42,472', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '42,563', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '42,573', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '42,576', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '48', '42,577', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,694', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '42,695', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '48', '42,696', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '42,696', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '42,737', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '48', '42,737', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '42,738', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '42,739', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '42,740', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '42,740', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '42,740', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '42,741', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '42,741', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '42,782', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '42,788', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '42,789', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '42,789', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,790', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '42,805', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '48', '42,824', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '42,833', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '43,140', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '43,140', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,154', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '43,156', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=Country Name, label=True, save=False, system=True)']\n", "['2020-07-29 09', '48', '43,156', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,157', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '43,186', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '48', '43,188', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '43,188', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '43,192', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '43,192', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,193', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '43,193', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '43,194', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '43,194', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '43,230', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '43,232', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '43,233', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '43,233', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,233', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '43,246', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '48', '43,268', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '43,274', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '43,585', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '43,585', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,599', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '43,601', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=tsne, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '48', '43,602', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,602', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '43,658', 'INFO', 'plot type', 'tsne']\n", "['2020-07-29 09', '48', '43,659', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '43,659', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '43,661', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '43,662', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,662', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '43,663', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '43,664', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '43,664', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '43,711', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '43,713', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '43,714', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '43,714', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,714', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '43,718', 'INFO', 'Fitting TSNE()']\n", "['2020-07-29 09', '48', '49,461', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '59,261', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '59,268', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '59,625', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '59,626', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '59,656', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '59,658', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=elbow, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '48', '59,658', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '59,658', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '59,688', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '48', '59,688', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '49', '01,501', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '49', '01,501', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '01,532', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '49', '01,533', 'INFO', \"plot_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), plot=umap, feature=None, save=False, system=True)']\n", "['2020-07-29 09', '49', '01,533', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '49', '01,533', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '49', '01,555', 'INFO', 'plot type', 'umap']\n", "['2020-07-29 09', '49', '01,556', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '49', '01,556', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '49', '01,556', 'INFO', \"assign_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), transformation=True, score=False, verbose=False)']\n", "['2020-07-29 09', '49', '01,557', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '49', '01,557', 'INFO', 'Copying data']\n", "['2020-07-29 09', '49', '01,558', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '49', '01,588', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '49', '01,589', 'INFO', 'Trained Model', 'Assigned Isolation Forest']\n", "['2020-07-29 09', '49', '01,590', 'INFO', '(1000, 11)']\n", "['2020-07-29 09', '49', '01,590', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '01,590', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '49', '01,598', 'INFO', 'Getting dummies to cast categorical variables']\n", "['2020-07-29 09', '49', '02,407', 'INFO', 'Extracting Trigrams']\n", "['2020-07-29 09', '49', '05,305', 'INFO', 'Fitting UMAP()']\n", "['2020-07-29 09', '49', '14,048', 'INFO', 'PyCaret Regression Module']\n", "['2020-07-29 09', '49', '14,048', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '49', '14,048', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'USI', 'd354']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'setup(data=(1338, 7), target=charges, train_size=0.7, sampling=True, sample_estimator=None, categorical_features=None, categorical_imputation=constant, ordinal_features=None,']\n", "['high_cardinality_features=None, high_cardinality_method=frequency, numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=None, normalize=False,']\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None, remove_outliers=False, outliers_threshold=0.05,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, remove_perfect_collinearity=False, create_clusters=False, cluster_iter=20,']\n", "['polynomial_features=False, polynomial_degree=2, trigonometry_features=False, polynomial_threshold=0.1, group_features=None,']\n", "['group_names=None, feature_selection=False, feature_selection_threshold=0.8, feature_interaction=False, feature_ratio=False, interaction_threshold=0.01, transform_target=False,']\n", "['transform_target_method=box-cox, data_split_shuffle=True, folds_shuffle=False, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=insurance1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '49', '14,050', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '49', '14,050', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '49', '14,050', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Memory', 'svmem(total=17032478720, available=5629382656, percent=66.9, used=11403096064, free=5629382656)']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '49', '14,098', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '49', '14,935', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '49', '15,080', 'INFO', 'xgboost==1.1.1']\n", "['2020-07-29 09', '49', '15,220', 'INFO', 'lightgbm==2.3.1']\n", "['2020-07-29 09', '49', '15,339', 'INFO', 'catboost==0.23.2']\n", "['2020-07-29 09', '49', '16,374', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '49', '16,375', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '49', '16,375', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '49', '16,375', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '49', '16,408', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '49', '19,757', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '49', '19,758', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '49', '19,777', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '49', '19,777', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '49', '21,005', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '49', '22,813', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '49', '22,813', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '22,814', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '49', '22,818', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '49', '22,997', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '49', '23,497', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '23,497', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '23,514', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '49', '23,514', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '23,528', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '23,556', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), None]']\n", "['2020-07-29 09', '49', '23,557', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '23,557', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'create_model_container', '0']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'master_model_container', '0']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'display_container', '0']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '49', '25,845', 'INFO', 'Initializing compare_models()']\n", "['2020-07-29 09', '49', '25,845', 'INFO', 'compare_models(blacklist=None, whitelist=None, fold=5, round=4, sort=R2, n_select=1, turbo=True, verbose=True)']\n", "['2020-07-29 09', '49', '25,845', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '49', '25,846', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '49', '25,846', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '49', '25,953', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '49', '25,957', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '49', '25,997', 'INFO', 'Importing untrained models']\n", "['2020-07-29 09', '49', '26,001', 'INFO', 'Import successful']\n", "['2020-07-29 09', '49', '26,023', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '49', '26,023', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '49', '26,023', 'INFO', 'Initializing Linear Regression']\n", "['2020-07-29 09', '49', '26,050', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '26,072', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,081', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,097', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,098', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,243', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '26,280', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,291', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,298', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,298', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,372', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '26,407', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,424', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,430', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,430', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,489', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '26,529', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,542', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,547', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,547', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,627', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '26,685', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,695', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,701', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,702', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,784', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '26,787', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '26,947', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '27,492', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '27,492', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '27,496', 'INFO', 'save_model(model=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '27,496', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '27,584', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '27,637', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", 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completed......................................']\n", "['2020-07-29 09', '49', '27,638', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '27,641', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '49', '27,775', 'INFO', 'Initializing Lasso Regression']\n", "['2020-07-29 09', '49', '27,790', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '27,809', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '27,819', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '27,824', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '27,824', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '27,842', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '27,862', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '27,871', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '27,876', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '27,876', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '27,899', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '27,909', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '49', '27,910', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '27,921', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '27,931', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '27,939', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '27,939', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '27,968', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '27,993', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,006', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,013', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,014', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,044', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '28,072', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,083', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,091', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,091', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,118', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '28,119', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '28,162', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '28,366', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '28,367', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '28,367', 'INFO', 'save_model(model=Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '28,368', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '28,392', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '28,410', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '49', '28,410', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '28,410', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '28,583', 'INFO', 'Initializing Ridge Regression']\n", "['2020-07-29 09', '49', '28,598', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '28,599', 'INFO', \"save_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), model_name=iforest, verbose=True)']\n", "['2020-07-29 09', '49', '28,600', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '28,607', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '28,630', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,638', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,645', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,645', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,663', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '28,682', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,692', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,697', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,697', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,720', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '28,744', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,752', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,758', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,759', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,766', 'INFO', 'iforest.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '28,782', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '28,787', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)]']\n", "['2020-07-29 09', '49', '28,788', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '28,808', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,818', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,826', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,826', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,853', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '28,878', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,886', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,893', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,893', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,917', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '28,918', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '28,963', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '29,109', 'INFO', 'Initializing deploy_model()']\n", "['2020-07-29 09', '49', '29,111', 'INFO', \"deploy_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "[\"random_state=123, verbose=0), model_name=iforest-aws, authentication={'bucket'\", \"'pycaret-test'}, platform=aws)\"]\n", "['2020-07-29 09', '49', '29,111', 'INFO', 'Platform', 'AWS S3']\n", "['2020-07-29 09', '49', '29,245', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '29,245', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '29,246', 'INFO', 'save_model(model=Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '29,247', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '29,272', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '29,288', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), None]\"]\n", "['2020-07-29 09', '49', '29,289', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '29,289', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '29,429', 'INFO', 'Saving model in current working directory']\n", "['2020-07-29 09', '49', '29,430', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '29,430', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '29,430', 'INFO', \"save_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), model_name=iforest-aws, verbose=False)']\n", "['2020-07-29 09', '49', '29,431', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '29,481', 'INFO', 'Initializing Elastic Net']\n", "['2020-07-29 09', '49', '29,503', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '29,528', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,540', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,545', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,546', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,573', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '29,595', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,606', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,614', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,615', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,654', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '29,677', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,689', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,697', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,697', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,698', 'INFO', 'iforest-aws.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '29,722', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)]']\n", "['2020-07-29 09', '49', '29,722', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '29,723', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '29,723', 'INFO', 'Initializing S3 client']\n", "['2020-07-29 09', '49', '29,729', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '29,755', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,767', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,776', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,776', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,804', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '29,831', 'INFO', 'Fitting Model']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '49', '29,843', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,850', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,850', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,888', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '29,891', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '29,955', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '30,209', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '30,210', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '30,211', 'INFO', 'save_model(model=ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,']\n", "['max_iter=1000, normalize=False, positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '30,211', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '30,234', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '30,256', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,']\n", "['max_iter=1000, normalize=False, positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '49', '30,256', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '30,257', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '30,444', 'INFO', 'Initializing Least Angle Regression']\n", "['2020-07-29 09', '49', '30,464', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '30,487', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,514', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,521', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,521', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,546', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '30,571', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,595', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,600', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,600', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,630', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '30,652', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,670', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,677', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,678', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,704', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '30,731', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,752', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,759', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,759', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,783', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '30,813', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,830', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,838', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,839', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,858', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '30,859', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '30,898', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '31,084', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '31,084', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '31,085', 'INFO', 'save_model(model=Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '31,085', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '31,100', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '31,113', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), None]']\n", "['2020-07-29 09', '49', '31,114', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,114', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '31,259', 'INFO', 'Initializing Lasso Least Angle Regression']\n", "['2020-07-29 09', '49', '31,273', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '31,290', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,303', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,307', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,307', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,322', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '31,337', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,349', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,353', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,354', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,371', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '31,385', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,397', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,401', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,401', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,418', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '31,435', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,447', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,454', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,454', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,476', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '31,493', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,505', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,510', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,510', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,533', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '31,535', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '31,571', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '31,659', 'INFO', \"IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)']\n", "['2020-07-29 09', '49', '31,660', 'INFO', 'deploy_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,676', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '49', '31,677', 'INFO', 'get_config(variable=X)']\n", "['2020-07-29 09', '49', '31,677', 'INFO', 'Global variable', 'X returned']\n", "['2020-07-29 09', '49', '31,678', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,728', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '49', '31,729', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-29 09', '49', '31,729', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-29 09', '49', '31,729', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,747', 'INFO', 'Initializing set_config()']\n", "['2020-07-29 09', '49', '31,748', 'INFO', 'set_config(variable=seed, value=999)']\n", "['2020-07-29 09', '49', '31,748', 'INFO', 'Global variable', 'seed updated']\n", "['2020-07-29 09', '49', '31,748', 'INFO', 'set_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,762', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '49', '31,763', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-29 09', '49', '31,764', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-29 09', '49', '31,764', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,768', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '31,768', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '31,770', 'INFO', 'save_model(model=LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '31,770', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '31,804', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '31,838', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), None]\"]\n", "['2020-07-29 09', '49', '31,838', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,839', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '32,048', 'INFO', 'Initializing Orthogonal Matching Pursuit']\n", "['2020-07-29 09', '49', '32,071', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '32,100', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '32,114', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '32,120', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '32,121', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '32,149', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '32,171', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '32,182', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '32,189', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '32,190', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '32,214', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '32,239', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '32,251', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '32,259', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '32,259', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '32,293', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '32,320', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '32,332', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '32,339', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '32,340', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '32,364', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '32,391', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '32,401', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '32,410', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '32,410', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '32,438', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '32,439', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '32,496', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '32,721', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '32,721', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '32,722', 'INFO', 'save_model(model=OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,']\n", "[\"normalize=True, precompute='auto', tol=None), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '32,723', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '32,747', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '32,777', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,']\n", "[\"normalize=True, precompute='auto', tol=None), None]\"]\n", "['2020-07-29 09', '49', '32,778', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '32,778', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '33,009', 'INFO', 'Initializing Bayesian Ridge']\n", "['2020-07-29 09', '49', '33,039', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '33,069', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '33,090', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '33,097', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '33,097', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '33,123', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '33,148', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '33,166', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '33,174', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '33,174', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '33,201', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '33,231', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '33,253', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '33,263', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '33,264', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '33,299', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '33,329', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '33,346', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '33,355', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '33,356', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '33,388', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '33,414', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '33,433', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '33,441', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '33,441', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '33,467', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '33,469', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '33,543', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '33,846', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '33,846', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '33,848', 'INFO', 'save_model(model=BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,']\n", "['compute_score=False, copy_X=True, fit_intercept=True,']\n", "['lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,']\n", "['normalize=False, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '33,848', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '33,884', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '33,914', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,']\n", "['compute_score=False, copy_X=True, fit_intercept=True,']\n", "['lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,']\n", "['normalize=False, tol=0.001, verbose=False), None]']\n", "['2020-07-29 09', '49', '33,914', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '33,914', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '34,122', 'INFO', 'Initializing Passive Aggressive Regressor']\n", "['2020-07-29 09', '49', '34,147', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '34,176', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '34,202', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '34,208', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '34,208', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '34,230', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '34,248', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '34,269', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '34,274', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '34,275', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '34,299', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '34,327', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '34,354', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '34,362', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '34,363', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '34,396', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '34,425', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '34,454', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '34,458', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '34,459', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '34,488', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '34,517', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '34,543', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '34,551', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '34,552', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '34,582', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '34,584', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '34,638', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '34,855', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '34,855', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '34,857', 'INFO', 'save_model(model=PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,']\n", "['epsilon=0.1, fit_intercept=True,']\n", "[\"loss='epsilon_insensitive', max_iter=1000,\"]\n", "['n_iter_no_change=5, random_state=123, shuffle=True,']\n", "['tol=0.001, validation_fraction=0.1, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '34,857', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '34,884', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '34,912', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,']\n", "['epsilon=0.1, fit_intercept=True,']\n", "[\"loss='epsilon_insensitive', max_iter=1000,\"]\n", "['n_iter_no_change=5, random_state=123, shuffle=True,']\n", "['tol=0.001, validation_fraction=0.1, verbose=0,']\n", "['warm_start=False), None]']\n", "['2020-07-29 09', '49', '34,912', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '34,912', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '35,070', 'INFO', 'Initializing Random Sample Consensus']\n", "['2020-07-29 09', '49', '35,086', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '35,110', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '35,317', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '35,323', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '35,324', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '35,341', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '35,357', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '35,576', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '35,580', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '35,581', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '35,600', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '35,617', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '35,900', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '35,907', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '35,908', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '35,938', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '35,965', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '36,277', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '36,283', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '36,283', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '36,307', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '36,328', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '36,615', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '36,620', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '36,620', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '36,638', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '36,639', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '36,682', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '36,866', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '36,866', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '36,867', 'INFO', 'save_model(model=RANSACRegressor(base_estimator=None, is_data_valid=None, is_model_valid=None,']\n", "[\"loss='absolute_loss', max_skips=inf, max_trials=100,\"]\n", "['min_samples=0.5, random_state=123, residual_threshold=None,']\n", "['stop_n_inliers=inf, stop_probability=0.99, stop_score=inf), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '36,867', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '36,881', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '36,893', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RANSACRegressor(base_estimator=None, is_data_valid=None, is_model_valid=None,']\n", "[\"loss='absolute_loss', max_skips=inf, max_trials=100,\"]\n", "['min_samples=0.5, random_state=123, residual_threshold=None,']\n", "['stop_n_inliers=inf, stop_probability=0.99, stop_score=inf), None]']\n", "['2020-07-29 09', '49', '36,893', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '36,894', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '37,043', 'INFO', 'Initializing TheilSen Regressor']\n", "['2020-07-29 09', '49', '37,062', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '37,081', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '45,284', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '45,289', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '45,289', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '45,308', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '45,327', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '47,087', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '47,092', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '47,093', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '47,110', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '47,130', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '48,914', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '48,918', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '48,919', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '48,938', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '48,960', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '50,969', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '50,974', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '50,974', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '50,997', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '51,022', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '52,626', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '52,633', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '52,633', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '52,651', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '52,651', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '52,706', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '53,189', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '53,190', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '53,191', 'INFO', 'save_model(model=TheilSenRegressor(copy_X=True, fit_intercept=True, max_iter=300,']\n", "['max_subpopulation=10000, n_jobs=-1, n_subsamples=None,']\n", "['random_state=123, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '53,191', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '53,205', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '53,219', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), TheilSenRegressor(copy_X=True, fit_intercept=True, max_iter=300,']\n", "['max_subpopulation=10000, n_jobs=-1, n_subsamples=None,']\n", "['random_state=123, tol=0.001, verbose=False), None]']\n", "['2020-07-29 09', '49', '53,220', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '53,220', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '53,380', 'INFO', 'Initializing Huber Regressor']\n", "['2020-07-29 09', '49', '53,393', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '53,418', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '53,583', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '53,587', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '53,587', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '53,608', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '53,627', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '53,750', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '53,755', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '53,755', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '53,775', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '53,797', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '53,937', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '53,943', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '53,944', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '53,964', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '53,987', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '54,134', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '54,141', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '54,141', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '54,160', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '54,180', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '54,320', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '54,325', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '54,326', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '54,347', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '54,348', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '54,389', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '54,547', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '54,547', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '54,547', 'INFO', 'save_model(model=HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,']\n", "['tol=1e-05, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '54,548', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '54,560', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '54,572', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,']\n", "['tol=1e-05, warm_start=False), None]']\n", "['2020-07-29 09', '49', '54,573', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '54,573', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '54,742', 'INFO', 'Initializing Support Vector Machine']\n", "['2020-07-29 09', '49', '54,758', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '54,775', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '54,906', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '54,927', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '54,928', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '54,956', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '54,983', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '55,088', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '55,109', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '55,109', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '55,136', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '55,173', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '55,286', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '55,308', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '55,309', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '55,353', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '55,376', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '55,499', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '55,525', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '55,525', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '55,579', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '55,643', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '55,789', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '55,814', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '55,815', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '55,874', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '55,877', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '55,972', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '56,261', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '56,261', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '56,263', 'INFO', \"save_model(model=SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\"]\n", "[\"kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '56,263', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '56,290', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '56,309', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\"]\n", "[\"kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False), None]\"]\n", "['2020-07-29 09', '49', '56,309', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '56,310', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '56,443', 'INFO', 'Initializing K Neighbors Regressor']\n", "['2020-07-29 09', '49', '56,461', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '56,479', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '56,490', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '56,608', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '56,608', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '56,633', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '56,648', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '56,658', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '56,771', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '56,772', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '56,792', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '56,812', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '56,829', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '56,946', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '56,946', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '56,965', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '56,984', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '56,995', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,106', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '57,107', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,121', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '57,136', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '57,143', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,254', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '57,254', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,273', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '57,273', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '57,305', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '57,442', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '57,442', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '57,443', 'INFO', \"save_model(model=KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform'), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '57,443', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '57,456', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '57,468', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform'), None]\"]\n", "['2020-07-29 09', '49', '57,469', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '57,469', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '57,561', 'INFO', 'Initializing Decision Tree']\n", "['2020-07-29 09', '49', '57,572', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '57,586', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '57,595', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,599', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '57,599', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,611', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '57,626', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '57,641', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,646', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '57,647', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,671', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '57,697', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '57,714', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,720', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '57,721', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,747', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '57,776', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '57,794', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,802', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '57,802', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,827', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '57,844', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '57,856', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '57,861', 'INFO', 'No inverse transformer found']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '49', '57,861', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '57,880', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '57,882', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '57,920', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '58,087', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '58,088', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '58,089', 'INFO', \"save_model(model=DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "[\"min_weight_fraction_leaf=0.0, presort='deprecated',\"]\n", "[\"random_state=123, splitter='best'), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '58,090', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '58,105', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '58,125', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "[\"min_weight_fraction_leaf=0.0, presort='deprecated',\"]\n", "[\"random_state=123, splitter='best'), None]\"]\n", "['2020-07-29 09', '49', '58,126', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '58,126', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '58,253', 'INFO', 'Initializing Random Forest']\n", "['2020-07-29 09', '49', '58,267', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '58,286', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '58,838', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '58,950', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '58,951', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '58,967', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '58,988', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '59,551', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '59,666', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '59,667', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '59,693', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '59,726', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '00,434', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '00,551', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '00,552', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '00,569', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '00,585', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '01,120', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '01,231', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '01,232', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '01,249', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '01,269', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '01,827', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '01,937', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '01,937', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '01,951', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '01,952', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '01,989', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '02,150', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '02,150', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '02,151', 'INFO', \"save_model(model=RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '02,151', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '02,248', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '02,262', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '50', '02,263', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '02,263', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '02,392', 'INFO', 'Initializing Extra Trees Regressor']\n", "['2020-07-29 09', '50', '02,406', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '02,420', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '02,827', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '02,938', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '02,938', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '02,953', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '02,969', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '03,270', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '03,380', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '03,380', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '03,395', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '03,411', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '03,707', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '03,821', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '03,821', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '03,841', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '03,855', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '04,177', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '04,286', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '04,286', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '04,302', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '04,315', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '04,609', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '04,719', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '04,719', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '04,731', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '04,732', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '04,773', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '04,942', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '04,942', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '04,943', 'INFO', \"save_model(model=ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '04,943', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '05,031', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '05,043', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '50', '05,043', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '05,043', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '05,162', 'INFO', 'Initializing AdaBoost Regressor']\n", "['2020-07-29 09', '50', '05,174', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '05,191', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '05,255', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '05,260', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '05,260', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '05,273', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '05,288', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '05,331', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '05,337', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '05,337', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '05,349', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '05,363', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '05,396', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '05,402', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '05,402', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '05,416', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '05,434', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '05,466', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '05,471', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '05,472', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '05,486', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '05,500', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '05,548', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '05,555', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '05,555', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '05,569', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '05,570', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '05,608', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '05,786', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '05,786', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '05,786', 'INFO', \"save_model(model=AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',\"]\n", "['n_estimators=50, random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '05,786', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '05,802', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '05,813', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',\"]\n", "['n_estimators=50, random_state=123), None]']\n", "['2020-07-29 09', '50', '05,813', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '05,814', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '05,897', 'INFO', 'Initializing Gradient Boosting Regressor']\n", "['2020-07-29 09', '50', '05,908', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '05,922', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '06,084', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '06,089', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '06,089', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '06,101', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '06,113', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '06,270', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '06,273', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '06,273', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '06,285', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '06,299', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '06,448', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '06,452', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '06,452', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '06,464', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '06,479', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '06,630', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '06,634', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '06,634', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '06,645', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '06,659', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '06,809', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '06,813', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '06,813', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '06,824', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '06,825', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '06,856', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '07,002', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '07,002', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '07,003', 'INFO', \"save_model(model=GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='friedman_mse',\"]\n", "[\"init=None, learning_rate=0.1, loss='ls', max_depth=3,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=100,']\n", "[\"n_iter_no_change=None, presort='deprecated',\"]\n", "['random_state=123, subsample=1.0, tol=0.0001,']\n", "['validation_fraction=0.1, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '07,003', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '07,018', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '07,028', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='friedman_mse',\"]\n", "[\"init=None, learning_rate=0.1, loss='ls', max_depth=3,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=100,']\n", "[\"n_iter_no_change=None, presort='deprecated',\"]\n", "['random_state=123, subsample=1.0, tol=0.0001,']\n", "['validation_fraction=0.1, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '50', '07,029', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '07,029', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '07,161', 'INFO', 'Initializing Extreme Gradient Boosting']\n", "['2020-07-29 09', '50', '07,173', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '07,190', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '07,362', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '07,368', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '07,369', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '07,394', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '07,416', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '07,586', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '07,592', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '07,592', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '07,620', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '07,643', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '07,828', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '07,834', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '07,834', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '07,863', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '07,887', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '08,074', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '08,081', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '08,081', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '08,110', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '08,135', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '08,339', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '08,346', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '08,346', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '08,375', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '08,376', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '08,448', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '08,679', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '08,680', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '08,686', 'INFO', \"save_model(model=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,']\n", "[\"importance_type='gain', interaction_constraints='',\"]\n", "['learning_rate=0.300000012, max_delta_step=0, max_depth=6,']\n", "[\"min_child_weight=1, missing=nan, monotone_constraints='()',\"]\n", "['n_estimators=100, n_jobs=-1, num_parallel_tree=1,']\n", "[\"objective='reg\", \"squarederror', random_state=123, reg_alpha=0,\"]\n", "[\"reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method='exact',\"]\n", "['validate_parameters=1, verbosity=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '08,686', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '08,711', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '08,730', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,']\n", "[\"importance_type='gain', interaction_constraints='',\"]\n", "['learning_rate=0.300000012, max_delta_step=0, max_depth=6,']\n", "[\"min_child_weight=1, missing=nan, monotone_constraints='()',\"]\n", "['n_estimators=100, n_jobs=-1, num_parallel_tree=1,']\n", "[\"objective='reg\", \"squarederror', random_state=123, reg_alpha=0,\"]\n", "[\"reg_lambda=1, scale_pos_weight=1, subsample=1, tree_method='exact',\"]\n", "['validate_parameters=1, verbosity=0), None]']\n", "['2020-07-29 09', '50', '08,730', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '08,730', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '08,868', 'INFO', 'Initializing Light Gradient Boosting Machine']\n", "['2020-07-29 09', '50', '08,881', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '08,901', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '09,213', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '09,226', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '09,226', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '09,258', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '09,282', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '09,525', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '09,535', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '09,535', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '09,567', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '09,592', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '09,871', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '09,882', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '09,882', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '09,913', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '09,938', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '10,228', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '10,241', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '10,241', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '10,271', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '10,299', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '10,568', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '10,579', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '10,579', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '10,610', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '10,612', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '10,683', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '10,933', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '10,933', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '10,936', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '10,936', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '10,982', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '11,014', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '50', '11,015', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '11,015', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '11,186', 'INFO', 'Initializing CatBoost Regressor']\n", "['2020-07-29 09', '50', '11,198', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '11,213', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '15,134', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '15,140', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '15,140', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '15,156', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '15,174', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '19,173', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '19,181', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '19,181', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '19,199', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '19,214', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '20,317', 'INFO', 'PyCaret Clustering Module']\n", "['2020-07-29 09', '50', '20,317', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '50', '20,317', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '50', '20,317', 'INFO', 'USI', 'a262']\n", "['2020-07-29 09', '50', '20,318', 'INFO', 'setup(data=(224, 21), categorical_features=None, categorical_imputation=constant, ordinal_features=None, high_cardinality_features=None,']\n", "[\"numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=['Country Name'], normalize=False,\"]\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, group_features=None,']\n", "['group_names=None, supervised=False, supervised_target=None, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=health1, log_plots=True, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '50', '20,318', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '50', '20,318', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '50', '20,318', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '50', '20,318', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '50', '20,319', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '50', '20,400', 'INFO', 'Memory', 'svmem(total=17032478720, available=4871823360, percent=71.4, used=12160655360, free=4871823360)']\n", "['2020-07-29 09', '50', '20,402', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '50', '20,402', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '50', '20,402', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '50', '20,402', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '50', '20,402', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '50', '22,550', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '50', '22,554', 'INFO', 'kmodes==0.10.2']\n", "['2020-07-29 09', '50', '23,217', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '23,224', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '23,224', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '23,238', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '23,257', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '25,615', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '50', '25,615', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '50', '25,616', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '25,827', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '25,889', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '25,889', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '50', '25,889', 'INFO', 'Copying data for preprocessing']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '50', '25,902', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '50', '25,902', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '50', '27,230', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '27,237', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '27,237', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '27,252', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '27,271', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '29,232', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '50', '31,016', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '31,022', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '50', '31,022', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '31,035', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '31,036', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '31,082', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '31,207', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '31,207', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '31,207', 'INFO', 'save_model(model=, model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '31,207', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '31,227', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '31,240', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), , None]']\n", "['2020-07-29 09', '50', '31,240', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '31,240', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '31,614', 'INFO', 'Finalizing top_n models']\n", "['2020-07-29 09', '50', '31,615', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-29 09', '50', '31,630', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '50', '31,630', 'INFO', 'create_model(estimator=gbr, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-29 09', '50', '31,630', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '31,630', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '31,631', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '31,652', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '50', '31,653', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '31,655', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '50', '31,655', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '50', '31,656', 'INFO', 'Gradient Boosting Regressor Imported succesfully']\n", "['2020-07-29 09', '50', '31,657', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '50', '31,659', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '31,662', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '31,827', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '31,831', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '31,832', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '31,846', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '31,848', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '32,015', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '32,017', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '32,018', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '32,029', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '32,031', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '32,183', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '32,187', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '32,187', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '32,198', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '32,201', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '32,348', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '32,351', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '32,352', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '32,362', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '32,364', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '32,528', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '32,532', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '32,532', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '32,544', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '50', '32,547', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '32,700', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '32,704', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '32,704', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '32,714', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '50', '32,716', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '32,866', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '32,869', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '32,869', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '32,881', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '50', '32,885', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '33,045', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '33,049', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '33,050', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '33,061', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '50', '33,064', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '33,222', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '33,225', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '33,226', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '33,235', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '50', '33,237', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '33,386', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '33,389', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '33,389', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '33,399', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '33,400', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '33,408', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '50', '33,570', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '50', '33,570', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '50', '33,570', 'INFO', 'create_model_container', '1']\n", "['2020-07-29 09', '50', '33,571', 'INFO', 'master_model_container', '1']\n", "['2020-07-29 09', '50', '33,571', 'INFO', 'display_container', '1']\n", "['2020-07-29 09', '50', '33,572', 'INFO', \"GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='friedman_mse',\"]\n", "[\"init=None, learning_rate=0.1, loss='ls', max_depth=3,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=100,']\n", "[\"n_iter_no_change=None, presort='deprecated',\"]\n", "['random_state=123, subsample=1.0, tol=0.0001,']\n", "['validation_fraction=0.1, verbose=0, warm_start=False)']\n", "['2020-07-29 09', '50', '33,572', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '33,572', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-29 09', '50', '33,736', 'INFO', 'create_model_container', '1']\n", "['2020-07-29 09', '50', '33,736', 'INFO', 'master_model_container', '1']\n", "['2020-07-29 09', '50', '33,736', 'INFO', 'display_container', '2']\n", "['2020-07-29 09', '50', '33,737', 'INFO', \"GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='friedman_mse',\"]\n", "[\"init=None, learning_rate=0.1, loss='ls', max_depth=3,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=100,']\n", "[\"n_iter_no_change=None, presort='deprecated',\"]\n", "['random_state=123, subsample=1.0, tol=0.0001,']\n", "['validation_fraction=0.1, verbose=0, warm_start=False)']\n", "['2020-07-29 09', '50', '33,737', 'INFO', 'compare_models() succesfully completed......................................']\n", "['2020-07-29 09', '50', '38,592', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '50', '38,593', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-29 09', '50', '38,593', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '38,593', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '38,593', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '38,629', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '50', '38,630', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '38,631', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '50', '38,631', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '50', '38,639', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '50', '38,640', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '50', '38,647', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '38,656', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '38,849', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '38,857', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '38,857', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '38,908', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '38,925', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '39,151', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '39,159', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '39,159', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '39,219', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '39,239', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '39,508', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '39,518', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '39,518', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '39,580', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '39,603', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '39,908', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '39,919', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '39,920', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '39,994', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '40,018', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '40,307', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '40,315', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '40,316', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '40,402', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '50', '40,424', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '40,753', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '40,763', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '40,764', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '40,860', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '50', '40,885', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '41,203', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '41,212', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '41,213', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '41,289', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '50', '41,312', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '41,654', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '41,665', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '41,665', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '41,742', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '50', '41,764', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '42,039', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '42,049', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '42,050', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '42,129', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '50', '42,151', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '42,228', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '50', '42,228', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '50', '42,233', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '50', '42,511', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '42,521', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '42,521', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '42,601', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '42,606', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '42,633', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '50', '42,983', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '43,314', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '50', '43,501', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '43,502', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '43,503', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '43,504', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '43,542', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '43,572', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '50', '43,573', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '43,573', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '43,664', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '50', '43,664', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '50', '43,819', 'INFO', 'create_model_container', '2']\n", "['2020-07-29 09', '50', '43,819', 'INFO', 'master_model_container', '2']\n", "['2020-07-29 09', '50', '43,819', 'INFO', 'display_container', '3']\n", "['2020-07-29 09', '50', '43,821', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '50', '43,821', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '43,841', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '50', '43,842', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '50', '43,842', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '43,843', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '43,843', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '43,885', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '50', '43,886', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '43,889', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '50', '43,889', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '50', '43,890', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '50', '43,893', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '50', '43,895', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '43,901', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '44,135', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '44,136', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '44,171', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '50', '44,172', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '44,203', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '44,258', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country 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'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '44,437', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '44,448', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '44,448', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '44,477', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '44,483', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '44,521', 'INFO', 'Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)']\n", "['2020-07-29 09', '50', '44,521', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '50', '44,623', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '50', '44,624', 'INFO', 'create_model(model=kmeans, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-29 09', '50', '44,625', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '44,625', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '44,625', 'INFO', 'Setting num_cluster param']\n", "['2020-07-29 09', '50', '44,626', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '44,690', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '50', '44,690', 'INFO', 'K-Means Clustering Imported succesfully']\n", "['2020-07-29 09', '50', '44,711', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '44,901', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '44,946', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-29 09', '50', '44,956', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '45,024', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '45,037', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '45,038', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '45,068', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '45,074', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '45,271', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-29 09', '50', '45,271', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '50', '45,273', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '50', '45,273', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '45,273', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '45,551', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '45,564', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '45,565', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '45,597', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '45,608', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '46,101', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '46,111', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '46,112', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '46,140', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '46,145', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '46,487', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '46,498', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '46,499', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '46,530', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '50', '46,538', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '46,999', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '47,011', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '47,011', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '47,042', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '50', '47,047', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '47,395', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '47,408', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '47,408', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '47,437', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '50', '47,442', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '47,856', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '47,866', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '47,867', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '47,897', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '50', '47,905', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '48,279', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '48,290', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '48,291', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '48,325', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '50', '48,330', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '48,701', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '48,712', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '48,713', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '48,743', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '48,748', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '48,768', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '50', '49,134', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '49,651', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '49,651', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '49,652', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '49,653', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '49,697', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '49,727', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '50', '49,728', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '49,728', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '49,815', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '50', '49,815', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '50', '49,815', 'INFO', 'create_model_container', '3']\n", "['2020-07-29 09', '50', '49,815', 'INFO', 'master_model_container', '3']\n", "['2020-07-29 09', '50', '49,815', 'INFO', 'display_container', '4']\n", "['2020-07-29 09', '50', '49,817', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '50', '49,817', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '49,818', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '50', '49,818', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '50', '49,818', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '49,818', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '49,819', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '49,851', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '50', '49,852', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '49,855', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '50', '49,855', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '50', '49,857', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '50', '49,860', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '50', '49,862', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '49,868', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '50,229', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '50,237', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '50,238', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '50,268', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '50', '50,273', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '50,640', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '50,650', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '50,650', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '50,680', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '50', '50,687', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '51,379', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '50', '51,379', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '50', '51,379', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '50', '51,381', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '50', '51,381', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '51,382', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '51,382', 'INFO', 'Copying data']\n", "['2020-07-29 09', '50', '51,383', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '50', '51,383', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '51,441', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '50', '51,443', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '50', '51,443', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '50', '51,444', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '51,444', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '50', '51,481', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '50', '51,501', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '50', '51,510', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '50', '51,800', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '51,811', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '51,811', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '51,840', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '50', '51,855', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '52,980', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '52,992', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '52,993', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '53,024', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '50', '53,029', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '53,902', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '53,914', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '53,914', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '53,950', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '50', '53,955', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '54,501', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '54,512', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '54,512', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '54,544', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '50', '54,549', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '55,374', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '55,384', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '55,384', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '55,410', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '50', '55,415', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '55,458', 'INFO', 'PyCaret NLP Module']\n", "['2020-07-29 09', '50', '55,459', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '50', '55,459', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '50', '55,460', 'INFO', 'USI', '2c3d']\n", "['2020-07-29 09', '50', '55,460', 'INFO', 'setup(data=(6818, 7), target=en, custom_stopwords=None, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=kiva1, log_plots=True, log_data=False, verbose=True)']\n", "['2020-07-29 09', '50', '55,460', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '50', '55,461', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '50', '55,461', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '50', '55,461', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '50', '55,462', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '50', '55,546', 'INFO', 'Memory', 'svmem(total=17032478720, available=4700733440, percent=72.4, used=12331745280, free=4700733440)']\n", "['2020-07-29 09', '50', '55,546', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '50', '55,547', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '50', '55,547', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '50', '55,547', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '50', '55,547', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '50', '55,982', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '55,993', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '55,993', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '56,032', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '50', '56,038', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '56,505', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '56,516', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '56,516', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '56,545', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '50', '56,551', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '57,714', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '50', '57,725', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '50', '57,725', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '50', '57,754', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '50', '57,759', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '50', '57,779', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '50', '58,308', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '50', '58,410', 'INFO', 'gensim==3.8.3']\n", "['2020-07-29 09', '50', '58,896', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '50', '58,897', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '50', '58,899', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '50', '58,899', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '50', '58,945', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '50', '58,978', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '50', '58,978', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '58,979', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '50', '59,072', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '50', '59,072', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '50', '59,072', 'INFO', 'create_model_container', '4']\n", "['2020-07-29 09', '50', '59,072', 'INFO', 'master_model_container', '4']\n", "['2020-07-29 09', '50', '59,073', 'INFO', 'display_container', '5']\n", "['2020-07-29 09', '50', '59,074', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '50', '59,075', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '50', '59,075', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '50', '59,075', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '50', '59,076', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '50', '59,076', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '50', '59,076', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '50', '59,110', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '50', '59,112', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '50', '59,115', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '50', '59,115', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '50', '59,116', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '50', '59,120', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '50', '59,122', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '50', '59,129', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '50', '59,817', 'INFO', 'spacy==2.2.4']\n", "['2020-07-29 09', '51', '00,027', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '00,037', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '00,037', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '00,072', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '00,081', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '00,692', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-29 09', '51', '00,692', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '00,692', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '00,907', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '00,919', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '00,919', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '00,948', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '00,954', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '01,313', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '01,323', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '01,323', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '01,349', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '01,354', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '01,554', 'INFO', 'nltk==3.5']\n", "['2020-07-29 09', '51', '01,706', 'INFO', 'textblob==0.15.3']\n", "['2020-07-29 09', '51', '01,774', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '01,783', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '01,783', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '01,814', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '01,819', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '02,155', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '02,165', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '02,165', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '02,189', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '02,190', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=distribution, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '51', '02,191', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '02,191', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '02,194', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '02,200', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '02,220', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '51', '02,221', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '02,221', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '02,223', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '51', '02,224', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '02,224', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '02,224', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '02,225', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '02,271', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '02,273', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '51', '02,274', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '51', '02,274', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '02,274', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '02,275', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '02,294', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '02,690', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '02,701', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '02,701', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '02,728', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '02,734', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '03,122', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-29 09', '51', '03,122', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '03,122', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '03,236', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '03,240', 'INFO', 'pyLDAvis==2.1.2']\n", "['2020-07-29 09', '51', '03,244', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '03,244', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '03,273', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '03,278', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '03,482', 'INFO', 'wordcloud==1.7.0']\n", "['2020-07-29 09', '51', '03,624', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '03,636', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '03,637', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '03,663', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '03,668', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '03,979', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '03,989', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '03,989', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '04,017', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '04,023', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '04,361', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '04,371', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '04,372', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '04,400', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '04,406', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '04,424', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '04,475', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '04,477', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=elbow, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '51', '04,477', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '04,477', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '04,503', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '51', '04,642', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '51', '04,861', 'INFO', 'Creating MLFlow logs']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '51', '05,101', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '51', '05,102', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '51', '05,449', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '05,450', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '05,452', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '05,452', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '05,498', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '05,521', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '05,522', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '05,522', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '05,602', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '05,602', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '05,602', 'INFO', 'create_model_container', '5']\n", "['2020-07-29 09', '51', '05,603', 'INFO', 'master_model_container', '5']\n", "['2020-07-29 09', '51', '05,603', 'INFO', 'display_container', '6']\n", "['2020-07-29 09', '51', '05,605', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '05,606', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '05,606', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '05,606', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '51', '05,607', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '05,607', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '05,607', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '05,637', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '05,638', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '05,641', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '05,641', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '05,642', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '51', '05,643', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '05,645', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '05,651', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '05,963', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '05,971', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '05,971', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '05,997', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '06,002', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '06,313', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '06,321', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '06,322', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '06,345', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '06,349', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '06,432', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '06,700', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '06,708', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '06,709', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '06,740', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '06,744', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '07,071', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '07,080', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '07,080', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '07,101', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '07,106', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '07,403', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '07,411', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '07,411', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '07,438', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '07,443', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '07,767', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '07,781', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '07,782', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '07,808', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '07,813', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '08,123', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '08,170', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '08,179', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '08,180', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '08,189', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-29 09', '51', '08,189', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '08,189', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '08,207', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '08,211', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '08,234', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-29 09', '51', '08,234', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '08,234', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '08,236', 'INFO', \"save_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '08,236', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '08,262', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '08,273', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '08,285', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)]']\n", "['2020-07-29 09', '51', '08,285', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '08,285', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '08,344', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '08,344', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '51', '08,345', 'INFO', 'Input provided', 'dataframe']\n", "['2020-07-29 09', '51', '08,345', 'INFO', 'session_id set to', '123']\n", "['2020-07-29 09', '51', '08,347', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '08,351', 'INFO', 'Importing stopwords from nltk']\n", "['2020-07-29 09', '51', '08,398', 'INFO', \"KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)']\n", "['2020-07-29 09', '51', '08,399', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '51', '08,419', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '08,419', 'INFO', 'create_model(model=kmodes, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-29 09', '51', '08,419', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '08,420', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '08,421', 'INFO', 'Setting num_cluster param']\n", "['2020-07-29 09', '51', '08,421', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '08,484', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '51', '08,493', 'INFO', 'K-Modes Clustering Imported succesfully']\n", "['2020-07-29 09', '51', '08,516', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '08,689', 'INFO', 'No custom stopwords defined']\n", "['2020-07-29 09', '51', '08,692', 'INFO', 'Removing numeric characters from the text']\n", "['2020-07-29 09', '51', '10,128', 'INFO', 'Removing special characters from the text']\n", "['2020-07-29 09', '51', '14,072', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '14,083', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '14,083', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '14,112', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '14,120', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '14,712', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '14,721', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '14,722', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '14,747', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '14,751', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '15,185', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '15,195', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '15,196', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '15,225', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '15,233', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '15,250', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '15,429', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '15,460', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-29 09', '51', '15,467', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '15,686', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-29 09', '51', '15,687', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '15,687', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=cluster, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '51', '15,687', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '15,687', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '15,712', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '51', '15,712', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '15,712', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '15,714', 'INFO', \"assign_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '51', '15,714', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '15,714', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '15,714', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '15,715', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '51', '15,715', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '15,750', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '15,751', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-29 09', '51', '15,752', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '51', '15,752', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '15,753', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '15,768', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '51', '15,785', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '15,791', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '15,848', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '16,197', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-29 09', '51', '16,197', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '16,198', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '16,439', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '16,439', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '16,441', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '16,441', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '16,481', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '16,508', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '16,508', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '16,508', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '16,609', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '16,609', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '16,610', 'INFO', 'create_model_container', '6']\n", "['2020-07-29 09', '51', '16,610', 'INFO', 'master_model_container', '6']\n", "['2020-07-29 09', '51', '16,610', 'INFO', 'display_container', '7']\n", "['2020-07-29 09', '51', '16,612', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '16,612', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '16,613', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '16,613', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '51', '16,613', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '16,613', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '16,613', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '16,641', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '16,642', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '16,644', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '16,645', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '16,646', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '51', '16,648', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '16,650', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '16,655', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '16,986', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '16,996', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '16,996', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '17,026', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '17,032', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '17,396', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '17,407', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '17,407', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '17,433', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '17,438', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '17,523', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '17,525', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=distribution, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '51', '17,525', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '17,525', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '17,550', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '51', '17,550', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '17,551', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '17,552', 'INFO', \"assign_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '51', '17,553', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '17,553', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '17,553', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '17,554', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '17,595', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '17,597', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-29 09', '51', '17,597', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '51', '17,597', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '17,598', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '17,598', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '17,611', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '17,786', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '17,795', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '17,795', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '17,822', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '17,828', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '18,047', 'INFO', 'Tokenizing Words']\n", "['2020-07-29 09', '51', '18,251', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '18,259', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-29 09', '51', '18,259', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '18,259', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '18,259', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '18,261', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '18,286', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '18,290', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '18,650', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '18,657', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '18,658', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '18,680', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '18,685', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '19,010', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '19,019', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '19,019', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '19,041', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '19,046', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '19,353', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '19,361', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '19,361', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '19,383', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '19,387', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '19,654', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '19,655', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=elbow, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '51', '19,656', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '19,656', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '19,680', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '51', '19,722', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '19,743', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '19,744', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '19,776', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '51', '19,780', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '19,789', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '20,182', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '20,190', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '20,191', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '20,218', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '20,223', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '20,568', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '20,579', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '20,579', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '20,608', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '20,614', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '20,633', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '20,990', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '21,496', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '21,496', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '21,498', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '21,498', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '21,545', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '21,572', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '21,572', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '21,572', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '21,660', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '21,660', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '21,660', 'INFO', 'create_model_container', '7']\n", "['2020-07-29 09', '51', '21,661', 'INFO', 'master_model_container', '7']\n", "['2020-07-29 09', '51', '21,661', 'INFO', 'display_container', '8']\n", "['2020-07-29 09', '51', '21,663', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '21,663', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '21,664', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '21,664', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '51', '21,664', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '21,664', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '21,664', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '21,704', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '21,705', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '21,707', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '21,707', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '21,708', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '51', '21,711', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '21,714', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '21,719', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '22,073', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '22,082', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '22,082', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '22,110', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '22,114', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '22,485', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '22,494', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '22,495', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '22,521', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '22,526', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '22,854', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '22,863', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '22,863', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '22,886', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '22,892', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '23,201', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '23,209', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '23,209', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '23,234', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '23,239', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '23,566', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '23,577', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '23,578', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '23,604', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '23,609', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '24,001', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '24,010', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '24,011', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '24,039', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '24,045', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '24,458', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '24,469', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '24,470', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '24,497', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '24,502', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '24,843', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '24,854', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '24,855', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '24,878', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '24,883', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '25,229', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '25,237', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '25,238', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '25,260', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '25,264', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '25,610', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '25,619', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '25,620', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '25,649', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '25,654', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '25,676', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '26,031', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '26,558', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '26,558', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '26,560', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '26,561', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '26,610', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '26,641', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '26,641', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '26,641', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '26,727', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '26,728', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '26,728', 'INFO', 'create_model_container', '8']\n", "['2020-07-29 09', '51', '26,728', 'INFO', 'master_model_container', '8']\n", "['2020-07-29 09', '51', '26,728', 'INFO', 'display_container', '9']\n", "['2020-07-29 09', '51', '26,729', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '26,729', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '26,730', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '26,730', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '51', '26,730', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '26,730', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '26,730', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '26,757', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '26,758', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '26,761', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '26,761', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '26,762', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '51', '26,765', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '26,767', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '26,772', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '27,137', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '27,145', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '27,146', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '27,180', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '27,185', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '27,525', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '27,537', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '27,537', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '27,568', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '27,574', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '27,918', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '27,927', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '27,927', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '27,957', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '27,964', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '28,283', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '28,292', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '28,292', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '28,317', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '28,323', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '28,657', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '28,666', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '28,667', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '28,694', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '28,698', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '29,025', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '29,033', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '29,033', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '29,060', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '29,064', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '29,407', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '29,418', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '29,418', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '29,447', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '29,454', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '29,799', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '29,810', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '29,810', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '29,839', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '29,845', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '30,163', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '30,170', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '30,171', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '30,197', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '30,202', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '30,523', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '30,533', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '30,533', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '30,559', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '30,562', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '30,580', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '30,932', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '31,478', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '31,479', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '31,481', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '31,481', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '31,512', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '31,536', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '31,536', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '31,536', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '31,619', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '31,620', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '31,620', 'INFO', 'create_model_container', '9']\n", "['2020-07-29 09', '51', '31,620', 'INFO', 'master_model_container', '9']\n", "['2020-07-29 09', '51', '31,620', 'INFO', 'display_container', '10']\n", "['2020-07-29 09', '51', '31,622', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '31,623', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '31,623', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '31,624', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '51', '31,624', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '31,624', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '31,624', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '31,656', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '31,658', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '31,660', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '31,661', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '31,662', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '51', '31,664', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '31,667', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '31,672', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '32,036', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '32,044', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '32,044', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '32,068', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '32,073', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '32,380', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '32,391', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '32,391', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '32,418', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '32,423', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '32,741', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '32,749', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '32,750', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '32,774', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '32,779', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '33,089', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '33,096', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '33,096', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '33,122', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '33,127', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '33,448', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '33,456', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '33,456', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '33,478', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '33,482', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '33,801', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '33,811', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '33,812', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '33,838', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '33,843', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '33,875', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '34,159', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '34,168', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '34,168', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '34,193', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '34,198', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '34,434', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-29 09', '51', '34,435', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '34,435', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '34,471', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-29 09', '51', '34,472', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '34,472', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '34,473', 'INFO', \"save_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '34,473', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '34,506', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '34,514', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '34,514', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '34,537', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '34,542', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '34,842', 'INFO', 'Removing stopwords']\n", "['2020-07-29 09', '51', '34,868', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '34,879', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '34,880', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '34,904', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '34,909', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '35,141', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '35,166', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0)]']\n", "['2020-07-29 09', '51', '35,166', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '35,167', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '35,226', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '35,245', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '35,246', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '35,271', 'INFO', \"KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0)']\n", "['2020-07-29 09', '51', '35,272', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '51', '35,275', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '35,280', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '35,295', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '35,297', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=True)']\n", "['2020-07-29 09', '51', '35,297', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '35,298', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '35,298', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '35,299', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '35,300', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '35,373', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '35,375', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '51', '35,378', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '51', '35,378', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '35,468', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '35,470', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '51', '35,470', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '35,470', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '35,494', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '51', '35,494', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '35,494', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '35,496', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '51', '35,496', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '35,496', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '35,496', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '35,497', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '51', '35,497', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '35,530', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '35,532', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '51', '35,533', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '51', '35,533', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '35,534', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '35,549', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '51', '35,565', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '35,570', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '35,796', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '35,796', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '35,812', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '35,813', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=Country Name, label=True, save=False, system=True)']\n", "['2020-07-29 09', '51', '35,814', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '35,814', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '35,840', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '51', '35,841', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '35,841', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '35,842', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '51', '35,842', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '35,843', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '35,843', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '35,844', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '51', '35,844', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '35,878', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '35,880', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '51', '35,880', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '51', '35,881', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '35,881', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '35,897', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '51', '35,916', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '35,923', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '36,095', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '36,190', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '36,190', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '36,205', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '36,206', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=tsne, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '51', '36,207', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '36,207', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '36,240', 'INFO', 'plot type', 'tsne']\n", "['2020-07-29 09', '51', '36,240', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '36,240', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '36,242', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '51', '36,242', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '36,243', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '36,243', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '36,244', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '51', '36,244', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '36,287', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '36,289', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '51', '36,289', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '51', '36,290', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '36,290', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '36,294', 'INFO', 'Fitting TSNE()']\n", "['2020-07-29 09', '51', '36,736', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '36,737', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '36,739', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '36,739', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '36,784', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '36,809', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '36,809', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '36,810', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '36,901', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '36,901', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '36,901', 'INFO', 'create_model_container', '10']\n", "['2020-07-29 09', '51', '36,901', 'INFO', 'master_model_container', '10']\n", "['2020-07-29 09', '51', '36,902', 'INFO', 'display_container', '11']\n", "['2020-07-29 09', '51', '36,903', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '36,904', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '36,904', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '36,904', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=True)']\n", "['2020-07-29 09', '51', '36,905', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '36,905', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '36,905', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '36,943', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '36,944', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '36,947', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '36,948', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '36,949', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-29 09', '51', '36,952', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '36,954', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '36,958', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '37,684', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '37,692', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '37,692', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '37,716', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '37,721', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '38,429', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '38,437', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '38,437', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '38,460', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '51', '38,464', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '39,178', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '39,186', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '39,186', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '39,210', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '51', '39,215', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '39,960', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '39,968', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '39,968', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '39,992', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '51', '39,997', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '40,712', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '40,720', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '40,720', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '40,743', 'INFO', 'Initializing Fold 6']\n", "['2020-07-29 09', '51', '40,748', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '41,445', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '41,454', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '41,454', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '41,478', 'INFO', 'Initializing Fold 7']\n", "['2020-07-29 09', '51', '41,483', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '41,653', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '41,659', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '41,956', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '41,965', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '41,965', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '41,967', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '41,967', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '41,981', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '41,982', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=elbow, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '51', '41,983', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '41,984', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '41,994', 'INFO', 'Initializing Fold 8']\n", "['2020-07-29 09', '51', '41,997', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '42,027', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '51', '42,028', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '51', '42,381', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '42,393', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '42,394', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '42,420', 'INFO', 'Initializing Fold 9']\n", "['2020-07-29 09', '51', '42,425', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '42,790', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '42,799', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '42,799', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '42,822', 'INFO', 'Initializing Fold 10']\n", "['2020-07-29 09', '51', '42,827', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '43,263', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '43,283', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '43,284', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '43,307', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '51', '43,311', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '51', '43,331', 'INFO', 'Finalizing model']\n", "['2020-07-29 09', '51', '43,369', 'INFO', 'Extracting Bigrams']\n", "['2020-07-29 09', '51', '43,937', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '43,967', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '51', '44,615', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '44,615', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '44,617', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '51', '44,618', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '44,634', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '44,635', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '44,650', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '44,652', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=silhouette, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '51', '44,656', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '44,656', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '44,669', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '44,688', 'INFO', 'plot type', 'silhouette']\n", "['2020-07-29 09', '51', '44,689', 'INFO', 'Fitting SilhouetteVisualizer()']\n", "['2020-07-29 09', '51', '44,701', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-29 09', '51', '44,701', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '44,701', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '44,794', 'INFO', 'Uploading results into container']\n", "['2020-07-29 09', '51', '44,794', 'INFO', 'Uploading model into container']\n", "['2020-07-29 09', '51', '44,795', 'INFO', 'create_model_container', '11']\n", "['2020-07-29 09', '51', '44,795', 'INFO', 'master_model_container', '11']\n", "['2020-07-29 09', '51', '44,795', 'INFO', 'display_container', '12']\n", "['2020-07-29 09', '51', '44,798', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.1, max_depth=-1,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,']\n", "['n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,']\n", "['random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-29 09', '51', '44,798', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '44,800', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '44,906', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '51', '44,908', 'INFO', \"create_model(estimator=ExplainableBoostingRegressor(binning='quantile', early_stopping_rounds=50,\"]\n", "['early_stopping_tolerance=0, feature_names=None,']\n", "['feature_types=None, inner_bags=0, interactions=0,']\n", "[\"learning_rate=0.01, mains='all', max_bins=255,\"]\n", "['max_leaves=3, max_rounds=5000, min_samples_leaf=2,']\n", "['n_jobs=-2, outer_bags=16, random_state=42,']\n", "['validation_size=0.15), ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-29 09', '51', '44,909', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '44,909', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '44,909', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '45,006', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '51', '45,008', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '45,011', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '51', '45,012', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '51', '45,033', 'INFO', 'Declaring custom model']\n", "['2020-07-29 09', '51', '45,035', 'INFO', 'ExplainableBoostingRegressor Imported succesfully']\n", "['2020-07-29 09', '51', '45,039', 'INFO', 'Checking ensemble method']\n", "['2020-07-29 09', '51', '45,060', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '51', '45,083', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '45,326', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '45,327', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '45,342', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '45,344', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=distance, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '51', '45,344', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '45,345', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '45,377', 'INFO', 'plot type', 'distance']\n", "['2020-07-29 09', '51', '45,487', 'INFO', 'Fitting InterclusterDistance()']\n", "['2020-07-29 09', '51', '45,564', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '46,194', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '46,194', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '46,209', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '51', '46,212', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=distribution, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '51', '46,212', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '46,213', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '51', '46,239', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '51', '46,240', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '51', '46,240', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '51', '46,242', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '51', '46,242', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '51', '46,243', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '51', '46,243', 'INFO', 'Copying data']\n", "['2020-07-29 09', '51', '46,244', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '51', '46,295', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '51', '46,297', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '51', '46,297', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '51', '46,297', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '46,298', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '51', '46,298', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '51', '46,312', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '51', '46,914', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '51', '46,914', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '47,206', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '47,208', 'INFO', \"save_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), model_name=kmeans, verbose=True)']\n", "['2020-07-29 09', '51', '47,209', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '47,243', 'INFO', 'kmeans.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '47,273', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)]']\n", "['2020-07-29 09', '51', '47,275', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '47,520', 'INFO', 'Initializing deploy_model()']\n", "['2020-07-29 09', '51', '47,522', 'INFO', \"deploy_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "[\"random_state=123, tol=0.0001, verbose=0), model_name=kmeans-aws, authentication={'bucket'\", \"'pycaret-test'}, platform=aws)\"]\n", "['2020-07-29 09', '51', '47,522', 'INFO', 'Platform', 'AWS S3']\n", "['2020-07-29 09', '51', '49,570', 'INFO', 'Saving model in current working directory']\n", "['2020-07-29 09', '51', '49,571', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '51', '49,571', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '51', '49,573', 'INFO', \"save_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), model_name=kmeans-aws, verbose=False)']\n", "['2020-07-29 09', '51', '49,574', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '51', '49,638', 'INFO', 'kmeans-aws.pkl saved in current working directory']\n", "['2020-07-29 09', '51', '49,661', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)]']\n", "['2020-07-29 09', '51', '49,661', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '49,661', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '51', '49,661', 'INFO', 'Initializing S3 client']\n", "['2020-07-29 09', '51', '51,288', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '51', '51,296', 'INFO', 'No inverse transformation']\n", "['2020-07-29 09', '51', '51,296', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '51', '51,340', 'INFO', \"KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)']\n", "['2020-07-29 09', '51', '51,340', 'INFO', 'deploy_model() succesfully completed......................................']\n", "['2020-07-29 09', '51', '51,362', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '51', '51,363', 'INFO', 'get_config(variable=X)']\n", "['2020-07-29 09', '51', '51,363', 'INFO', 'Global variable', 'X returned']\n", "['2020-07-29 09', '51', '51,364', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '51', '51,382', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '51', '51,410', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '51', '51,471', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '51', '51,472', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-29 09', '51', '51,472', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-29 09', '51', '51,472', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '51', '51,496', 'INFO', 'Initializing set_config()']\n", "['2020-07-29 09', '51', '51,496', 'INFO', 'set_config(variable=seed, value=999)']\n", "['2020-07-29 09', '51', '51,497', 'INFO', 'Global variable', 'seed updated']\n", "['2020-07-29 09', '51', '51,497', 'INFO', 'set_config() succesfully completed......................................']\n", "['2020-07-29 09', '51', '51,566', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '51', '51,567', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-29 09', '51', '51,567', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-29 09', '51', '51,567', 'INFO', 'get_config() succesfully completed......................................']\n" ] } ], "source": [ "get_system_logs()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 11. MLFlow UI" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Running the mlflow server failed. Please see the logs above for details.\n" ] } ], "source": [ "!mlflow ui" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# End\n", "Thank you. For more information / tutorials on PyCaret, please visit https://www.pycaret.org" ] } ], "metadata": { "kernelspec": { "display_name": "pycaret-nightly-env", "language": "python", "name": "pycaret-nightly-env" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.10" } }, "nbformat": 4, "nbformat_minor": 2 }