{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# PyCaret 2 Clustering Example\n", "This notebook is created using PyCaret 2.0. Last updated : 31-07-2020" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.0\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" }, { "name": "stderr", "output_type": "stream", "text": [ "2020/07/31 08:47:41 WARNING mlflow.tracking.context.git_context: Failed to import Git (the Git executable is probably not on your PATH), so Git SHA is not available. Error: No module named 'repository'\n" ] } ], "source": [ "from pycaret.clustering import *\n", "clu1 = setup(data, ignore_features = ['Country Name'], session_id=123, log_experiment=True, log_plots = True, \n", " 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" ] ], "hoverlabel": { "namelength": 0 }, "hovertemplate": "Cluster=Cluster 0
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\n", 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\n", 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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

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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 ... 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": 24, "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": 24, "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": 18, "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": 19, "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": 20, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "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": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X = get_config('X')\n", "X.head()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "123" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_config('seed')" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [], "source": [ "from pycaret.clustering import set_config\n", "set_config('seed', 999)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "999" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_config('seed')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 10. Get System Logs" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-31 01', '40', '51,509', 'INFO', 'PyCaret Classification Module']\n", "['2020-07-31 01', '40', '51,509', 'INFO', 'version 2.0']\n", "['2020-07-31 01', '40', '51,509', 'INFO', 'Initializing setup()']\n", "['2020-07-31 01', '40', '51,509', 'INFO', 'USI', '1cda']\n", "['2020-07-31 01', '40', '51,510', 'INFO', 'setup(data=(1070, 19), target=Purchase, 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,']\n", "['fix_imbalance=False, fix_imbalance_method=None, data_split_shuffle=True, folds_shuffle=False, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=juice1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-31 01', '40', '51,526', 'INFO', 'Checking environment']\n", "['2020-07-31 01', '40', '51,526', 'INFO', 'python_version', '3.7.4']\n", "['2020-07-31 01', '40', '51,527', 'INFO', 'python_build', \"('default', 'Aug 9 2019 18\", '34', \"13')\"]\n", "['2020-07-31 01', '40', '51,527', 'INFO', 'machine', 'AMD64']\n", "['2020-07-31 01', '40', '51,527', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-31 01', '40', '51,599', 'INFO', 'Memory', 'svmem(total=17032478720, available=12121403392, percent=28.8, used=4911075328, free=12121403392)']\n", "['2020-07-31 01', '40', '51,599', 'INFO', 'Physical Core', '4']\n", "['2020-07-31 01', '40', '51,599', 'INFO', 'Logical Core', '8']\n", "['2020-07-31 01', '40', '51,599', 'INFO', 'Checking libraries']\n", "['2020-07-31 01', '40', '51,599', 'INFO', 'pd==1.0.5']\n", "['2020-07-31 01', '40', '51,599', 'INFO', 'numpy==1.18.5']\n", "['2020-07-31 01', '40', '55,335', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-31 01', '40', '55,728', 'INFO', 'xgboost==0.90']\n", "['2020-07-31 01', '40', '56,084', 'INFO', 'lightgbm==2.3.1']\n", "['2020-07-31 01', '40', '56,736', 'INFO', 'catboost==0.20.2']\n", "['2020-07-31 01', '41', '00,681', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-31 01', '41', '00,681', 'INFO', 'Checking Exceptions']\n", "['2020-07-31 01', '41', '00,681', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '41', '00,681', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '41', '00,697', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '41', '10,136', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-31 01', '41', '10,136', 'INFO', 'Declaring global variables']\n", "['2020-07-31 01', '41', '10,162', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-31 01', '41', '10,162', 'INFO', 'Importing preprocessing module']\n", "['2020-07-31 01', '41', '14,303', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-31 01', '41', '16,174', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-31 01', '41', '16,174', 'INFO', 'Creating grid variables']\n", "['2020-07-31 01', '41', '16,174', 'INFO', 'Creating global containers']\n", "['2020-07-31 01', '41', '16,270', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-31 01', '41', '16,394', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '16,394', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '16,394', '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='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\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", "['2020-07-31 01', '41', '16,394', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '16,409', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '16,409', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\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='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False)]']\n", "['2020-07-31 01', '41', '16,409', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '16,409', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '16,487', 'INFO', 'create_model_container 0']\n", "['2020-07-31 01', '41', '16,487', 'INFO', 'master_model_container 0']\n", "['2020-07-31 01', '41', '16,487', 'INFO', 'display_container 0']\n", "['2020-07-31 01', '41', '16,487', 'INFO', 'Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False)']\n", "['2020-07-31 01', '41', '16,487', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-31 01', '41', '23,818', 'INFO', 'Initializing compare_models()']\n", "['2020-07-31 01', '41', '23,818', 'INFO', 'compare_models(blacklist=None, whitelist=None, fold=10, round=4, sort=Accuracy, n_select=1, turbo=True, verbose=True)']\n", "['2020-07-31 01', '41', '23,818', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '41', '23,820', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '41', '23,820', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '41', '23,838', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '41', '23,839', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '41', '23,910', 'INFO', 'Importing untrained models']\n", "['2020-07-31 01', '41', '23,922', 'INFO', 'Import successful']\n", "['2020-07-31 01', '41', '23,928', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '41', '23,928', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '41', '23,928', 'INFO', 'Initializing Logistic Regression']\n", "['2020-07-31 01', '41', '23,934', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '23,940', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '23,996', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,003', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,007', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '24,013', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,057', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,064', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,068', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '24,073', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,111', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,118', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,122', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '24,127', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,168', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,174', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,178', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '24,182', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,224', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,230', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,235', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '24,240', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,279', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,286', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,290', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '24,296', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,338', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,345', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,349', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '24,354', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,391', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,398', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,402', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '24,407', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,447', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,453', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,457', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '24,462', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,503', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,509', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,514', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '24,514', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '24,523', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'save_model(model=LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '24,580', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)]']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '24,580', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '24,644', 'INFO', 'Initializing K Neighbors Classifier']\n", "['2020-07-31 01', '41', '24,647', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '24,647', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,685', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '24,905', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '24,911', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '24,916', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '24,922', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '25,165', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '25,173', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '25,180', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '25,185', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '25,410', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '25,415', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '25,422', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '25,427', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '25,652', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '25,652', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '25,672', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '25,676', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '25,941', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '25,956', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '25,956', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '25,972', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '26,219', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '26,235', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '26,235', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '26,249', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '26,490', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '26,490', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '26,510', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '26,514', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '26,744', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '26,750', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '26,756', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '26,760', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '26,998', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,007', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '27,013', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,019', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,243', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,248', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '27,249', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '27,259', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '27,319', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '27,319', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '27,320', 'INFO', \"save_model(model=KNeighborsClassifier(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 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Dummify(target='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform')]\"]\n", "['2020-07-31 01', '41', '27,338', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '27,338', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '27,380', 'INFO', 'Initializing Naive Bayes']\n", "['2020-07-31 01', '41', '27,380', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '27,396', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,398', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,405', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,410', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '27,415', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,418', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,424', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,429', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '27,434', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,437', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,444', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,449', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '27,455', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,458', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,465', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,469', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '27,475', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,478', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,484', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,489', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '27,494', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,497', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,504', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,509', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '27,514', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,517', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,525', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,530', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '27,535', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,538', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,545', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,550', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '27,556', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,559', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,566', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,570', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '27,576', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,579', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,585', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,590', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '27,590', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '27,600', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '27,648', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '27,648', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '27,648', 'INFO', 'save_model(model=GaussianNB(priors=None, var_smoothing=1e-09), model_name=Trained 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Dummify(target='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), GaussianNB(priors=None, var_smoothing=1e-09)]']\n", "['2020-07-31 01', '41', '27,648', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '27,648', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '27,707', 'INFO', 'Initializing Decision Tree Classifier']\n", "['2020-07-31 01', '41', '27,712', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '27,718', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,766', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,773', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,778', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '27,783', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,788', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,794', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,799', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '27,806', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,811', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,817', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,825', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '27,834', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,840', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,847', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,853', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '27,860', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,866', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,873', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,879', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '27,886', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,891', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,899', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,904', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '27,912', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,917', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,926', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,931', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '27,938', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,944', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,951', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,957', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '27,962', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,967', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '27,976', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '27,982', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '27,987', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '27,993', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,000', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,006', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '28,006', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '28,017', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '28,076', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '28,076', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '28,077', 'INFO', \"save_model(model=DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, 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('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, 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')]\"]\n", "['2020-07-31 01', '41', '28,087', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '28,087', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '28,135', 'INFO', 'Initializing SVM - Linear Kernel']\n", "['2020-07-31 01', '41', '28,141', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '28,147', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,188', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,188', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,191', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,193', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,198', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '28,204', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,212', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,212', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,215', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,217', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,222', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '28,227', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,235', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,235', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,238', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,240', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,245', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '28,250', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,256', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,256', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,259', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,262', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,266', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '28,272', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,276', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,276', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,279', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,281', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,286', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '28,291', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,297', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,297', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,300', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,302', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,307', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '28,312', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,319', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,319', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,322', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,324', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,329', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '28,334', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,341', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,341', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,344', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,346', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,350', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '28,356', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,364', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,364', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,367', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,369', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,374', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '28,378', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,386', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,386', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,389', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,391', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,396', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '28,396', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '28,407', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '28,473', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '28,474', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '28,474', 'INFO', 'save_model(model=SGDClassifier(alpha=0.0001, average=False, class_weight=None,']\n", "['early_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,']\n", "[\"l1_ratio=0.15, learning_rate='optimal', loss='hinge',\"]\n", "[\"max_iter=1000, n_iter_no_change=5, n_jobs=-1, penalty='l2',\"]\n", "['power_t=0.5, random_state=123, shuffle=True, tol=0.001,']\n", "['validation_fraction=0.1, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '28,474', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '28,479', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '28,483', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), SGDClassifier(alpha=0.0001, average=False, class_weight=None,']\n", "['early_stopping=False, epsilon=0.1, eta0=0.0, fit_intercept=True,']\n", "[\"l1_ratio=0.15, learning_rate='optimal', loss='hinge',\"]\n", "[\"max_iter=1000, n_iter_no_change=5, n_jobs=-1, penalty='l2',\"]\n", "['power_t=0.5, random_state=123, shuffle=True, tol=0.001,']\n", "['validation_fraction=0.1, verbose=0, warm_start=False)]']\n", "['2020-07-31 01', '41', '28,483', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '28,483', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '28,532', 'INFO', 'Initializing Ridge Classifier']\n", "['2020-07-31 01', '41', '28,532', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '28,547', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,630', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,630', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,646', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,646', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,646', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '28,646', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,662', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,662', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,665', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,667', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,676', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '28,683', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,687', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,687', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,690', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,692', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,697', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '28,706', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,711', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,711', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,713', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,715', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,720', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '28,726', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,730', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,730', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,733', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,735', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,739', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '28,744', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,748', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,749', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,751', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,754', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,759', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '28,764', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,768', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,768', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,771', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,773', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,778', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '28,784', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,788', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,788', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,791', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,793', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,799', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '28,804', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,809', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,809', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,813', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,816', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,821', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '28,827', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '28,831', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '28,831', 'WARNING', 'model has no predict_proba attribute. pred_prob set to 0.00']\n", "['2020-07-31 01', '41', '28,834', 'WARNING', 'model has no predict_proba attribute. AUC set to 0.00']\n", "['2020-07-31 01', '41', '28,836', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '28,841', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '28,841', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '28,853', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '28,934', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '28,935', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '28,935', 'INFO', 'save_model(model=RidgeClassifier(alpha=1.0, class_weight=None, copy_X=True, fit_intercept=True,']\n", "[\"max_iter=None, normalize=False, random_state=123, solver='auto',\"]\n", "['tol=0.001), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '28,935', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '28,940', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '28,944', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RidgeClassifier(alpha=1.0, class_weight=None, copy_X=True, fit_intercept=True,']\n", "[\"max_iter=None, normalize=False, random_state=123, solver='auto',\"]\n", "['tol=0.001)]']\n", "['2020-07-31 01', '41', '28,944', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '28,944', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '28,994', 'INFO', 'Initializing Random Forest Classifier']\n", "['2020-07-31 01', '41', '29,000', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '29,006', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '29,127', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '29,363', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '29,378', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '29,378', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '29,496', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '29,712', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '29,716', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '29,723', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '29,834', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '30,077', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '30,087', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '30,095', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '30,207', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '30,439', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '30,448', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '30,455', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '30,569', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '30,799', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '30,799', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '30,814', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '30,933', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '31,162', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '31,175', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '31,183', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '31,295', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '31,538', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '31,547', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '31,553', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '31,666', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '31,902', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '31,913', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '31,916', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,034', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,263', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,263', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '32,263', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,387', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,626', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,630', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '32,630', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '32,642', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '32,713', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '32,713', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '32,713', 'INFO', 'save_model(model=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '32,713', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '32,713', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '32,729', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '41', '32,729', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '32,729', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '32,760', 'INFO', 'Initializing Quadratic Discriminant Analysis']\n", "['2020-07-31 01', '41', '32,776', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '32,776', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,838', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,838', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,854', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '32,854', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,854', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,870', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,870', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '32,870', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,885', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,885', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,885', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '32,901', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,901', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,901', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,916', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '32,916', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,916', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,932', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,932', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '32,932', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,948', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,948', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,948', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '32,963', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,963', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,963', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,979', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '32,979', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '32,979', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '32,995', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '32,995', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '33,010', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '33,010', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '33,023', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '33,029', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '33,033', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '33,039', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '33,045', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '33,050', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '33,050', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '33,062', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '33,114', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '33,114', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '33,114', 'INFO', 'save_model(model=QuadraticDiscriminantAnalysis(priors=None, reg_param=0.0,']\n", "['store_covariance=False, tol=0.0001), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '33,114', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '33,114', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '33,114', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", 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completed......................................']\n", "['2020-07-31 01', '41', '33,114', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '33,161', 'INFO', 'Initializing Ada Boost Classifier']\n", "['2020-07-31 01', '41', '33,161', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '33,177', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '33,239', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '33,255', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '33,255', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '33,270', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '33,333', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '33,348', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '33,348', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '33,364', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '33,427', 'INFO', 'Evaluating Metrics']\n", 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'Fitting Model']\n", "['2020-07-31 01', '41', '33,839', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '33,855', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '33,855', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '33,871', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '33,933', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '33,949', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '33,964', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '33,964', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,027', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '34,058', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '34,058', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '34,058', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,136', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '34,152', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '34,152', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '34,152', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '34,171', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '34,240', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '34,241', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '34,241', 'INFO', \"save_model(model=AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0,\"]\n", "['n_estimators=50, random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '34,241', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '34,250', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '34,250', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, 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'34,250', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '34,250', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '34,314', 'INFO', 'Initializing Gradient Boosting Classifier']\n", "['2020-07-31 01', '41', '34,322', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '34,328', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,447', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '34,455', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '34,460', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '34,466', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,582', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '34,589', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '34,594', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '34,600', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,726', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '34,733', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '34,739', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '34,745', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,851', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '34,868', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '34,872', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '34,877', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '34,995', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,002', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,008', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '35,013', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,134', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,142', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,146', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '35,151', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,277', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,284', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,290', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '35,296', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,398', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,398', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,413', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '35,413', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,532', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,539', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,545', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '35,550', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,674', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,680', 'INFO', 'Compiling 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'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '35,814', 'INFO', 'Initializing Linear Discriminant Analysis']\n", "['2020-07-31 01', '41', '35,832', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '35,838', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,848', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,855', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,860', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '35,865', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,873', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,880', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,885', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '35,890', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,900', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,906', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,911', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '35,916', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,924', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,931', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,936', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '35,941', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,949', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,956', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,960', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '35,966', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,973', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '35,980', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '35,985', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '35,990', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '35,999', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '36,005', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '36,013', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '36,021', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '36,031', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '36,037', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '36,043', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '36,048', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '36,055', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '36,062', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '36,066', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '36,071', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '36,079', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '36,086', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '36,091', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '36,091', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '36,103', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '36,160', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '36,160', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '36,161', 'INFO', 'save_model(model=LinearDiscriminantAnalysis(n_components=None, priors=None, shrinkage=None,']\n", "[\"solver='svd', store_covariance=False, tol=0.0001), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-31 01', '41', '36,161', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '36,165', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '36,168', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LinearDiscriminantAnalysis(n_components=None, priors=None, shrinkage=None,']\n", "[\"solver='svd', store_covariance=False, tol=0.0001)]\"]\n", "['2020-07-31 01', '41', '36,168', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '36,168', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '36,199', 'INFO', 'Initializing Extra Trees Classifier']\n", "['2020-07-31 01', '41', '36,215', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '36,221', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '36,359', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '36,592', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '36,602', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '36,612', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '36,759', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '36,976', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '36,983', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '36,990', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '37,131', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '37,369', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '37,369', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '37,390', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '37,529', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '37,769', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '37,769', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '37,792', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '37,934', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '38,165', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '38,181', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '38,181', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '38,333', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '38,572', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '38,572', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '38,588', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '38,732', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '38,984', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '38,994', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '39,003', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '39,164', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '39,413', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '39,419', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '39,419', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '39,586', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '39,808', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '39,808', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '39,823', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '39,966', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '40,196', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '40,196', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '40,196', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '40,211', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '40,302', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '40,302', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '40,302', 'INFO', 'save_model(model=ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '40,302', 'INFO', 'Appending 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Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '41', '40,349', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '40,349', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '40,395', 'INFO', 'Initializing Extreme Gradient Boosting']\n", "['2020-07-31 01', '41', '40,395', 'INFO', 'Initializing Fold 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'Compiling Metrics']\n", "['2020-07-31 01', '41', '40,751', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '40,761', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '40,800', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '40,813', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '40,820', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '40,834', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '40,873', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '40,886', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '40,897', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '40,906', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '40,946', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '40,959', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '40,970', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '40,980', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,020', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,032', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,043', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '41,054', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,096', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,109', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,119', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '41,128', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,175', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,188', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,199', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '41,199', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '41,228', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '41,348', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '41,349', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '41,349', 'INFO', \"save_model(model=XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "['learning_rate=0.1, max_delta_step=0, max_depth=3,']\n", "['min_child_weight=1, missing=None, n_estimators=100, n_jobs=-1,']\n", "[\"nthread=None, objective='binary\", \"logistic', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '41', '41,349', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '41,358', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '41,362', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, 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max_delta_step=0, max_depth=3,']\n", "['min_child_weight=1, missing=None, n_estimators=100, n_jobs=-1,']\n", "[\"nthread=None, objective='binary\", \"logistic', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)]']\n", "['2020-07-31 01', '41', '41,362', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '41,362', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '41,423', 'INFO', 'Initializing Light Gradient Boosting Machine']\n", "['2020-07-31 01', '41', '41,429', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '41,434', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,515', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,533', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,544', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '41,554', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,628', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,645', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,656', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '41,665', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,734', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,737', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,753', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '41,769', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,837', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,838', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,853', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '41,873', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '41,936', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '41,937', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '41,953', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '41,972', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '42,047', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '42,063', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '42,074', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '42,084', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '42,180', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '42,196', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '42,208', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '42,218', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '42,287', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '42,302', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '42,318', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '42,318', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '42,380', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '42,412', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '42,412', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '42,427', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '42,502', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '42,519', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '42,530', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '41', '42,531', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '41', '42,561', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '41', '42,651', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '41', '42,651', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '41', '42,652', 'INFO', \"save_model(model=LGBMClassifier(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", "['2020-07-31 01', '41', '42,652', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '41', '42,663', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '41', '42,675', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMClassifier(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", "['2020-07-31 01', '41', '42,675', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '41', '42,675', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '41', '42,777', 'INFO', 'Initializing CatBoost Classifier']\n", "['2020-07-31 01', '41', '42,783', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '41', '42,789', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '45,155', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '45,194', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '45,199', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '41', '45,205', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '47,070', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '47,086', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '47,086', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '41', '47,086', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '48,735', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '48,751', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '48,751', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '41', '48,764', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '50,511', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '50,526', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '50,542', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '41', '50,542', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '52,170', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '52,170', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '52,186', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '41', '52,193', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '53,805', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '53,820', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '53,820', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '41', '53,834', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '55,391', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '55,391', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '55,407', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '41', '55,407', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '56,979', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '56,994', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '56,994', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '41', '57,008', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '41', '58,639', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '41', '58,654', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '41', '58,670', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '41', '58,670', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,228', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,244', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,244', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '00,244', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '00,260', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '00,317', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '00,317', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '00,318', 'INFO', 'save_model(model=, model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '00,318', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '00,325', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '00,329', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ]']\n", "['2020-07-31 01', '42', '00,329', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '00,329', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '00,375', 'INFO', 'Finalizing top_n models']\n", "['2020-07-31 01', '42', '00,375', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-31 01', '42', '00,383', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '00,383', 'INFO', 'create_model(estimator=lr, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 01', '42', '00,383', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '00,383', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '00,383', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '00,391', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '00,391', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '00,391', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '00,391', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '00,392', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '00,392', 'INFO', 'Logistic Regression Imported succesfully']\n", "['2020-07-31 01', '42', '00,392', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '00,395', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '00,396', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,435', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,441', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,445', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '00,445', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,476', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,476', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,492', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '00,492', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,523', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,539', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,539', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '00,539', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,585', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,585', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,601', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '00,601', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,632', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,648', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,648', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '00,648', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,679', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,695', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,695', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '00,695', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,742', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,742', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,742', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '00,742', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,788', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,788', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,788', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '00,788', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,835', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,835', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,835', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '00,835', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '00,882', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '00,882', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '00,898', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '00,898', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '00,898', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'Uploading model into container now']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'create_model_container', '1']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'master_model_container', '1']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'display_container', '1']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '00,929', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-31 01', '42', '00,999', 'INFO', 'create_model_container', '1']\n", "['2020-07-31 01', '42', '00,999', 'INFO', 'master_model_container', '1']\n", "['2020-07-31 01', '42', '01,000', 'INFO', 'display_container', '2']\n", "['2020-07-31 01', '42', '01,000', 'INFO', 'LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '01,000', 'INFO', 'compare_models() succesfully completed......................................']\n", "['2020-07-31 01', '42', '01,009', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '01,009', 'INFO', 'create_model(estimator=lr, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '01,009', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '01,009', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '01,010', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '01,033', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '01,034', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '01,035', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '01,035', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '01,039', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '01,039', 'INFO', 'Logistic Regression Imported succesfully']\n", "['2020-07-31 01', '42', '01,040', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '01,046', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '01,050', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,094', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,101', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,113', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '01,118', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,160', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,166', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,180', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '01,185', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,230', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,236', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,248', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '01,253', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,295', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,301', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,314', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '01,322', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,368', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,374', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,378', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '01,378', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,432', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,438', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,444', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '01,444', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,497', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,503', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,511', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '01,511', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,561', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,568', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,582', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '01,587', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,626', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,633', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,646', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '01,651', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '01,694', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '01,700', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '01,715', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '01,716', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '01,724', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '01,766', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '01,930', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '01,931', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '01,931', 'INFO', 'save_model(model=LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '01,931', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '01,936', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '01,940', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '01,940', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '01,940', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '01,960', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '01,960', 'INFO', 'Uploading model into container now']\n", "['2020-07-31 01', '42', '01,993', 'INFO', 'create_model_container', '2']\n", "['2020-07-31 01', '42', '01,993', 'INFO', 'master_model_container', '2']\n", "['2020-07-31 01', '42', '01,993', 'INFO', 'display_container', '3']\n", "['2020-07-31 01', '42', '01,994', 'INFO', 'LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '01,994', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '02,000', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '02,000', 'INFO', 'create_model(estimator=dt, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '02,001', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '02,001', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '02,001', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '02,022', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '02,023', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '02,023', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '02,023', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '02,027', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '02,027', 'INFO', 'Decision Tree Classifier Imported succesfully']\n", "['2020-07-31 01', '42', '02,028', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '02,035', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '02,040', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,046', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,054', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,069', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '02,073', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,078', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,085', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,099', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '02,104', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,108', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,115', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,133', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '02,137', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,143', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,149', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,165', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '02,170', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,174', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,181', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,198', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '02,204', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,208', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,216', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,234', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '02,239', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,244', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,252', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,268', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '02,273', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,279', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,290', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,307', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '02,313', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,318', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,326', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,342', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '02,347', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,352', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '02,360', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '02,376', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '02,377', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '02,385', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '02,390', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '02,521', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '02,521', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '02,521', 'INFO', \"save_model(model=DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, 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", "['2020-07-31 01', '42', '02,521', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '02,526', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '02,530', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, 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')]\"]\n", "['2020-07-31 01', '42', '02,530', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '02,530', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '02,545', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '02,545', 'INFO', 'Uploading model into container now']\n", "['2020-07-31 01', '42', '02,583', 'INFO', 'create_model_container', '3']\n", "['2020-07-31 01', '42', '02,583', 'INFO', 'master_model_container', '3']\n", "['2020-07-31 01', '42', '02,583', 'INFO', 'display_container', '4']\n", "['2020-07-31 01', '42', '02,584', 'INFO', \"DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, 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')\"]\n", "['2020-07-31 01', '42', '02,584', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '02,591', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '02,591', 'INFO', 'create_model(estimator=rf, ensemble=False, method=None, fold=5, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '02,591', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '02,592', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '02,592', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '02,613', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '02,614', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '02,615', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '02,615', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '02,619', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '02,620', 'INFO', 'Random Forest Classifier Imported succesfully']\n", "['2020-07-31 01', '42', '02,620', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '02,626', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '02,631', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '02,758', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '03,008', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '03,028', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '03,034', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '03,159', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '03,378', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '03,408', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '03,412', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '03,526', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '03,754', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '03,773', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '03,778', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '03,894', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '04,129', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '04,146', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '04,146', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '04,276', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '04,495', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '04,517', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '04,518', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '04,524', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '04,642', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '05,033', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '05,033', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '05,033', 'INFO', 'save_model(model=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '05,033', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '05,049', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '05,049', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '05,049', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '05,049', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '05,065', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '05,065', 'INFO', 'Uploading model into container now']\n", "['2020-07-31 01', '42', '05,080', 'INFO', 'create_model_container', '4']\n", "['2020-07-31 01', '42', '05,080', 'INFO', 'master_model_container', '4']\n", "['2020-07-31 01', '42', '05,080', 'INFO', 'display_container', '5']\n", "['2020-07-31 01', '42', '05,080', 'INFO', 'RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '05,080', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '05,131', 'INFO', 'Initializing compare_models()']\n", "['2020-07-31 01', '42', '05,131', 'INFO', \"compare_models(blacklist=None, whitelist=['rf', 'ada', 'gbc', 'et', 'xgboost', 'lightgbm', 'catboost'], fold=3, round=4, sort=Accuracy, n_select=1, turbo=True, verbose=True)\"]\n", "['2020-07-31 01', '42', '05,131', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '05,132', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '05,132', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '05,155', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '05,156', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '05,160', 'INFO', 'Importing untrained models']\n", "['2020-07-31 01', '42', '05,160', 'INFO', 'Import successful']\n", "['2020-07-31 01', '42', '05,167', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '05,167', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '05,167', 'INFO', 'Initializing Random Forest Classifier']\n", "['2020-07-31 01', '42', '05,172', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '05,179', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '05,293', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '05,535', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '05,535', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '05,550', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '05,676', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '05,894', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '05,894', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '05,910', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '06,026', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '06,258', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '06,258', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '06,258', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '06,273', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '06,339', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '06,339', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '06,340', 'INFO', 'save_model(model=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '06,340', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '06,346', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '06,346', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '06,346', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '06,346', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '06,400', 'INFO', 'Initializing Ada Boost Classifier']\n", "['2020-07-31 01', '42', '06,405', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '06,411', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '06,478', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '06,496', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '06,496', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '06,496', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '06,575', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '06,581', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '06,596', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '06,596', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '06,670', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '06,680', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '06,680', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '06,680', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '06,696', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '06,760', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '06,760', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '06,760', 'INFO', \"save_model(model=AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0,\"]\n", "['n_estimators=50, random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '06,760', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '06,779', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '06,779', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0,\"]\n", "['n_estimators=50, random_state=123)]']\n", "['2020-07-31 01', '42', '06,779', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '06,779', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '06,825', 'INFO', 'Initializing Gradient Boosting Classifier']\n", "['2020-07-31 01', '42', '06,825', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '06,841', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '06,929', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '06,929', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '06,944', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '06,944', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '07,030', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '07,046', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '07,046', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '07,046', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '07,146', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '07,146', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '07,162', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '07,162', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '07,162', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '07,241', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '07,241', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '07,242', 'INFO', \"save_model(model=GradientBoostingClassifier(ccp_alpha=0.0, criterion='friedman_mse', init=None,\"]\n", "[\"learning_rate=0.1, loss='deviance', 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,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '07,242', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '07,249', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '07,254', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), GradientBoostingClassifier(ccp_alpha=0.0, criterion='friedman_mse', init=None,\"]\n", "[\"learning_rate=0.1, loss='deviance', 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,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '07,254', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '07,254', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '07,294', 'INFO', 'Initializing Extra Trees Classifier']\n", "['2020-07-31 01', '42', '07,294', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '07,313', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '07,459', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '07,694', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '07,694', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '07,694', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '07,859', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '08,109', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '08,109', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '08,109', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '08,277', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '08,495', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '08,495', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '08,495', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '08,511', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '08,611', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '08,611', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '08,611', 'INFO', 'save_model(model=ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '08,611', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '08,658', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '08,658', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '08,658', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '08,658', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '08,705', 'INFO', 'Initializing Extreme Gradient Boosting']\n", "['2020-07-31 01', '42', '08,721', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '08,727', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '08,759', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '08,773', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '08,781', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '08,794', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '08,828', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '08,842', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '08,853', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '08,864', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '08,900', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '08,913', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '08,924', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '08,925', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '08,947', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '09,139', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '09,139', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '09,139', 'INFO', \"save_model(model=XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "['learning_rate=0.1, max_delta_step=0, max_depth=3,']\n", "['min_child_weight=1, missing=None, n_estimators=100, n_jobs=-1,']\n", "[\"nthread=None, objective='binary\", \"logistic', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '09,139', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '09,154', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '09,154', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "['learning_rate=0.1, max_delta_step=0, max_depth=3,']\n", "['min_child_weight=1, missing=None, n_estimators=100, n_jobs=-1,']\n", "[\"nthread=None, objective='binary\", \"logistic', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)]']\n", "['2020-07-31 01', '42', '09,154', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '09,154', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '09,201', 'INFO', 'Initializing Light Gradient Boosting Machine']\n", "['2020-07-31 01', '42', '09,216', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '09,222', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '09,276', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '09,282', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '09,297', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '09,314', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '09,375', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '09,381', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '09,397', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '09,413', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '09,466', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '09,481', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '09,481', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '09,481', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '09,514', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '09,597', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '09,597', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '09,597', 'INFO', \"save_model(model=LGBMClassifier(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", "['2020-07-31 01', '42', '09,597', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '09,613', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '09,628', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LGBMClassifier(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", "['2020-07-31 01', '42', '09,628', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '09,628', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '09,722', 'INFO', 'Initializing CatBoost Classifier']\n", "['2020-07-31 01', '42', '09,733', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '09,738', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '11,485', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '11,485', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '11,501', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '11,508', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '13,655', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '13,671', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '13,671', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '13,686', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '15,832', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '15,844', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '15,851', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '15,851', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '15,867', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '15,935', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '15,936', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '15,936', 'INFO', 'save_model(model=, model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '15,936', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '15,944', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '15,950', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ]']\n", "['2020-07-31 01', '42', '15,950', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '15,950', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '16,009', 'INFO', 'Finalizing top_n models']\n", "['2020-07-31 01', '42', '16,009', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-31 01', '42', '16,014', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '16,014', 'INFO', 'create_model(estimator=xgboost, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 01', '42', '16,014', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '16,014', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '16,014', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '16,024', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '16,024', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '16,025', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '16,026', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '16,026', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '16,026', 'INFO', 'Extreme Gradient Boosting Imported succesfully']\n", "['2020-07-31 01', '42', '16,027', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '16,030', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '16,031', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,079', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,084', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,099', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '16,099', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,146', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,162', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,177', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '16,177', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,224', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,240', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,256', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '16,271', 'INFO', 'Fitting Model']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-31 01', '42', '16,318', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,334', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,349', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '16,349', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,396', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,412', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,427', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '16,427', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,474', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,490', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,505', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '16,521', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,568', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,584', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,599', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '16,599', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,646', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,662', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,677', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '16,693', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,740', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,755', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,771', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '16,771', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '16,834', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '16,849', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '16,865', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '16,865', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '16,880', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '16,927', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '16,927', 'INFO', 'Uploading model into container now']\n", "['2020-07-31 01', '42', '16,927', 'INFO', 'create_model_container', '5']\n", "['2020-07-31 01', '42', '16,927', 'INFO', 'master_model_container', '5']\n", "['2020-07-31 01', '42', '16,927', 'INFO', 'display_container', '6']\n", "['2020-07-31 01', '42', '16,943', 'INFO', \"XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "['learning_rate=0.1, max_delta_step=0, max_depth=3,']\n", "['min_child_weight=1, missing=None, n_estimators=100, n_jobs=-1,']\n", "[\"nthread=None, objective='binary\", \"logistic', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)']\n", "['2020-07-31 01', '42', '16,943', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '16,943', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-31 01', '42', '17,034', 'INFO', 'create_model_container', '5']\n", "['2020-07-31 01', '42', '17,034', 'INFO', 'master_model_container', '5']\n", "['2020-07-31 01', '42', '17,034', 'INFO', 'display_container', '7']\n", "['2020-07-31 01', '42', '17,034', 'INFO', \"XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "['learning_rate=0.1, max_delta_step=0, max_depth=3,']\n", "['min_child_weight=1, missing=None, n_estimators=100, n_jobs=-1,']\n", "[\"nthread=None, objective='binary\", \"logistic', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)']\n", "['2020-07-31 01', '42', '17,034', 'INFO', 'compare_models() succesfully completed......................................']\n", "['2020-07-31 01', '42', '17,048', 'INFO', 'Initializing tune_model()']\n", "['2020-07-31 01', '42', '17,049', 'INFO', 'tune_model(estimator=LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,']\n", "['intercept_scaling=1, l1_ratio=None, max_iter=100,']\n", "[\"multi_class='auto', n_jobs=None, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), fold=10, round=4, n_iter=10, custom_grid=None, optimize=Accuracy, choose_better=False, verbose=True)']\n", "['2020-07-31 01', '42', '17,049', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '17,051', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '17,051', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '17,077', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '17,078', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '17,078', 'INFO', 'Checking base model']\n", "['2020-07-31 01', '42', '17,079', 'INFO', 'Base model', 'Logistic Regression']\n", "['2020-07-31 01', '42', '17,080', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '17,080', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '17,088', 'INFO', 'Defining Hyperparameters']\n", "['2020-07-31 01', '42', '17,088', 'INFO', 'Initializing RandomizedSearchCV']\n", "['2020-07-31 01', '42', '20,205', 'INFO', 'Random search completed']\n", "['2020-07-31 01', '42', '20,213', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '20,220', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,253', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,261', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,282', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '20,289', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,320', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,328', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,347', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '20,354', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,386', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,394', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,414', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '20,420', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,451', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,460', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,478', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '20,484', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,516', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,525', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,543', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '20,549', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,579', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,589', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,609', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '20,615', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,651', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,661', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,683', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '20,689', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,723', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,732', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,756', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '20,762', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,796', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,805', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,825', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '20,832', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '20,863', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '20,872', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '20,894', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '20,895', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '20,904', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '20,934', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '20,934', 'INFO', 'Uploading model into container']\n", "['2020-07-31 01', '42', '20,935', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '21,014', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '21,015', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '21,015', 'INFO', \"save_model(model=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '21,015', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '21,018', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '21,018', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '21,018', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '21,018', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '21,237', 'INFO', 'create_model_container', '6']\n", "['2020-07-31 01', '42', '21,237', 'INFO', 'master_model_container', '6']\n", "['2020-07-31 01', '42', '21,237', 'INFO', 'display_container', '8']\n", "['2020-07-31 01', '42', '21,237', 'INFO', \"LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '21,237', 'INFO', 'tune_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '21,242', 'INFO', 'Initializing tune_model()']\n", "['2020-07-31 01', '42', '21,243', 'INFO', 'tune_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), fold=10, round=4, n_iter=10, custom_grid=None, optimize=Accuracy, choose_better=False, verbose=True)']\n", "['2020-07-31 01', '42', '21,243', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '21,244', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '21,244', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '21,264', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '21,265', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '21,265', 'INFO', 'Checking base model']\n", "['2020-07-31 01', '42', '21,266', 'INFO', 'Base model', 'Random Forest Classifier']\n", "['2020-07-31 01', '42', '21,266', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '21,266', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '21,272', 'INFO', 'Defining Hyperparameters']\n", "['2020-07-31 01', '42', '21,272', 'INFO', 'Initializing RandomizedSearchCV']\n", "['2020-07-31 01', '42', '22,790', 'INFO', 'Random search completed']\n", "['2020-07-31 01', '42', '22,816', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '22,831', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '22,955', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '23,185', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '23,211', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '23,217', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '23,340', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '23,563', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '23,582', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '23,586', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '23,716', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '23,951', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '23,968', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '23,974', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '24,091', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '24,320', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '24,351', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '24,356', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '24,483', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '24,718', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '24,742', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '24,747', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '24,866', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '25,117', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '25,141', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '25,146', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '25,283', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '25,518', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '25,542', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '25,547', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '25,666', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '25,919', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '25,938', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '25,938', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '26,084', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '26,312', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '26,334', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '26,338', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '26,457', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '26,677', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '26,699', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '26,700', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '26,707', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '26,829', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '26,830', 'INFO', 'Uploading model into container']\n", "['2020-07-31 01', '42', '26,830', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '26,911', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '26,911', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '26,912', 'INFO', 'save_model(model=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=30, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=10,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=30, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '26,912', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '26,927', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '26,931', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=30, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=10,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=30, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '26,931', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '26,931', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '27,309', 'INFO', 'create_model_container', '7']\n", "['2020-07-31 01', '42', '27,309', 'INFO', 'master_model_container', '7']\n", "['2020-07-31 01', '42', '27,309', 'INFO', 'display_container', '9']\n", "['2020-07-31 01', '42', '27,310', 'INFO', 'RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=30, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=10,']\n", "['min_weight_fraction_leaf=0.0, n_estimators=30, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '27,310', 'INFO', 'tune_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '27,315', 'INFO', 'Initializing ensemble_model()']\n", "['2020-07-31 01', '42', '27,316', 'INFO', \"ensemble_model(estimator=DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, 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'), method=Bagging, fold=10, n_estimators=10, round=4, choose_better=False, optimize=Accuracy, verbose=True)\"]\n", "['2020-07-31 01', '42', '27,316', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '27,316', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '27,316', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '27,335', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '27,335', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '27,336', 'INFO', 'Checking base model']\n", "['2020-07-31 01', '42', '27,337', 'INFO', 'Base model', 'Decision Tree Classifier']\n", "['2020-07-31 01', '42', '27,341', 'INFO', 'Importing untrained ensembler']\n", "['2020-07-31 01', '42', '27,342', 'INFO', 'BaggingClassifier() succesfully imported']\n", "['2020-07-31 01', '42', '27,347', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '27,347', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '27,349', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '27,356', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,384', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,416', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,430', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '27,435', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,459', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,487', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,504', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '27,509', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,534', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,567', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,582', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '27,587', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,612', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,644', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,658', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '27,663', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,686', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,718', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,733', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '27,738', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,764', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,799', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,816', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '27,822', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,852', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,892', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,904', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '27,904', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '27,938', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '27,970', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '27,985', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '27,990', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,015', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,047', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,062', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '28,067', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,092', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,121', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,139', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '28,140', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '28,150', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '28,173', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '28,173', 'INFO', 'Uploading model into container']\n", "['2020-07-31 01', '42', '28,174', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '28,239', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '28,239', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '28,240', 'INFO', 'save_model(model=BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=10, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '28,240', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '28,250', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '28,256', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=10, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False)]']\n", "['2020-07-31 01', '42', '28,256', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '28,256', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '28,419', 'INFO', 'create_model_container', '8']\n", "['2020-07-31 01', '42', '28,420', 'INFO', 'master_model_container', '8']\n", "['2020-07-31 01', '42', '28,420', 'INFO', 'display_container', '10']\n", "['2020-07-31 01', '42', '28,421', 'INFO', 'BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=10, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False)']\n", "['2020-07-31 01', '42', '28,421', 'INFO', 'ensemble_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '28,427', 'INFO', 'Initializing ensemble_model()']\n", "['2020-07-31 01', '42', '28,428', 'INFO', \"ensemble_model(estimator=DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\"]\n", "['max_depth=None, 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'), method=Boosting, fold=10, n_estimators=10, round=4, choose_better=False, optimize=Accuracy, verbose=True)\"]\n", "['2020-07-31 01', '42', '28,428', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '28,428', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '28,429', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '28,447', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '28,447', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '28,449', 'INFO', 'Checking base model']\n", "['2020-07-31 01', '42', '28,452', 'INFO', 'Base model', 'Decision Tree Classifier']\n", "['2020-07-31 01', '42', '28,456', 'INFO', 'Importing untrained ensembler']\n", "['2020-07-31 01', '42', '28,457', 'INFO', 'AdaBoostClassifier() succesfully imported']\n", "['2020-07-31 01', '42', '28,463', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '28,463', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '28,464', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '28,469', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,508', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,517', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,531', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '28,536', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,568', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,577', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,591', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '28,597', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,634', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,644', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,659', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '28,665', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,708', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,718', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,735', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '28,741', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,778', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,789', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,809', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '28,817', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,858', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,868', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,885', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '28,891', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '28,920', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '28,933', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '28,953', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '28,960', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '29,003', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '29,013', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '29,028', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '29,033', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '29,071', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '29,082', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '29,099', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '29,103', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '29,134', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '29,144', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '29,161', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '29,162', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '29,174', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '29,219', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '29,219', 'INFO', 'Uploading model into container']\n", "['2020-07-31 01', '42', '29,220', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '29,282', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '29,282', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '29,283', 'INFO', 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"[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['learning_rate=1.0, n_estimators=10, random_state=123)]']\n", "['2020-07-31 01', '42', '29,304', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '29,304', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '29,449', 'INFO', 'create_model_container', '9']\n", "['2020-07-31 01', '42', '29,449', 'INFO', 'master_model_container', '9']\n", "['2020-07-31 01', '42', '29,449', 'INFO', 'display_container', '11']\n", "['2020-07-31 01', '42', '29,450', 'INFO', \"AdaBoostClassifier(algorithm='SAMME.R',\"]\n", "['base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['learning_rate=1.0, n_estimators=10, random_state=123)']\n", "['2020-07-31 01', '42', '29,450', 'INFO', 'ensemble_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '29,456', 'INFO', 'Initializing blend_models()']\n", "['2020-07-31 01', '42', '29,459', 'INFO', \"blend_models(estimator_list=[AdaBoostClassifier(algorithm='SAMME.R',\"]\n", "['base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['learning_rate=1.0, n_estimators=10, random_state=123), BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=10, n_jobs=-1, oob_score=False,']\n", 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'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '29,482', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '29,486', 'INFO', 'Defining model names in estimator_list']\n", "['2020-07-31 01', '42', '29,656', 'INFO', 'n_jobs multiple passed']\n", "['2020-07-31 01', '42', '29,664', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '29,672', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '29,826', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '30,112', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '30,136', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '30,147', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '30,300', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '30,559', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '30,571', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '30,576', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '30,719', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '30,986', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '31,001', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '31,007', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '31,147', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '31,442', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '31,460', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '31,466', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '31,602', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '31,896', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '31,921', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '31,927', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '32,074', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '32,325', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '32,340', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '32,346', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '32,497', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '32,810', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '32,826', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '32,836', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '32,985', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '33,258', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '33,272', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '33,281', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '33,422', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '33,716', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '33,731', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '33,736', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '33,878', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '34,182', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '34,205', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '34,206', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '34,219', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '34,367', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '34,368', 'INFO', 'Uploading model into container']\n", "['2020-07-31 01', '42', '34,368', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '34,421', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '34,422', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '34,429', 'INFO', \"save_model(model=VotingClassifier(estimators=[('Bagging Classifier_1',\"]\n", "['BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", 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VotingClassifier(estimators=[('Bagging Classifier_1',\"]\n", "['BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['r...']\n", "['max_depth=30,']\n", "[\"max_features='auto',\"]\n", "['max_leaf_nodes=None,']\n", "['max_samples=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=10,']\n", "['min_weight_fraction_leaf=0.0,']\n", "['n_estimators=30, n_jobs=-1,']\n", "['oob_score=False,']\n", "['random_state=123,']\n", "['verbose=0,']\n", "['warm_start=False))],']\n", "['flatten_transform=True, n_jobs=-1, verbose=False,']\n", "[\"voting='soft', weights=None)]\"]\n", "['2020-07-31 01', '42', '34,489', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '34,489', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '34,946', 'INFO', 'create_model_container', '10']\n", "['2020-07-31 01', '42', '34,947', 'INFO', 'master_model_container', '10']\n", "['2020-07-31 01', '42', '34,947', 'INFO', 'display_container', '12']\n", "['2020-07-31 01', '42', '34,953', 'INFO', \"VotingClassifier(estimators=[('Bagging Classifier_1',\"]\n", "['BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['r...']\n", "['max_depth=30,']\n", "[\"max_features='auto',\"]\n", "['max_leaf_nodes=None,']\n", "['max_samples=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=10,']\n", "['min_weight_fraction_leaf=0.0,']\n", "['n_estimators=30, n_jobs=-1,']\n", "['oob_score=False,']\n", "['random_state=123,']\n", "['verbose=0,']\n", "['warm_start=False))],']\n", "['flatten_transform=True, n_jobs=-1, verbose=False,']\n", "[\"voting='soft', weights=None)\"]\n", "['2020-07-31 01', '42', '34,954', 'INFO', 'blend_models() succesfully completed......................................']\n", "['2020-07-31 01', '42', '34,961', 'INFO', 'Initializing stack_models()']\n", "['2020-07-31 01', '42', '34,963', 'INFO', \"stack_models(estimator_list=[AdaBoostClassifier(algorithm='SAMME.R',\"]\n", "['base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", 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"['warm_start=False), fold=10, round=4, method=soft, restack=True, plot=False, choose_better=False, optimize=Accuracy, finalize=False, verbose=True)']\n", "['2020-07-31 01', '42', '34,964', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '34,965', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '34,965', 'INFO', 'Copying estimator list']\n", "['2020-07-31 01', '42', '34,970', 'INFO', 'Defining meta model']\n", "['2020-07-31 01', '42', '34,972', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '34,990', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '34,991', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '34,993', 'INFO', 'Getting model names']\n", "['2020-07-31 01', '42', '34,995', 'INFO', 'Checking base model', 'AdaBoostClassifier']\n", "['2020-07-31 01', '42', '34,999', 'INFO', 'Fitting base model']\n", "['2020-07-31 01', '42', '35,039', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 01', '42', '35,373', 'INFO', 'Checking base model', 'BaggingClassifier']\n", "['2020-07-31 01', '42', '35,378', 'INFO', 'Fitting base model']\n", "['2020-07-31 01', '42', '35,408', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 01', '42', '35,751', 'INFO', 'Checking base model', 'RandomForestClassifier']\n", "['2020-07-31 01', '42', '35,751', 'INFO', 'Fitting base model']\n", "['2020-07-31 01', '42', '35,872', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 01', '42', '37,647', 'INFO', 'Base layer complete']\n", "['2020-07-31 01', '42', '37,802', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '37,804', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '37,809', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '37,921', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '38,152', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '38,166', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '38,172', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '38,289', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '38,509', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '38,540', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '38,554', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '38,673', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '38,892', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '38,922', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '38,929', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '39,040', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '39,259', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '39,274', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '39,286', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '39,406', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '39,641', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '39,660', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '39,660', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '39,792', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '40,042', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '40,064', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '40,070', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '40,189', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '40,439', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '40,454', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '40,461', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '40,574', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '40,793', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '40,808', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '40,816', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '40,938', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '41,188', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '41,209', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '41,215', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '41,339', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '41,557', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '41,572', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '41,572', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '41,583', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '41,583', 'INFO', 'Uploading model into container']\n", "['2020-07-31 01', '42', '41,583', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '41,658', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '41,658', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '41,658', 'INFO', 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'11']\n", "['2020-07-31 01', '42', '42,222', 'INFO', 'display_container', '13']\n", "['2020-07-31 01', '42', '42,224', 'INFO', \"[AdaBoostClassifier(algorithm='SAMME.R',\"]\n", "['base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['learning_rate=1.0, n_estimators=10, random_state=123), BaggingClassifier(base_estimator=DecisionTreeClassifier(ccp_alpha=0.0,']\n", "['class_weight=None,']\n", "[\"criterion='gini',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", 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max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "[\"warm_start=False), 'soft', True]\"]\n", "['2020-07-31 01', '42', '42,224', 'INFO', 'stack_models() succesfully completed......................................']\n", "['2020-07-31 01', '42', '42,230', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '42', '42,231', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=auc, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '42,231', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '42,342', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '42,342', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '42,342', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '42,342', 'INFO', 'plot type', 'auc']\n", "['2020-07-31 01', '42', '42,412', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '42,413', 'INFO', 'Scoring test/hold-out set']\n", "['2020-07-31 01', '42', '42,806', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '42,806', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '42,819', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '42', '42,820', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=confusion_matrix, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '42,820', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '42,926', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '42,926', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '42,941', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '42,941', 'INFO', 'plot type', 'confusion_matrix']\n", "['2020-07-31 01', '42', '42,957', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '42,957', 'INFO', 'Scoring test/hold-out set']\n", "['2020-07-31 01', '42', '43,239', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '43,239', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '43,245', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '42', '43,246', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=boundary, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '43,246', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '43,359', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '43,359', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '43,359', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '43,359', 'INFO', 'plot type', 'boundary']\n", "['2020-07-31 01', '42', '43,491', 'INFO', 'Fitting StandardScaler()']\n", "['2020-07-31 01', '42', '43,497', 'INFO', 'Fitting PCA()']\n", "['2020-07-31 01', '42', '43,525', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '44,935', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '44,935', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '44,969', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '42', '44,970', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=parameter, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '44,970', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '45,076', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '45,076', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '45,076', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '45,076', 'INFO', 'plot type', 'parameter']\n", "['2020-07-31 01', '42', '45,092', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '45,092', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '45,100', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '45,100', 'INFO', 'create_model(estimator=catboost, ensemble=False, method=None, fold=10, round=4, cross_validation=False, verbose=True, system=True)']\n", "['2020-07-31 01', '42', '45,100', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '45,100', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '45,100', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '45,120', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '45,121', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '45,122', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '45,122', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '45,127', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '45,128', 'INFO', 'CatBoost Classifier Imported succesfully']\n", "['2020-07-31 01', '42', '45,128', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '45,133', 'INFO', 'Cross validation set to False']\n", "['2020-07-31 01', '42', '45,134', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '46,706', 'INFO', 'create_model_container 11']\n", "['2020-07-31 01', '42', '46,706', 'INFO', 'master_model_container 11']\n", "['2020-07-31 01', '42', '46,706', 'INFO', 'display_container 13']\n", "['2020-07-31 01', '42', '46,706', 'INFO', '']\n", "['2020-07-31 01', '42', '46,706', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-31 01', '42', '46,719', 'INFO', 'Initializing interpret_model()']\n", "['2020-07-31 01', '42', '46,719', 'INFO', 'interpret_model(estimator=, plot=summary, feature=None, observation=None)']\n", "['2020-07-31 01', '42', '46,719', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '47,417', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '47,417', 'INFO', 'plot type', 'summary']\n", "['2020-07-31 01', '42', '47,417', 'INFO', 'model type detected', 'type 2']\n", "['2020-07-31 01', '42', '47,417', 'INFO', 'Creating TreeExplainer']\n", "['2020-07-31 01', '42', '47,714', 'INFO', 'Compiling shap values']\n", "['2020-07-31 01', '42', '48,401', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '48,401', 'INFO', 'interpret_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'Initializing interpret_model()']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'interpret_model(estimator=, plot=correlation, feature=None, observation=None)']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'plot type', 'correlation']\n", "['2020-07-31 01', '42', '48,424', 'WARNING', 'No feature passed. Default value of feature used for correlation plot', 'WeekofPurchase']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'model type detected', 'type 2']\n", "['2020-07-31 01', '42', '48,424', 'INFO', 'Creating TreeExplainer']\n", "['2020-07-31 01', '42', '48,742', 'INFO', 'Compiling shap values']\n", "['2020-07-31 01', '42', '49,226', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '49,226', 'INFO', 'interpret_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '49,245', 'INFO', 'Initializing interpret_model()']\n", "['2020-07-31 01', '42', '49,245', 'INFO', 'interpret_model(estimator=, plot=reason, feature=None, observation=12)']\n", "['2020-07-31 01', '42', '49,246', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '49,246', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '49,246', 'INFO', 'plot type', 'reason']\n", "['2020-07-31 01', '42', '49,246', 'INFO', 'model type detected', 'type 2']\n", "['2020-07-31 01', '42', '49,246', 'INFO', 'Creating TreeExplainer']\n", "['2020-07-31 01', '42', '49,564', 'INFO', 'Compiling shap values']\n", "['2020-07-31 01', '42', '49,970', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '42', '49,970', 'INFO', 'interpret_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '50,001', 'INFO', 'Initializing automl()']\n", "['2020-07-31 01', '42', '50,001', 'INFO', 'automl(optimize=Recall, use_holdout=False)']\n", "['2020-07-31 01', '42', '50,001', 'INFO', 'Model Selection Basis', 'CV Results on Training set']\n", "['2020-07-31 01', '42', '50,007', 'INFO', 'SubProcess finalize_model() called ==================================']\n", "['2020-07-31 01', '42', '50,008', 'INFO', 'Initializing finalize_model()']\n", "['2020-07-31 01', '42', '50,009', 'INFO', \"finalize_model(estimator=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False))']\n", "['2020-07-31 01', '42', '50,009', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '50,009', 'INFO', 'Getting model name']\n", "['2020-07-31 01', '42', '50,009', 'INFO', 'Finalizing Logistic Regression']\n", "['2020-07-31 01', '42', '50,038', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 01', '42', '50,073', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-31 01', '42', '50,073', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 01', '42', '50,074', 'INFO', \"create_model(estimator=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 01', '42', '50,074', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '42', '50,074', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '42', '50,074', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '42', '50,082', 'INFO', 'Copying training dataset']\n", "['2020-07-31 01', '42', '50,082', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '42', '50,083', 'INFO', 'Defining folds']\n", "['2020-07-31 01', '42', '50,083', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 01', '42', '50,083', 'INFO', 'Importing untrained model']\n", "['2020-07-31 01', '42', '50,083', 'INFO', 'Declaring custom model']\n", "['2020-07-31 01', '42', '50,084', 'INFO', 'Logistic Regression Imported succesfully']\n", "['2020-07-31 01', '42', '50,085', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 01', '42', '50,087', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 01', '42', '50,088', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,114', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,121', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,126', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 01', '42', '50,128', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,152', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,158', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,162', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 01', '42', '50,163', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,181', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,181', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,181', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 01', '42', '50,196', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,212', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,212', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,228', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 01', '42', '50,228', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,243', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,259', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,259', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 01', '42', '50,259', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,275', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,290', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,290', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 01', '42', '50,290', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,306', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,321', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,321', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 01', '42', '50,321', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,353', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,353', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,353', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 01', '42', '50,353', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,389', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,402', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,407', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 01', '42', '50,409', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '42', '50,430', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 01', '42', '50,431', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 01', '42', '50,431', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 01', '42', '50,431', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 01', '42', '50,431', 'INFO', 'Finalizing model']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'Uploading results into container']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'Uploading model into container now']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'create_model_container', '12']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'master_model_container', '12']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'display_container', '14']\n", "['2020-07-31 01', '42', '50,462', 'INFO', \"LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '50,462', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-31 01', '42', '50,509', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '42', '50,509', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '42', '50,509', 'INFO', \"save_model(model=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 01', '42', '50,509', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '42', '50,509', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 01', '42', '50,509', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)]']\n", "['2020-07-31 01', '42', '50,509', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '50,509', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '42', '50,556', 'INFO', 'create_model_container', '12']\n", "['2020-07-31 01', '42', '50,556', 'INFO', 'master_model_container', '12']\n", "['2020-07-31 01', '42', '50,556', 'INFO', 'display_container', '14']\n", "['2020-07-31 01', '42', '50,556', 'INFO', \"LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '50,556', 'INFO', 'finalize_model() succesfully completed......................................']\n", "['2020-07-31 01', '42', '50,556', 'INFO', 'SubProcess finalize_model() end ==================================']\n", "['2020-07-31 01', '42', '50,556', 'INFO', \"LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '42', '50,556', 'INFO', 'automl() succesfully completed......................................']\n", "['2020-07-31 01', '45', '01,294', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '45', '01,295', 'INFO', \"save_model(model=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), model_name=best-model, verbose=True)']\n", "['2020-07-31 01', '45', '01,295', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '45', '01,303', 'INFO', 'best-model.pkl saved in current working directory']\n", "['2020-07-31 01', '45', '01,308', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)]']\n", "['2020-07-31 01', '45', '01,309', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '45', '03,776', 'INFO', 'Initializing deploy_model()']\n", "['2020-07-31 01', '45', '03,776', 'INFO', \"deploy_model(model=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "[\"warm_start=False), model_name=best-aws, authentication={'bucket'\", \"'pycaret-test'}, platform=aws)\"]\n", "['2020-07-31 01', '45', '03,798', 'INFO', 'Platform', 'AWS S3']\n", "['2020-07-31 01', '45', '03,997', 'INFO', 'Saving model in active working directory']\n", "['2020-07-31 01', '45', '03,997', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 01', '45', '03,997', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 01', '45', '03,998', 'INFO', \"save_model(model=LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False), model_name=best-aws, verbose=False)']\n", "['2020-07-31 01', '45', '03,998', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 01', '45', '04,004', 'INFO', 'best-aws.pkl saved in current working directory']\n", "['2020-07-31 01', '45', '04,008', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='classification',\"]\n", "[\"numerical_features=[], target='Purchase',\"]\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", "[\"('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='Purchase')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)]']\n", "['2020-07-31 01', '45', '04,008', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 01', '45', '04,008', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 01', '45', '04,008', 'INFO', 'Initializing S3 client']\n", "['2020-07-31 01', '45', '04,989', 'INFO', \"LogisticRegression(C=5.5600000000000005, class_weight='balanced', dual=False,\"]\n", "['fit_intercept=True, intercept_scaling=1, l1_ratio=None,']\n", "[\"max_iter=100, multi_class='auto', n_jobs=-1, penalty='l2',\"]\n", "[\"random_state=123, solver='lbfgs', tol=0.0001, verbose=0,\"]\n", "['warm_start=False)']\n", "['2020-07-31 01', '45', '04,989', 'INFO', 'deploy_model() succesfully completed......................................']\n", "['2020-07-31 01', '45', '05,013', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 01', '45', '05,013', 'INFO', 'get_config(variable=X_train)']\n", "['2020-07-31 01', '45', '05,013', 'INFO', 'Global variable', 'X_train returned']\n", "['2020-07-31 01', '45', '05,013', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 01', '45', '05,044', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 01', '45', '05,044', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-31 01', '45', '05,045', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-31 01', '45', '05,045', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 01', '45', '05,495', 'INFO', 'Initializing set_config()']\n", "['2020-07-31 01', '45', '05,495', 'INFO', 'set_config(variable=seed, value=999)']\n", "['2020-07-31 01', '45', '05,495', 'INFO', 'Global variable', 'seed updated']\n", "['2020-07-31 01', '45', '05,495', 'INFO', 'set_config() succesfully completed......................................']\n", "['2020-07-31 01', '45', '05,898', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 01', '45', '05,898', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-31 01', '45', '05,898', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-31 01', '45', '05,898', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 01', '45', '23,821', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '45', '23,822', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=FEATURE, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '45', '23,822', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '45', '27,575', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '45', '27,577', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=feature, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '45', '27,577', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '45', '27,691', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '45', '27,691', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '45', '27,691', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '45', '27,691', 'INFO', 'plot type', 'feature']\n", "['2020-07-31 01', '45', '27,691', 'WARNING', 'No coef_ found. Trying feature_importances_']\n", "['2020-07-31 01', '45', '27,906', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '45', '27,906', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 01', '45', '31,933', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '45', '31,934', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=pr, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '45', '31,934', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '45', '32,042', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '45', '32,042', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '45', '32,042', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '45', '32,042', 'INFO', 'plot type', 'pr']\n", "['2020-07-31 01', '45', '32,042', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '45', '32,057', 'INFO', 'Scoring test/hold-out set']\n", "['2020-07-31 01', '45', '32,376', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '45', '32,376', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 01', '45', '42,906', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 01', '45', '42,907', 'INFO', 'plot_model(estimator=RandomForestClassifier(bootstrap=True, ccp_alpha=0.0, class_weight=None,']\n", "[\"criterion='gini', max_depth=None, max_features='auto',\"]\n", "['max_leaf_nodes=None, max_samples=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=10, n_jobs=-1,']\n", "['oob_score=False, random_state=123, verbose=0,']\n", "['warm_start=False), plot=class_report, save=False, verbose=True, system=True)']\n", "['2020-07-31 01', '45', '42,907', 'INFO', 'Checking exceptions']\n", "['2020-07-31 01', '45', '43,013', 'INFO', 'Preloading libraries']\n", "['2020-07-31 01', '45', '43,013', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 01', '45', '43,013', 'INFO', 'Importing libraries']\n", "['2020-07-31 01', '45', '43,013', 'INFO', 'plot type', 'class_report']\n", "['2020-07-31 01', '45', '43,032', 'INFO', 'Fitting Model']\n", "['2020-07-31 01', '45', '43,033', 'INFO', 'Scoring test/hold-out set']\n", "['2020-07-31 01', '45', '43,362', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 01', '45', '43,362', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '16,732', 'INFO', 'PyCaret Regression Module']\n", "['2020-07-31 08', '44', '16,733', 'INFO', 'version 2.0']\n", "['2020-07-31 08', '44', '16,733', 'INFO', 'Initializing setup()']\n", "['2020-07-31 08', '44', '16,733', 'INFO', 'USI', '5b1c']\n", "['2020-07-31 08', '44', '16,733', '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", "['2020-07-31 08', '44', '16,733', 'INFO', 'Checking environment']\n", "['2020-07-31 08', '44', '16,733', 'INFO', 'python_version', '3.7.4']\n", "['2020-07-31 08', '44', '16,733', 'INFO', 'python_build', \"('default', 'Aug 9 2019 18\", '34', \"13')\"]\n", "['2020-07-31 08', '44', '16,733', 'INFO', 'machine', 'AMD64']\n", "['2020-07-31 08', '44', '16,734', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-31 08', '44', '16,785', 'INFO', 'Memory', 'svmem(total=17032478720, available=12508303360, percent=26.6, used=4524175360, free=12508303360)']\n", "['2020-07-31 08', '44', '16,785', 'INFO', 'Physical Core', '4']\n", "['2020-07-31 08', '44', '16,785', 'INFO', 'Logical Core', '8']\n", "['2020-07-31 08', '44', '16,785', 'INFO', 'Checking libraries']\n", "['2020-07-31 08', '44', '16,785', 'INFO', 'pd==1.0.5']\n", "['2020-07-31 08', '44', '16,785', 'INFO', 'numpy==1.18.5']\n", "['2020-07-31 08', '44', '17,421', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-31 08', '44', '17,518', 'INFO', 'xgboost==0.90']\n", "['2020-07-31 08', '44', '17,654', 'INFO', 'lightgbm==2.3.1']\n", "['2020-07-31 08', '44', '17,720', 'INFO', 'catboost==0.20.2']\n", "['2020-07-31 08', '44', '19,702', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-31 08', '44', '19,702', 'INFO', 'Checking Exceptions']\n", "['2020-07-31 08', '44', '19,702', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '44', '19,702', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '44', '19,702', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '44', '21,667', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-31 08', '44', '21,667', 'INFO', 'Declaring global variables']\n", "['2020-07-31 08', '44', '21,672', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-31 08', '44', '21,672', 'INFO', 'Importing preprocessing module']\n", "['2020-07-31 08', '44', '22,570', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-31 08', '44', '23,523', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-31 08', '44', '23,523', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '23,523', 'INFO', 'Creating grid variables']\n", "['2020-07-31 08', '44', '23,525', 'INFO', 'Creating global containers']\n", "['2020-07-31 08', '44', '23,590', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-31 08', '44', '23,723', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '23,724', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '23,728', '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", "['2020-07-31 08', '44', '23,728', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '23,732', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '23,740', '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), 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", "['2020-07-31 08', '44', '23,740', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '23,740', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '23,806', 'INFO', 'create_model_container', '0']\n", "['2020-07-31 08', '44', '23,806', 'INFO', 'master_model_container', '0']\n", "['2020-07-31 08', '44', '23,806', 'INFO', 'display_container', '0']\n", "['2020-07-31 08', '44', '23,806', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-31 08', '44', '25,731', 'INFO', 'Initializing compare_models()']\n", "['2020-07-31 08', '44', '25,731', 'INFO', 'compare_models(blacklist=None, whitelist=None, fold=5, round=4, sort=R2, n_select=1, turbo=True, verbose=True)']\n", "['2020-07-31 08', '44', '25,731', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '44', '25,731', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '44', '25,731', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '44', '25,754', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '44', '25,756', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '44', '25,767', 'INFO', 'Importing untrained models']\n", "['2020-07-31 08', '44', '25,768', 'INFO', 'Import successful']\n", "['2020-07-31 08', '44', '25,774', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '44', '25,774', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '44', '25,774', 'INFO', 'Initializing Linear Regression']\n", "['2020-07-31 08', '44', '25,782', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '25,788', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '25,795', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '25,796', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '25,797', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '25,856', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '25,873', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '25,876', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '25,877', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '25,877', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '25,883', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '25,888', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '25,892', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '25,894', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '25,894', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '25,900', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '25,905', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '25,907', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '25,909', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '25,909', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '25,915', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '25,920', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '25,923', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '25,925', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '25,925', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '25,931', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '25,932', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '25,940', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '25,990', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '25,990', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '25,991', 'INFO', 'save_model(model=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '44', '25,991', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '25,995', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '25,999', '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", "['2020-07-31 08', '44', '25,999', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '25,999', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '26,024', 'INFO', 'Initializing Lasso Regression']\n", "['2020-07-31 08', '44', '26,039', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '26,051', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,056', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,057', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,058', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,063', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '26,071', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,074', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,076', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,076', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,082', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '26,088', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,092', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,093', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,093', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,099', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '26,105', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,108', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,109', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,110', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,115', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '26,121', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,125', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,126', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,126', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,132', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '26,132', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '26,140', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '26,196', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '26,197', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '26,197', '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", "['2020-07-31 08', '44', '26,197', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '26,201', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '26,205', '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", "['2020-07-31 08', '44', '26,206', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '26,206', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '26,250', 'INFO', 'Initializing Ridge Regression']\n", "['2020-07-31 08', '44', '26,255', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '26,260', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,265', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,266', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,266', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,272', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '26,278', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,281', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,283', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,283', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,289', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '26,294', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,297', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,298', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,298', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,304', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '26,309', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,312', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,314', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,314', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,320', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '26,325', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,329', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,330', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,330', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,336', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '26,336', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '26,346', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '26,403', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '26,403', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '26,403', '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", "['2020-07-31 08', '44', '26,403', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '26,407', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '26,413', '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", "['2020-07-31 08', '44', '26,413', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '26,413', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '26,453', 'INFO', 'Initializing Elastic Net']\n", "['2020-07-31 08', '44', '26,458', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '26,463', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,467', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,468', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,468', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,474', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '26,480', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,483', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,485', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,485', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,490', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '26,496', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,498', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,500', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,500', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,505', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '26,511', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,514', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,517', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,517', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,523', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '26,528', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,530', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,532', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,532', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,538', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '26,538', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '26,552', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '26,618', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '26,618', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '26,618', '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", "['2020-07-31 08', '44', '26,619', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '26,623', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '26,627', '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", "['2020-07-31 08', '44', '26,627', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '26,628', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '26,667', 'INFO', 'Initializing Least Angle Regression']\n", "['2020-07-31 08', '44', '26,672', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '26,678', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,684', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,686', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,686', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,692', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '26,698', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,703', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,705', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,705', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,710', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '26,716', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,721', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,723', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,723', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,728', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '26,735', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,742', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,744', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,744', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,751', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '26,756', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,762', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,764', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,764', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,771', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '26,772', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '26,787', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '26,842', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '26,842', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '26,842', '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", "['2020-07-31 08', '44', '26,842', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '26,842', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '26,857', '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", "['2020-07-31 08', '44', '26,857', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '26,857', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '26,889', 'INFO', 'Initializing Lasso Least Angle Regression']\n", "['2020-07-31 08', '44', '26,909', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '26,918', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,923', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,924', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,924', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,932', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '26,937', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,943', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,945', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,945', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,954', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '26,961', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,967', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,968', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,969', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,975', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '26,982', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '26,988', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '26,990', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '26,990', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '26,997', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '27,003', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,009', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,012', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,012', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,021', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '27,021', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '27,032', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '27,089', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '27,090', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '27,090', '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", "['2020-07-31 08', '44', '27,090', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '27,095', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '27,100', '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", "['2020-07-31 08', '44', '27,100', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '27,100', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '27,144', 'INFO', 'Initializing Orthogonal Matching Pursuit']\n", "['2020-07-31 08', '44', '27,148', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '27,155', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,158', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,160', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,160', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,166', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '27,173', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,177', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,178', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,179', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,186', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '27,194', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,197', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,199', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,199', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,206', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '27,213', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,216', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,218', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,218', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,224', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '27,232', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,236', 'INFO', 'Evaluating Metrics']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-31 08', '44', '27,237', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,237', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,244', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '27,245', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '27,262', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '27,325', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '27,325', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '27,326', '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", "['2020-07-31 08', '44', '27,326', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '27,331', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '27,335', '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", "['2020-07-31 08', '44', '27,335', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '27,335', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '27,376', 'INFO', 'Initializing Bayesian Ridge']\n", "['2020-07-31 08', '44', '27,381', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '27,387', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,393', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,395', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,396', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,403', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '27,410', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,415', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,417', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,417', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,423', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '27,429', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,434', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,435', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,436', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,441', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '27,447', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,455', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,457', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,457', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,463', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '27,469', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,474', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,476', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,476', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,482', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '27,482', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '27,493', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '27,550', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '27,551', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '27,551', '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", "['2020-07-31 08', '44', '27,551', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '27,556', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '27,559', '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", "['2020-07-31 08', '44', '27,559', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '27,559', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '27,590', 'INFO', 'Initializing Passive Aggressive Regressor']\n", "['2020-07-31 08', '44', '27,606', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '27,612', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,619', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,620', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,620', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,626', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '27,631', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,638', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,640', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,640', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,645', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '27,651', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,656', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,658', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,658', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,664', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '27,669', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,675', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,677', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,677', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,683', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '27,687', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,694', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,696', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,696', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,701', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '27,702', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '27,712', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '27,773', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '27,773', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '27,774', '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", "['2020-07-31 08', '44', '27,774', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '27,775', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '27,783', '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", "['2020-07-31 08', '44', '27,783', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '27,783', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '27,826', 'INFO', 'Initializing Random Sample Consensus']\n", "['2020-07-31 08', '44', '27,831', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '27,836', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '27,923', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '27,924', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '27,924', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '27,930', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '27,935', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '28,015', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '28,017', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '28,017', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '28,022', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '28,027', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '28,105', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '28,106', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '28,106', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '28,112', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '28,116', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '28,195', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '28,197', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '28,197', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '28,202', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '28,208', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '28,298', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '28,300', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '28,300', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '28,306', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '28,306', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '28,322', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '28,377', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '28,377', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '28,377', '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", "['2020-07-31 08', '44', '28,377', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '28,377', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '28,396', '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", "['2020-07-31 08', '44', '28,396', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '28,396', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '28,441', 'INFO', 'Initializing TheilSen Regressor']\n", "['2020-07-31 08', '44', '28,446', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '28,450', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '30,326', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '30,328', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '30,328', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '30,334', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '30,339', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '30,808', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '30,808', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '30,808', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '30,824', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '30,830', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '31,292', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '31,292', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '31,292', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '31,307', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '31,313', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '31,820', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '31,822', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '31,822', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '31,827', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '31,827', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,321', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,321', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,321', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,336', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '32,336', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '32,353', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '32,409', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '32,409', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '32,410', '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", "['2020-07-31 08', '44', '32,410', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '32,410', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '32,410', '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), 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", "['2020-07-31 08', '44', '32,410', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '32,410', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '32,457', 'INFO', 'Initializing Huber Regressor']\n", "['2020-07-31 08', '44', '32,457', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '32,468', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,520', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,522', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,522', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,527', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '32,527', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,579', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,580', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,580', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,586', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '32,591', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,636', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,638', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,638', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,643', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '32,650', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,690', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,692', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,692', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,697', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '32,702', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,749', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,750', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,750', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,756', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '32,756', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '32,761', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '32,821', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '32,822', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '32,822', '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", "['2020-07-31 08', '44', '32,822', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '32,827', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '32,831', '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", "['2020-07-31 08', '44', '32,831', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '32,831', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '32,860', 'INFO', 'Initializing Support Vector Machine']\n", "['2020-07-31 08', '44', '32,860', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '32,880', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,938', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,942', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,943', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,948', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '32,953', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '32,976', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '32,981', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '32,981', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '32,986', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '32,990', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,013', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,018', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,018', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,024', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '33,029', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,053', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,058', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,058', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,062', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '33,067', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,092', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,096', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,096', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,101', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '33,102', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '33,113', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '33,175', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '33,176', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '33,176', '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", "['2020-07-31 08', '44', '33,176', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '33,177', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '33,177', '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", "['2020-07-31 08', '44', '33,177', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '33,177', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '33,211', 'INFO', 'Initializing K Neighbors Regressor']\n", "['2020-07-31 08', '44', '33,227', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '33,227', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,227', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,358', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,358', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,373', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '33,383', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,388', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,507', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,507', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,507', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '33,519', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,523', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,641', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,641', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,657', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '33,669', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,674', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,780', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,780', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,788', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '33,794', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '33,798', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '33,908', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '33,908', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '33,908', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '33,908', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '33,945', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '34,004', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '34,005', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '34,005', '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", "['2020-07-31 08', '44', '34,005', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '34,010', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '34,011', '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", "['2020-07-31 08', '44', '34,011', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '34,011', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '34,042', 'INFO', 'Initializing Decision Tree']\n", "['2020-07-31 08', '44', '34,060', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '34,065', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,070', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,072', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,072', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,078', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '34,084', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,089', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,090', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,090', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,096', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '34,101', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,105', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,107', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,107', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,113', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '34,118', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,122', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,124', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,124', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,130', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '34,135', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,140', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,141', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,141', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,147', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '34,147', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '34,159', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '34,216', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '34,217', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '34,217', '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", "['2020-07-31 08', '44', '34,217', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '34,222', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '34,226', '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", "['2020-07-31 08', '44', '34,226', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '34,226', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '34,259', 'INFO', 'Initializing Random Forest']\n", "['2020-07-31 08', '44', '34,259', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '34,276', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,425', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,550', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,550', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,550', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '34,561', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '34,708', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '34,813', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '34,814', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '34,828', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '34,844', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '35,092', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '35,197', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '35,197', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '35,203', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '35,208', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '35,456', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '35,575', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '35,575', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '35,582', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '35,590', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '35,840', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '35,966', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '35,966', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '35,966', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '35,966', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '35,981', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '36,045', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '36,045', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '36,045', '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", "['2020-07-31 08', '44', '36,045', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '36,076', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '36,076', '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", "['2020-07-31 08', '44', '36,076', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '36,076', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '36,123', 'INFO', 'Initializing Extra Trees Regressor']\n", "['2020-07-31 08', '44', '36,123', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '36,141', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '36,290', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '36,396', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '36,396', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '36,412', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '36,412', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '36,574', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '36,684', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '36,684', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '36,684', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '36,699', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '36,842', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '36,962', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '36,962', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '36,977', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '36,990', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,141', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,267', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,267', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,282', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '37,299', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,441', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,558', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,558', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,558', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '37,558', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '37,573', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '37,661', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '37,661', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '37,661', '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", "['2020-07-31 08', '44', '37,661', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '37,693', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '37,693', '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", "['2020-07-31 08', '44', '37,693', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '37,693', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '37,739', 'INFO', 'Initializing AdaBoost Regressor']\n", "['2020-07-31 08', '44', '37,739', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '37,758', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,782', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,785', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,785', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,790', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '37,797', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,817', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,820', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,820', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,827', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '37,833', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,851', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,854', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,854', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,861', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '37,866', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,882', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,884', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,884', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,891', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '37,897', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '37,916', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '37,918', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '37,918', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '37,925', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '37,925', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '37,939', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '37,998', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '37,998', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '37,999', '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", "['2020-07-31 08', '44', '37,999', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '38,008', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '38,013', '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", "['2020-07-31 08', '44', '38,013', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '38,013', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '38,045', 'INFO', 'Initializing Gradient Boosting Regressor']\n", "['2020-07-31 08', '44', '38,045', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '38,066', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,130', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,145', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,145', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,145', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '38,159', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,230', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,230', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,230', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,230', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '38,245', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,318', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,320', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,320', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,326', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '38,332', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,396', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,396', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,396', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,396', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '38,415', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,484', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,486', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,486', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,492', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '38,492', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '38,508', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '38,563', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '38,563', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '38,563', '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", "['2020-07-31 08', '44', '38,563', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '38,563', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '38,578', '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", "['2020-07-31 08', '44', '38,578', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '38,578', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '38,625', 'INFO', 'Initializing Extreme Gradient Boosting']\n", "['2020-07-31 08', '44', '38,625', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '38,642', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,685', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,686', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,687', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,697', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '38,711', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,753', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,755', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,755', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,773', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '38,783', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,827', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,829', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,829', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,846', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '38,855', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,899', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,901', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,901', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,914', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '38,926', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '38,968', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '38,970', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '38,970', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '38,982', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '38,983', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '39,014', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '39,096', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '39,096', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '39,096', 'INFO', \"save_model(model=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '44', '39,096', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '39,096', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '39,112', '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,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0), None]']\n", "['2020-07-31 08', '44', '39,112', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '39,112', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '39,143', 'INFO', 'Initializing Light Gradient Boosting Machine']\n", "['2020-07-31 08', '44', '39,159', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '39,165', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '39,231', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '39,246', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '39,246', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '39,246', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '39,269', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '39,361', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '39,365', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '39,365', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '39,378', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '39,388', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '39,482', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '39,486', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '39,486', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '39,499', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '39,510', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '39,581', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '39,581', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '39,581', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '39,596', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '39,608', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '39,693', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '39,697', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '39,697', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '39,710', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '39,710', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '39,742', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '39,836', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '39,836', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '39,837', '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", "['2020-07-31 08', '44', '39,837', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '39,848', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '39,848', '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", "['2020-07-31 08', '44', '39,848', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '39,848', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '39,956', 'INFO', 'Initializing CatBoost Regressor']\n", "['2020-07-31 08', '44', '39,961', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '39,969', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '41,306', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '41,306', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '41,306', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '41,322', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '41,330', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '42,400', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '42,402', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '42,403', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '42,410', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '42,416', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '43,476', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '43,492', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '43,492', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '43,492', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '43,504', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '44,609', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '44,609', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '44,609', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '44,609', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '44,627', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '45,698', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '45,698', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '44', '45,698', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '45,698', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '45,698', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '45,723', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '44', '45,774', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '44', '45,775', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '44', '45,775', 'INFO', 'save_model(model=, model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '44', '45,775', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '44', '45,813', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '44', '45,834', '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", "['2020-07-31 08', '44', '45,834', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '45,834', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '44', '45,916', 'INFO', 'Finalizing top_n models']\n", "['2020-07-31 08', '44', '45,916', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-31 08', '44', '45,927', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '44', '45,927', 'INFO', 'create_model(estimator=xgboost, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '44', '45,927', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '44', '45,927', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '44', '45,927', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '44', '45,935', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '44', '45,935', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '44', '45,936', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '44', '45,936', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '44', '45,937', 'INFO', 'Extreme Gradient Boosting Regressor Imported succesfully']\n", "['2020-07-31 08', '44', '45,937', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '44', '45,938', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '44', '45,939', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '45,977', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '45,979', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '45,979', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '45,990', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '44', '45,992', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,031', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,033', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,033', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,044', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '44', '46,048', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,067', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,083', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,083', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,083', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '44', '46,083', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,129', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,129', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,129', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,129', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '44', '46,145', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,176', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,176', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,176', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,192', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '44', '46,192', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,223', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,223', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,223', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,239', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '44', '46,239', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,270', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,270', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,270', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,286', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '44', '46,286', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,335', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,337', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,337', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,349', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '44', '46,350', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,397', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,397', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,397', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,412', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '44', '46,412', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '44', '46,459', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '44', '46,459', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '44', '46,459', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '44', '46,475', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '44', '46,475', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '44', '46,490', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'create_model_container', '1']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'master_model_container', '1']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'display_container', '1']\n", "['2020-07-31 08', '44', '46,521', 'INFO', \"XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '44', '46,521', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-31 08', '44', '46,646', 'INFO', 'create_model_container', '1']\n", "['2020-07-31 08', '44', '46,646', 'INFO', 'master_model_container', '1']\n", "['2020-07-31 08', '44', '46,646', 'INFO', 'display_container', '2']\n", "['2020-07-31 08', '44', '46,646', 'INFO', \"XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)']\n", "['2020-07-31 08', '44', '46,646', 'INFO', 'compare_models() succesfully completed......................................']\n", "['2020-07-31 08', '45', '06,693', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '06,693', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '06,694', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '06,694', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '06,694', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '06,717', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '06,717', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '06,718', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '06,718', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '06,722', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '06,723', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '06,728', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '06,733', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '06,819', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '06,823', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '06,823', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '06,852', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '06,860', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '06,951', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '06,955', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '06,955', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '06,984', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '06,992', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '07,090', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '07,094', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '07,094', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '07,123', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '07,132', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '07,207', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '07,207', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '07,207', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '07,246', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '07,255', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '07,339', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '07,343', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '07,343', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '07,374', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '07,383', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '07,466', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '07,469', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '07,469', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '07,499', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '07,507', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '07,591', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '07,595', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '07,595', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '07,626', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '07,635', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '07,717', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '07,721', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '07,721', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '07,753', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '07,761', 'INFO', 'Fitting Model']\n", 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'08,329', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '08,330', '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", "['2020-07-31 08', '45', '08,330', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '08,349', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '08,360', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", 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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", "['2020-07-31 08', '45', '08,360', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '08,361', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '08,401', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '08,401', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '08,459', 'INFO', 'create_model_container', '2']\n", "['2020-07-31 08', '45', '08,459', 'INFO', 'master_model_container', '2']\n", "['2020-07-31 08', '45', '08,459', 'INFO', 'display_container', '3']\n", "['2020-07-31 08', '45', '08,459', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, 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'45', '09,754', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '09,755', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '09,756', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '09,756', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '09,761', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '09,761', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '09,766', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '09,771', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '09,853', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '09,857', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '09,857', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '09,886', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '09,894', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '09,980', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '09,984', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '09,984', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '10,013', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '10,023', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '10,104', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '10,108', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '10,108', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '10,137', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '10,145', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '10,250', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '10,253', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '10,254', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '10,285', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '10,294', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '10,393', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '10,396', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '10,397', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '10,426', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '10,435', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '10,516', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '10,520', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '10,520', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '10,542', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '10,565', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '10,650', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '10,654', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '10,654', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '10,685', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '10,693', 'INFO', 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std']\n", "['2020-07-31 08', '45', '11,077', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '11,094', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '11,191', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '11,397', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '11,397', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '11,398', '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", "['2020-07-31 08', '45', '11,399', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '11,417', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '11,427', '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", "['2020-07-31 08', '45', '11,428', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '11,428', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '11,465', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '11,465', 'INFO', 'Uploading model into 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'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '11,523', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '11,523', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '11,523', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '11,540', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '11,541', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '11,542', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '11,542', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '11,546', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '11,547', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '11,551', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '11,557', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '11,638', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '11,642', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '11,642', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '11,670', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '11,679', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '11,784', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '11,788', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '11,788', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '11,812', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '11,820', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,003', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,007', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,007', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,037', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '12,046', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,125', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,126', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,126', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,159', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '12,168', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,250', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,254', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,254', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,285', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '12,294', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,383', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,387', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,387', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,417', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '12,426', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,492', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,508', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,508', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,542', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '12,550', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,660', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,663', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,664', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,698', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '12,708', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,794', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,798', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,798', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,830', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '12,838', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '12,921', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '12,925', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '12,925', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '12,959', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '12,961', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '12,975', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '13,077', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '13,302', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '13,303', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '13,304', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.2, 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", "['2020-07-31 08', '45', '13,304', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '13,323', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '13,335', '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", 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subsample_freq=0), None]']\n", "['2020-07-31 08', '45', '13,335', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '13,335', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '13,373', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '13,373', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '13,434', 'INFO', 'create_model_container', '4']\n", "['2020-07-31 08', '45', '13,434', 'INFO', 'master_model_container', '4']\n", "['2020-07-31 08', '45', '13,434', 'INFO', 'display_container', '5']\n", "['2020-07-31 08', '45', '13,434', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.2, 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", "['2020-07-31 08', '45', '13,435', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '13,435', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '13,435', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '13,435', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '13,435', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '13,435', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '13,452', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '13,452', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '13,453', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '13,453', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '13,458', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '13,458', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '13,463', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '13,469', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '13,542', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '13,542', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '13,542', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '13,579', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '13,588', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '13,659', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '13,659', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '13,659', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '13,700', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '13,708', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '13,776', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '13,776', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '13,776', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '13,820', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '13,828', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '13,910', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '13,910', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '13,910', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '13,943', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '13,951', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '14,043', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '14,043', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '14,043', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '14,081', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '14,090', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '14,196', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '14,200', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '14,200', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '14,230', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '14,240', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '14,334', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '14,337', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '14,338', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '14,370', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '14,379', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '14,463', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '14,467', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '14,467', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '14,498', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '14,507', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '14,588', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '14,592', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '14,592', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '14,625', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '14,634', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '14,732', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '14,736', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '14,736', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '14,767', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '14,769', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '14,783', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '14,871', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '15,089', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '15,090', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '15,091', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.30000000000000004,\"]\n", "['max_depth=-1, min_child_samples=20, min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100, n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123, reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0, subsample_for_bin=200000,']\n", "['subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '45', '15,091', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '15,110', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '15,122', '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), 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'master_model_container', '5']\n", "['2020-07-31 08', '45', '15,219', 'INFO', 'display_container', '6']\n", "['2020-07-31 08', '45', '15,219', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.30000000000000004,\"]\n", "['max_depth=-1, min_child_samples=20, min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100, n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123, reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0, subsample_for_bin=200000,']\n", "['subsample_freq=0)']\n", "['2020-07-31 08', '45', '15,219', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '15,220', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '15,220', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '15,220', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '15,220', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '15,220', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '15,236', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '15,237', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '15,238', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '15,238', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '15,242', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '15,243', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '15,247', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '15,252', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '15,327', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '15,327', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '15,327', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '15,364', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '15,373', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '15,457', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '15,461', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '15,461', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '15,489', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '15,497', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '15,578', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '15,578', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '15,578', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '15,610', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '15,619', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '15,726', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '15,730', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '15,730', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '15,759', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '15,769', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '15,861', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '15,865', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '15,865', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '15,897', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '15,906', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '16,004', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '16,008', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '16,008', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '16,039', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '16,049', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '16,142', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '16,146', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '16,147', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '16,180', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '16,189', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '16,280', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '16,284', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '16,284', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '16,315', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '16,325', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '16,410', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '16,414', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '16,414', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '16,449', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '16,458', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '16,553', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '16,557', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '16,557', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '16,592', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '16,594', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '16,608', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '16,701', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '16,919', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '16,920', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '16,921', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.4, 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, 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"[\"('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=0.4, 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", "['2020-07-31 08', '45', '16,956', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '16,956', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '16,995', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '16,995', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '17,052', 'INFO', 'create_model_container', '6']\n", "['2020-07-31 08', '45', '17,052', 'INFO', 'master_model_container', '6']\n", "['2020-07-31 08', '45', '17,053', 'INFO', 'display_container', '7']\n", "['2020-07-31 08', '45', '17,053', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.4, 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", "['2020-07-31 08', '45', '17,053', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '17,054', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '17,054', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '17,054', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '17,054', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '17,054', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '17,072', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '17,072', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '17,073', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '17,074', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '17,078', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '17,079', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '17,083', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '17,087', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,160', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,160', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,160', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,198', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '17,207', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,292', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,296', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,296', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,323', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '17,333', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,428', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,432', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,432', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,465', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '17,474', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,575', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,578', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,579', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,610', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '17,618', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,703', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,707', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,707', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,738', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '17,744', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,830', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,834', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,834', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,865', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '17,873', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '17,945', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '17,961', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '17,961', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '17,992', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '18,001', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '18,090', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '18,094', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '18,094', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '18,128', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '18,140', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '18,227', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '18,232', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '18,232', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '18,268', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '18,276', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '18,360', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '18,364', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '18,365', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '18,399', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '18,401', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '18,414', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '18,521', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '18,779', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '18,779', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '18,779', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.5, 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", "['2020-07-31 08', '45', '18,779', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '18,795', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '18,811', '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=0.5, 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", "['2020-07-31 08', '45', '18,811', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '18,811', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '18,857', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '18,857', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '18,918', 'INFO', 'create_model_container', '7']\n", "['2020-07-31 08', '45', '18,918', 'INFO', 'master_model_container', '7']\n", "['2020-07-31 08', '45', '18,918', 'INFO', 'display_container', '8']\n", "['2020-07-31 08', '45', '18,918', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.5, 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", "['2020-07-31 08', '45', '18,918', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '18,919', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '18,919', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '18,919', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '18,919', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '18,919', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '18,934', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '18,935', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '18,935', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '18,936', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '18,940', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '18,941', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '18,946', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '18,951', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,042', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,046', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,047', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,076', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '19,087', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,162', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,162', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,162', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,205', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '19,214', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,296', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,296', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,296', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,330', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '19,339', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,424', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,428', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,428', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,458', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '19,467', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,578', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,578', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,578', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,618', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '19,628', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,716', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,720', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,720', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,752', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '19,761', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,843', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,847', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,848', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '19,881', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '19,890', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '19,986', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '19,990', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '19,990', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '20,023', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '20,032', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '20,122', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '20,126', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '20,126', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '20,163', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '20,172', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '20,246', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '20,246', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '20,246', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '20,292', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '20,294', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '20,309', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '20,394', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '20,611', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '20,612', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '20,613', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.6, 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", "['2020-07-31 08', '45', '20,613', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '20,630', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '20,645', '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=0.6, 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", "['2020-07-31 08', '45', '20,645', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '20,645', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '20,692', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '20,692', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '20,742', 'INFO', 'create_model_container', '8']\n", "['2020-07-31 08', '45', '20,742', 'INFO', 'master_model_container', '8']\n", "['2020-07-31 08', '45', '20,742', 'INFO', 'display_container', '9']\n", "['2020-07-31 08', '45', '20,743', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.6, 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", "['2020-07-31 08', '45', '20,743', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '20,744', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '20,744', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '20,744', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '20,744', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '20,744', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '20,760', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '20,760', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '20,761', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '20,761', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '20,765', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '20,766', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '20,770', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '20,777', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '20,846', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '20,846', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '20,846', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '20,888', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '20,897', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '20,996', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '20,996', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '20,996', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,041', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '21,051', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '21,146', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '21,162', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '21,162', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,200', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '21,215', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '21,297', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '21,313', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '21,313', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,346', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '21,356', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '21,450', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '21,454', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '21,454', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,485', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '21,497', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '21,597', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '21,601', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '21,601', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,634', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '21,643', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '21,742', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '21,747', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '21,747', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,782', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '21,795', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '21,879', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '21,879', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '21,879', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '21,924', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '21,934', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '22,027', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '22,043', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '22,043', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '22,084', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '22,093', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '22,195', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '22,195', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '22,195', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '22,245', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '22,248', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '22,266', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '22,362', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '22,584', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '22,584', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '22,586', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.7000000000000001,\"]\n", "['max_depth=-1, min_child_samples=20, min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100, n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123, reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0, subsample_for_bin=200000,']\n", "['subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '45', '22,586', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '22,609', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '22,614', '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=0.7000000000000001,\"]\n", "['max_depth=-1, min_child_samples=20, min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100, n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123, reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0, subsample_for_bin=200000,']\n", "['subsample_freq=0), None]']\n", "['2020-07-31 08', '45', '22,614', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '22,614', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '22,692', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '22,692', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '22,739', 'INFO', 'create_model_container', '9']\n", "['2020-07-31 08', '45', '22,739', 'INFO', 'master_model_container', '9']\n", "['2020-07-31 08', '45', '22,739', 'INFO', 'display_container', '10']\n", "['2020-07-31 08', '45', '22,743', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.7000000000000001,\"]\n", "['max_depth=-1, min_child_samples=20, min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100, n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123, reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0, subsample_for_bin=200000,']\n", "['subsample_freq=0)']\n", "['2020-07-31 08', '45', '22,743', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '22,744', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '22,748', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '22,748', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '22,748', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '22,748', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '22,799', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '22,802', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '22,803', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '22,803', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '22,812', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '22,812', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '22,827', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '22,844', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '22,930', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '22,930', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '22,930', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '22,969', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '22,979', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,064', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,064', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,064', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,098', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '23,113', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,197', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,197', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,197', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,235', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '23,244', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,330', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,331', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,331', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,365', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '23,375', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,498', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,502', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,503', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,544', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '23,554', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,660', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,664', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,664', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,699', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '23,710', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,811', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,816', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,816', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,851', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '23,861', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '23,947', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '23,947', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '23,947', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '23,987', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '23,996', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '24,081', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '24,081', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '24,081', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '24,122', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '24,132', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '24,229', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '24,229', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '24,229', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '24,271', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '24,273', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '24,288', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '24,380', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '24,596', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '24,597', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '24,598', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.8, 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", "['2020-07-31 08', '45', '24,598', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '24,614', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '24,614', '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=0.8, 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", "['2020-07-31 08', '45', '24,629', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '24,629', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '24,660', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '24,660', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '24,726', 'INFO', 'create_model_container', '10']\n", "['2020-07-31 08', '45', '24,726', 'INFO', 'master_model_container', '10']\n", "['2020-07-31 08', '45', '24,726', 'INFO', 'display_container', '11']\n", "['2020-07-31 08', '45', '24,726', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.8, 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", "['2020-07-31 08', '45', '24,726', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '24,727', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '24,727', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '24,727', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '24,727', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '24,727', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '24,744', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '24,744', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '24,745', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '24,745', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '24,750', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '45', '24,750', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '24,755', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '24,760', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '24,841', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '24,845', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '24,845', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '24,875', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '24,884', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '24,965', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '24,965', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '24,965', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,005', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '25,015', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,130', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,130', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,130', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,165', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '25,165', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,280', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,280', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,280', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,318', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '25,327', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,423', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,427', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,427', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,460', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '25,469', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,572', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,577', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,577', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,612', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '25,621', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,698', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,698', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,698', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,747', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '25,755', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,832', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,832', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,832', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '25,878', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '25,887', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '25,981', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '25,986', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '25,986', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '26,023', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '26,034', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '26,137', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '26,142', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '26,142', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '26,180', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '26,182', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '26,197', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '26,299', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '26,531', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '26,532', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '26,533', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.9, 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", "['2020-07-31 08', '45', '26,533', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '26,548', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '26,564', '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=0.9, 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", "['2020-07-31 08', '45', '26,564', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '26,564', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '26,626', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '26,626', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '26,673', 'INFO', 'create_model_container', '11']\n", "['2020-07-31 08', '45', '26,673', 'INFO', 'master_model_container', '11']\n", "['2020-07-31 08', '45', '26,673', 'INFO', 'display_container', '12']\n", "['2020-07-31 08', '45', '26,675', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.9, 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", "['2020-07-31 08', '45', '26,675', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '35,225', 'INFO', 'Initializing tune_model()']\n", "['2020-07-31 08', '45', '35,225', 'INFO', \"tune_model(estimator=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), fold=10, round=4, n_iter=50, custom_grid=None, optimize=MAE, choose_better=False, verbose=True)']\n", "['2020-07-31 08', '45', '35,226', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '35,226', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '35,226', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '35,246', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '35,246', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '35,247', 'INFO', 'Checking base model']\n", "['2020-07-31 08', '45', '35,248', 'INFO', 'Base model', 'Light Gradient Boosting Machine']\n", "['2020-07-31 08', '45', '35,249', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '35,249', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '35,255', 'INFO', 'Defining Hyperparameters']\n", "['2020-07-31 08', '45', '35,255', 'INFO', 'Initializing RandomizedSearchCV']\n", "['2020-07-31 08', '45', '37,358', 'INFO', 'Random search completed']\n", "['2020-07-31 08', '45', '37,367', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '37,377', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,389', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,392', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,423', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '37,431', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,444', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,447', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,478', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '37,488', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,500', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,504', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,536', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '37,545', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,564', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,567', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,598', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '37,608', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,621', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,625', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,656', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '37,664', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,677', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,681', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,717', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '37,726', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,738', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,741', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,778', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '37,788', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,802', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,806', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,841', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '37,851', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,863', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,866', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,903', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '37,913', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '37,926', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '37,930', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '37,967', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '37,969', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '37,984', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '37,996', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '37,996', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '37,997', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '38,113', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '38,113', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '38,114', 'INFO', \"save_model(model=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.3, max_depth=70,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.2,']\n", "['n_estimators=10, n_jobs=-1, num_leaves=10, objective=None,']\n", "['random_state=123, reg_alpha=0.4, reg_lambda=0.1, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '45', '38,114', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '38,121', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '38,132', '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=0.3, max_depth=70,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.2,']\n", "['n_estimators=10, n_jobs=-1, num_leaves=10, objective=None,']\n", "['random_state=123, reg_alpha=0.4, reg_lambda=0.1, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), None]']\n", "['2020-07-31 08', '45', '38,132', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '38,132', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '38,394', 'INFO', 'create_model_container', '12']\n", "['2020-07-31 08', '45', '38,394', 'INFO', 'master_model_container', '12']\n", "['2020-07-31 08', '45', '38,395', 'INFO', 'display_container', '13']\n", "['2020-07-31 08', '45', '38,395', 'INFO', \"LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\"]\n", "[\"importance_type='split', learning_rate=0.3, max_depth=70,\"]\n", "['min_child_samples=20, min_child_weight=0.001, min_split_gain=0.2,']\n", "['n_estimators=10, n_jobs=-1, num_leaves=10, objective=None,']\n", "['random_state=123, reg_alpha=0.4, reg_lambda=0.1, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0)']\n", "['2020-07-31 08', '45', '38,395', 'INFO', 'tune_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '38,408', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '45', '38,409', 'INFO', 'create_model(estimator=dt, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=True, system=True)']\n", "['2020-07-31 08', '45', '38,409', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '38,409', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '38,409', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '38,428', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '38,428', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '38,429', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '38,430', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '38,435', 'INFO', 'Decision Tree Regressor Imported succesfully']\n", "['2020-07-31 08', '45', '38,437', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '45', '38,440', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '38,446', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,451', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,453', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,453', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,467', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '38,472', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,478', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,479', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,479', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,493', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '38,500', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,505', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,507', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,507', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,521', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '38,527', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,532', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,534', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,534', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,549', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '38,555', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,560', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,562', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,562', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,577', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '38,583', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,588', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,590', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,590', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,606', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '38,612', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,617', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,619', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,619', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,635', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '38,640', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,647', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,648', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,648', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,664', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '38,671', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,675', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,677', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,677', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,693', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '38,698', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '38,704', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '38,705', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '45', '38,705', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '38,722', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '38,723', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '38,731', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '38,739', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '38,888', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '38,888', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '38,889', '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", "['2020-07-31 08', '45', '38,889', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '38,895', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '38,900', '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", "['2020-07-31 08', '45', '38,900', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '38,901', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '38,918', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '38,918', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '38,949', 'INFO', 'create_model_container', '13']\n", "['2020-07-31 08', '45', '38,949', 'INFO', 'master_model_container', '13']\n", "['2020-07-31 08', '45', '38,949', 'INFO', 'display_container', '14']\n", "['2020-07-31 08', '45', '38,950', 'INFO', \"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')\"]\n", "['2020-07-31 08', '45', '38,950', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '38,955', 'INFO', 'Initializing ensemble_model()']\n", "['2020-07-31 08', '45', '38,955', 'INFO', \"ensemble_model(estimator=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'), method=Bagging, fold=10, n_estimators=50, round=4, choose_better=False, optimize=R2, verbose=True)\"]\n", "['2020-07-31 08', '45', '38,955', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '38,955', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '38,955', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '38,978', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '38,978', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '38,980', 'INFO', 'Checking base model']\n", "['2020-07-31 08', '45', '38,981', 'INFO', 'Base model', 'Decision Tree']\n", "['2020-07-31 08', '45', '38,985', 'INFO', 'BaggingRegressor() succesfully imported']\n", "['2020-07-31 08', '45', '38,990', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '38,991', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '38,996', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '39,156', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '39,162', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '39,178', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '39,183', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '39,330', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '39,335', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '39,350', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '39,355', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '39,486', 'INFO', 'Evaluating Metrics']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-31 08', '45', '39,486', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '39,515', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '39,521', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '39,651', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '39,666', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '39,684', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '39,689', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '39,816', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '39,816', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '39,844', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '39,849', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '39,986', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '39,986', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '40,007', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '40,012', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '40,154', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '40,154', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '40,178', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '40,183', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '40,327', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '40,332', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '40,348', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '40,353', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '40,503', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '40,509', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '40,528', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '40,533', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '40,698', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '40,704', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '40,721', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '40,722', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '40,730', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '40,882', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '40,882', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '40,883', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '40,950', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '40,951', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '40,952', 'INFO', 'save_model(model=BaggingRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=50, n_jobs=None, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '45', '40,952', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '40,976', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '40,981', '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), BaggingRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=50, n_jobs=None, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-31 08', '45', '40,981', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '40,981', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '41,120', 'INFO', 'create_model_container', '14']\n", "['2020-07-31 08', '45', '41,120', 'INFO', 'master_model_container', '14']\n", "['2020-07-31 08', '45', '41,120', 'INFO', 'display_container', '15']\n", "['2020-07-31 08', '45', '41,120', 'INFO', 'BaggingRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "['bootstrap=True, bootstrap_features=False, max_features=1.0,']\n", "['max_samples=1.0, n_estimators=50, n_jobs=None, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False)']\n", "['2020-07-31 08', '45', '41,120', 'INFO', 'ensemble_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '41,133', 'INFO', 'Initializing ensemble_model()']\n", "['2020-07-31 08', '45', '41,134', 'INFO', \"ensemble_model(estimator=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'), method=Boosting, fold=10, n_estimators=10, round=4, choose_better=False, optimize=R2, verbose=True)\"]\n", "['2020-07-31 08', '45', '41,134', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '41,134', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '41,134', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '41,157', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '41,157', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '41,159', 'INFO', 'Checking base model']\n", "['2020-07-31 08', '45', '41,160', 'INFO', 'Base model', 'Decision Tree']\n", "['2020-07-31 08', '45', '41,166', 'INFO', 'AdaBoostRegressor() succesfully imported']\n", "['2020-07-31 08', '45', '41,172', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '41,172', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '41,179', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,212', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,214', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,228', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '41,233', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,265', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,268', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,283', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '41,288', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,322', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,325', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,339', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '41,345', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,378', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,380', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,395', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '41,399', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,443', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,445', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,460', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '45', '41,465', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,496', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,499', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,516', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '45', '41,521', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,555', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,557', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,573', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '45', '41,578', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,616', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,619', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,638', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '45', '41,644', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,686', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,690', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,707', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '45', '41,713', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '41,749', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '41,751', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '41,768', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '45', '41,768', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '45', '41,776', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '45', '41,814', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '45', '41,814', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '45', '41,814', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '45', '41,869', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '45', '41,869', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '45', '41,870', 'INFO', 'save_model(model=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '45', '41,871', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '45', '41,878', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '45', '41,883', '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=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), None]']\n", "['2020-07-31 08', '45', '41,883', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '41,883', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '45', '42,011', 'INFO', 'create_model_container', '15']\n", "['2020-07-31 08', '45', '42,011', 'INFO', 'master_model_container', '15']\n", "['2020-07-31 08', '45', '42,011', 'INFO', 'display_container', '16']\n", "['2020-07-31 08', '45', '42,012', 'INFO', 'AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123)']\n", "['2020-07-31 08', '45', '42,012', 'INFO', 'ensemble_model() succesfully completed......................................']\n", "['2020-07-31 08', '45', '42,017', 'INFO', 'Initializing blend_models()']\n", "['2020-07-31 08', '45', '42,017', 'INFO', 'blend_models(estimator_list=All, fold=10, round=4, choose_better=False, optimize=R2, turbo=True, verbose=True)']\n", "['2020-07-31 08', '45', '42,017', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '45', '42,017', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '45', '42,017', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '45', '42,034', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '45', '42,034', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '45', '42,036', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '45', '42,036', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '45', '42,041', 'INFO', 'Importing untrained models']\n", "['2020-07-31 08', '45', '42,041', 'INFO', 'Import successful']\n", "['2020-07-31 08', '45', '42,042', 'INFO', 'Defining model names in estimator_list']\n", "['2020-07-31 08', '45', '45,250', 'INFO', 'n_jobs multiple passed']\n", "['2020-07-31 08', '45', '45,265', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '45', '45,280', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '48,335', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '48,715', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '48,739', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '45', '48,753', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '51,531', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '51,907', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '51,935', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '45', '51,944', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '54,960', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '55,340', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '55,370', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '45', '55,380', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '45', '58,319', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '45', '58,719', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '45', '58,743', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '45', '58,761', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '01,634', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '02,022', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '02,053', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '46', '02,064', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '04,996', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '05,375', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '05,404', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '46', '05,415', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '08,454', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '08,850', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '08,884', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '46', '08,894', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '11,712', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '12,102', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '12,118', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '46', '12,134', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '14,865', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '15,254', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '15,270', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '46', '15,286', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '18,564', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '18,970', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '19,005', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '19,007', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '19,022', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '46', '22,593', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '46', '22,593', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '46', '22,594', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '22,641', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '22,642', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '22,679', 'INFO', \"save_model(model=VotingRegressor(estimators=[('Linear Regression_0',\"]\n", "['LinearRegression(copy_X=True, fit_intercept=True,']\n", "['n_jobs=-1, normalize=False)),']\n", "[\"('Lasso_1',\"]\n", "['Lasso(alpha=1.0, copy_X=True, fit_intercept=True,']\n", "['max_iter=1000, normalize=False,']\n", "['positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic',\"]\n", "['tol=0.0001, warm_start=False)),']\n", "[\"('Ridge_2',\"]\n", "['Ridge(alpha=1.0, copy_X=True...']\n", "['min_child_samples=20,']\n", "['min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100,']\n", "['n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123,']\n", "['reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0,']\n", "['subsample_for_bin=200000,']\n", "['subsample_freq=0)),']\n", "[\"('CatBoost Regressor_21',\"]\n", "[')],']\n", "['n_jobs=-1, verbose=False, weights=None), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '46', '22,679', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '22,831', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '22,915', '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), VotingRegressor(estimators=[('Linear Regression_0',\"]\n", "['LinearRegression(copy_X=True, fit_intercept=True,']\n", "['n_jobs=-1, normalize=False)),']\n", "[\"('Lasso_1',\"]\n", "['Lasso(alpha=1.0, copy_X=True, fit_intercept=True,']\n", "['max_iter=1000, normalize=False,']\n", "['positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic',\"]\n", "['tol=0.0001, warm_start=False)),']\n", "[\"('Ridge_2',\"]\n", "['Ridge(alpha=1.0, copy_X=True...']\n", "['min_child_samples=20,']\n", "['min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100,']\n", "['n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123,']\n", "['reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0,']\n", "['subsample_for_bin=200000,']\n", "['subsample_freq=0)),']\n", "[\"('CatBoost Regressor_21',\"]\n", "[')],']\n", "['n_jobs=-1, verbose=False, weights=None), None]']\n", "['2020-07-31 08', '46', '22,915', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '22,915', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '23,715', 'INFO', 'create_model_container', '16']\n", "['2020-07-31 08', '46', '23,715', 'INFO', 'master_model_container', '16']\n", "['2020-07-31 08', '46', '23,715', 'INFO', 'display_container', '17']\n", "['2020-07-31 08', '46', '23,735', 'INFO', \"VotingRegressor(estimators=[('Linear Regression_0',\"]\n", "['LinearRegression(copy_X=True, fit_intercept=True,']\n", "['n_jobs=-1, normalize=False)),']\n", "[\"('Lasso_1',\"]\n", "['Lasso(alpha=1.0, copy_X=True, fit_intercept=True,']\n", "['max_iter=1000, normalize=False,']\n", "['positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic',\"]\n", "['tol=0.0001, warm_start=False)),']\n", "[\"('Ridge_2',\"]\n", "['Ridge(alpha=1.0, copy_X=True...']\n", "['min_child_samples=20,']\n", "['min_child_weight=0.001,']\n", "['min_split_gain=0.0, n_estimators=100,']\n", "['n_jobs=-1, num_leaves=31,']\n", "['objective=None, random_state=123,']\n", "['reg_alpha=0.0, reg_lambda=0.0,']\n", "['silent=True, subsample=1.0,']\n", "['subsample_for_bin=200000,']\n", "['subsample_freq=0)),']\n", "[\"('CatBoost Regressor_21',\"]\n", "[')],']\n", "['n_jobs=-1, verbose=False, weights=None)']\n", "['2020-07-31 08', '46', '23,735', 'INFO', 'blend_models() succesfully completed......................................']\n", "['2020-07-31 08', '46', '23,746', 'INFO', 'Initializing compare_models()']\n", "['2020-07-31 08', '46', '23,746', 'INFO', \"compare_models(blacklist=None, whitelist=['rf', 'et', 'ada', 'gbr', 'xgboost', 'lightgbm', 'catboost'], fold=5, round=4, sort=R2, n_select=5, turbo=True, verbose=True)\"]\n", "['2020-07-31 08', '46', '23,746', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '46', '23,746', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '46', '23,746', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '46', '23,764', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '46', '23,765', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '46', '23,770', 'INFO', 'Importing untrained models']\n", "['2020-07-31 08', '46', '23,771', 'INFO', 'Import successful']\n", "['2020-07-31 08', '46', '23,777', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '46', '23,777', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '46', '23,777', 'INFO', 'Initializing Random Forest']\n", "['2020-07-31 08', '46', '23,782', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '23,789', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '24,034', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '24,142', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '24,143', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '24,164', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '24,176', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '24,434', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '24,549', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '24,549', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '24,561', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '24,578', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '24,918', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '25,038', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '25,038', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '25,064', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '25,081', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '25,328', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '25,435', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '25,436', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '25,448', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '25,458', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '25,707', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '25,823', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '25,823', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '25,823', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '25,823', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '25,838', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '25,900', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '25,900', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '25,900', '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", "['2020-07-31 08', '46', '25,900', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '25,932', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '25,932', '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", "['2020-07-31 08', '46', '25,932', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '25,932', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '25,987', 'INFO', 'Initializing Extra Trees Regressor']\n", "['2020-07-31 08', '46', '25,992', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '25,998', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '26,142', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '26,268', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '26,268', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '26,284', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '26,303', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '26,440', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '26,546', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '26,546', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '26,553', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '26,563', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '26,705', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '26,821', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '26,821', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '26,836', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '26,852', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,011', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,117', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,118', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,139', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '27,139', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,295', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,421', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,421', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,421', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '27,421', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '27,436', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '27,502', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '27,502', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '27,503', '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", "['2020-07-31 08', '46', '27,503', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '27,523', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '27,539', '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", "['2020-07-31 08', '46', '27,539', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '27,539', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '27,586', 'INFO', 'Initializing AdaBoost Regressor']\n", "['2020-07-31 08', '46', '27,601', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '27,601', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,633', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,633', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,633', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,633', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '27,647', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,663', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,665', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,665', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,670', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '27,674', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,674', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,674', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,674', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,689', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '27,689', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,705', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,705', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,705', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,705', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '27,721', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,736', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,736', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,736', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,736', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '27,736', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '27,752', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '27,799', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '27,799', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '27,799', '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", "['2020-07-31 08', '46', '27,799', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '27,814', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '27,814', '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", "['2020-07-31 08', '46', '27,814', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '27,814', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '27,846', 'INFO', 'Initializing Gradient Boosting Regressor']\n", "['2020-07-31 08', '46', '27,846', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '27,861', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '27,924', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '27,924', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '27,924', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '27,939', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '27,939', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,002', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,018', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,018', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,018', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '28,018', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,096', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,096', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,096', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,096', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '28,096', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,174', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,174', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,174', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,174', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '28,189', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,252', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,252', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,252', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,267', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '28,267', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '28,267', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '28,330', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '28,330', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '28,330', '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", "['2020-07-31 08', '46', '28,330', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '28,346', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '28,346', '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", "['2020-07-31 08', '46', '28,346', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '28,346', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '28,408', 'INFO', 'Initializing Extreme Gradient Boosting']\n", "['2020-07-31 08', '46', '28,408', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '28,424', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,471', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,471', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,471', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,486', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '28,502', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,549', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,549', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,549', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,564', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '28,580', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,611', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,611', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,611', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,627', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '28,642', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,689', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,689', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,689', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,705', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '28,720', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '28,767', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '28,783', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '28,783', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '28,799', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '28,799', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '28,830', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '28,939', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '28,939', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '28,939', 'INFO', \"save_model(model=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '46', '28,939', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '28,955', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '28,955', '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,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0), None]']\n", "['2020-07-31 08', '46', '28,955', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '28,955', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '29,017', 'INFO', 'Initializing Light Gradient Boosting Machine']\n", "['2020-07-31 08', '46', '29,017', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '29,033', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '29,127', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '29,127', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '29,127', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '29,142', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '29,158', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '29,252', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '29,267', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '29,267', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '29,283', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '29,283', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '29,392', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '29,392', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '29,392', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '29,423', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '29,423', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '29,533', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '29,533', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '29,533', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '29,548', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '29,564', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '29,658', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '29,673', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '29,673', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '29,689', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '29,689', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '29,720', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '29,830', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '29,830', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '29,830', '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", "['2020-07-31 08', '46', '29,830', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '29,861', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '29,876', '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", "['2020-07-31 08', '46', '29,876', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '29,876', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '29,970', 'INFO', 'Initializing CatBoost Regressor']\n", "['2020-07-31 08', '46', '29,970', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '29,986', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '31,376', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '31,392', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '31,392', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '31,392', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '31,407', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '32,847', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '32,863', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '32,863', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '32,863', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '32,878', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '34,175', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '34,175', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '34,175', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '34,190', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '34,190', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '35,582', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '35,582', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '35,582', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '35,582', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '35,598', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,028', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,028', 'INFO', 'No inverse transformer found']\n", "['2020-07-31 08', '46', '37,028', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,043', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '37,043', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '37,059', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '46', '37,121', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '46', '37,121', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '46', '37,121', 'INFO', 'save_model(model=, model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '46', '37,121', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '46', '37,137', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '46', '37,137', '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", "['2020-07-31 08', '46', '37,137', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '37,137', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '46', '37,184', 'INFO', 'Finalizing top_n models']\n", "['2020-07-31 08', '46', '37,184', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'create_model(estimator=xgboost, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Extreme Gradient Boosting Regressor Imported succesfully']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '37,200', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,246', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,246', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,246', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,262', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '37,262', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,309', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,309', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,309', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,325', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '37,325', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,371', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,371', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,371', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,387', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '37,387', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,434', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,434', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,434', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,449', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '37,449', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,496', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,496', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,496', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,512', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '46', '37,512', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,559', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,559', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,559', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,574', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '46', '37,590', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,621', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,637', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,637', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,653', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '46', '37,653', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,699', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,699', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,699', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,715', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '46', '37,715', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,762', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,762', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,762', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,778', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '46', '37,778', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '37,840', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '37,840', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '37,840', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '37,856', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '37,856', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '37,871', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '46', '37,934', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '46', '37,934', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '46', '37,934', 'INFO', 'create_model_container', '17']\n", "['2020-07-31 08', '46', '37,934', 'INFO', 'master_model_container', '17']\n", "['2020-07-31 08', '46', '37,934', 'INFO', 'display_container', '18']\n", "['2020-07-31 08', '46', '37,934', 'INFO', \"XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "['silent=None, subsample=1, verbosity=0)']\n", "['2020-07-31 08', '46', '37,934', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '37,949', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '46', '37,949', 'INFO', 'create_model(estimator=gbr, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '46', '37,949', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '46', '37,949', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '46', '37,949', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Gradient Boosting Regressor Imported succesfully']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '37,981', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,121', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,121', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,121', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,121', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '38,121', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,231', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,231', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,231', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,231', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '38,231', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,324', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,324', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,324', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,340', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '38,340', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,418', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,418', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,418', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,434', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '38,434', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,512', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,512', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,512', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,512', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '46', '38,512', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,590', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,590', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,590', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,605', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '46', '38,605', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,683', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,683', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,683', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,683', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '46', '38,683', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,762', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,762', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,762', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,762', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '46', '38,762', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,840', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,840', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,840', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,840', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '46', '38,840', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '38,918', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '38,918', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '38,918', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '38,918', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '38,918', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '38,933', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'create_model_container', '18']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'master_model_container', '18']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'display_container', '19']\n", "['2020-07-31 08', '46', '39,012', '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", "['2020-07-31 08', '46', '39,012', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'create_model(estimator=catboost, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '46', '39,012', 'INFO', 'Preloading 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'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '41,620', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '41,620', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '41,620', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '41,636', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '41,636', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '42,979', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '42,995', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '42,995', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '42,995', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '42,995', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '44,323', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '44,323', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '44,323', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '44,323', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '44,323', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '45,653', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '45,653', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '45,653', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '45,669', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '46', '45,669', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '47,181', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '47,181', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '47,181', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '47,197', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '46', '47,197', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '48,509', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '48,509', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '48,509', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '48,524', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '46', '48,524', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '49,928', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '49,939', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '49,940', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '49,953', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '46', '49,955', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '51,527', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '51,530', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '51,530', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '51,540', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '46', '51,542', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '53,254', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '53,260', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '53,260', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '53,270', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '53,272', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '53,276', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '46', '54,768', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '46', '54,768', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '46', '54,768', 'INFO', 'create_model_container', '19']\n", "['2020-07-31 08', '46', '54,769', 'INFO', 'master_model_container', '19']\n", "['2020-07-31 08', '46', '54,769', 'INFO', 'display_container', '20']\n", "['2020-07-31 08', '46', '54,769', 'INFO', '']\n", "['2020-07-31 08', '46', '54,769', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '54,775', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '46', '54,775', 'INFO', 'create_model(estimator=rf, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '46', '54,775', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '46', '54,775', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '46', '54,775', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '46', '54,786', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '46', '54,787', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '46', '54,787', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '46', '54,788', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '46', '54,788', 'INFO', 'Random Forest Regressor Imported succesfully']\n", "['2020-07-31 08', '46', '54,789', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '46', '54,790', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '54,792', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '55,056', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '55,173', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '55,173', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '55,183', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '55,185', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '55,444', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '55,568', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '55,568', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '55,568', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '55,568', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '55,811', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '55,932', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '55,932', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '55,932', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '55,932', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '56,191', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '56,303', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '56,303', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '56,310', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '56,311', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '56,564', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '56,678', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '56,678', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '56,684', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '46', '56,685', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '56,948', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '57,053', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '57,055', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '57,066', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '46', '57,066', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '57,232', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '57,338', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '57,338', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '57,348', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '46', '57,349', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '57,609', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '57,724', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '57,724', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '57,726', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '46', '57,740', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '57,980', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '58,097', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '58,097', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '58,097', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '46', '58,097', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '58,350', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '58,456', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '58,456', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '58,464', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '58,465', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '58,469', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '46', '58,727', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '46', '58,727', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '46', '58,727', 'INFO', 'create_model_container', '20']\n", "['2020-07-31 08', '46', '58,727', 'INFO', 'master_model_container', '20']\n", "['2020-07-31 08', '46', '58,727', 'INFO', 'display_container', '21']\n", "['2020-07-31 08', '46', '58,727', 'INFO', \"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)']\n", "['2020-07-31 08', '46', '58,727', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '46', '58,743', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '46', '58,743', 'INFO', 'create_model(estimator=lightgbm, ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '46', '58,743', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '46', '58,743', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '46', '58,743', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '46', '58,766', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '46', '58,767', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '46', '58,768', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '46', '58,768', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '46', '58,768', 'INFO', 'Light Gradient Boosting Machine Imported succesfully']\n", "['2020-07-31 08', '46', '58,769', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '46', '58,770', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '46', '58,772', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '58,848', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '58,848', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '58,848', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '58,864', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '46', '58,864', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '58,926', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '58,942', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '58,942', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '58,942', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '46', '58,958', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,037', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,041', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,041', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,053', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '46', '59,055', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,148', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,152', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,153', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,164', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '46', '59,166', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,250', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,250', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,250', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,265', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '46', '59,265', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,359', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,375', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,375', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,375', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '46', '59,390', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,492', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,497', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,497', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,510', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '46', '59,513', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,629', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,634', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,634', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,649', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '46', '59,652', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,760', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,765', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,765', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,778', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '46', '59,780', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '46', '59,935', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '46', '59,941', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '46', '59,941', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '46', '59,956', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '46', '59,959', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '46', '59,969', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '47', '00,131', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '47', '00,131', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '47', '00,131', 'INFO', 'create_model_container', '21']\n", "['2020-07-31 08', '47', '00,132', 'INFO', 'master_model_container', '21']\n", "['2020-07-31 08', '47', '00,132', 'INFO', 'display_container', '22']\n", "['2020-07-31 08', '47', '00,133', '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", "['2020-07-31 08', '47', '00,133', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '00,133', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-31 08', '47', '00,231', 'INFO', 'create_model_container', '21']\n", "['2020-07-31 08', '47', '00,231', 'INFO', 'master_model_container', '21']\n", "['2020-07-31 08', '47', '00,231', 'INFO', 'display_container', '23']\n", "['2020-07-31 08', '47', '00,233', 'INFO', \"[XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "[\"silent=None, subsample=1, verbosity=0), 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), , 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), 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", "['2020-07-31 08', '47', '00,233', 'INFO', 'compare_models() succesfully completed......................................']\n", "['2020-07-31 08', '47', '00,241', 'INFO', 'Initializing stack_models()']\n", "['2020-07-31 08', '47', '00,243', 'INFO', \"stack_models(estimator_list=[XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "[\"silent=None, subsample=1, verbosity=0), 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), , 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), 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)], meta_model=None, fold=10, round=4, restack=True, plot=False, choose_better=False, optimize=R2, finalize=False, verbose=True)']\n", "['2020-07-31 08', '47', '00,243', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '00,243', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '00,243', 'INFO', 'Copying estimator list']\n", "['2020-07-31 08', '47', '00,296', 'INFO', 'Defining meta model']\n", "['2020-07-31 08', '47', '00,299', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '00,346', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '00,348', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '47', '00,349', 'INFO', 'Getting model names']\n", "['2020-07-31 08', '47', '00,356', 'INFO', 'Checking base model', 'XGBRegressor']\n", "['2020-07-31 08', '47', '00,367', 'INFO', 'Fitting base model']\n", "['2020-07-31 08', '47', '00,435', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 08', '47', '01,084', 'INFO', 'Checking base model', 'GradientBoostingRegressor']\n", "['2020-07-31 08', '47', '01,096', 'INFO', 'Fitting base model']\n", "['2020-07-31 08', '47', '01,257', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 08', '47', '02,082', 'INFO', 'Checking base model', 'CatBoostRegressor']\n", "['2020-07-31 08', '47', '02,097', 'INFO', 'Fitting base model']\n", "['2020-07-31 08', '47', '03,663', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 08', '47', '24,424', 'INFO', 'Checking base model', 'RandomForestRegressor']\n", "['2020-07-31 08', '47', '24,430', 'INFO', 'Fitting base model']\n", "['2020-07-31 08', '47', '24,814', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 08', '47', '28,106', 'INFO', 'Checking base model', 'LGBMRegressor']\n", "['2020-07-31 08', '47', '28,120', 'INFO', 'Fitting base model']\n", "['2020-07-31 08', '47', '28,227', 'INFO', 'Generating cross val predictions']\n", "['2020-07-31 08', '47', '29,899', 'INFO', 'Base layer complete']\n", "['2020-07-31 08', '47', '29,916', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '47', '29,919', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '47', '29,935', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '29,942', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '29,948', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '29,990', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '47', '29,999', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,006', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,008', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,031', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '47', '30,044', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,052', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,057', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,089', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '47', '30,101', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,108', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,112', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,141', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '47', '30,153', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,158', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,163', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,190', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '47', '30,200', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,206', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,208', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,237', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '47', '30,247', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,253', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,255', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,280', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '47', '30,289', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,296', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,300', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,321', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '47', '30,330', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,335', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,338', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,369', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '47', '30,380', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '30,387', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '30,390', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '30,419', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '47', '30,420', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '47', '30,429', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '47', '30,430', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '47', '30,431', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '47', '30,542', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '47', '30,542', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '47', '30,547', 'INFO', \"save_model(model=[XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "[\"silent=None, subsample=1, verbosity=0), 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, 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verbose=False)']\n", "['2020-07-31 08', '47', '30,547', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '47', '30,631', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '47', '30,651', '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,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "[\"silent=None, subsample=1, verbosity=0), 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, 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reg_alpha=0.0, reg_lambda=0.0, silent=True,']\n", "['subsample=1.0, subsample_for_bin=200000, subsample_freq=0), LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), True], None]']\n", "['2020-07-31 08', '47', '30,652', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '30,652', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '47', '31,205', 'INFO', 'create_model_container', '22']\n", "['2020-07-31 08', '47', '31,205', 'INFO', 'master_model_container', '22']\n", "['2020-07-31 08', '47', '31,205', 'INFO', 'display_container', '24']\n", "['2020-07-31 08', '47', '31,209', 'INFO', \"[XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\"]\n", "['colsample_bynode=1, colsample_bytree=1, gamma=0,']\n", "[\"importance_type='gain', learning_rate=0.1, max_delta_step=0,\"]\n", "['max_depth=3, min_child_weight=1, missing=None, n_estimators=100,']\n", "[\"n_jobs=-1, nthread=None, objective='reg\", \"linear', random_state=123,\"]\n", "['reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,']\n", "[\"silent=None, subsample=1, verbosity=0), 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), , 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), 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), LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), True]']\n", "['2020-07-31 08', '47', '31,209', 'INFO', 'stack_models() succesfully completed......................................']\n", "['2020-07-31 08', '47', '31,222', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '31,223', 'INFO', \"plot_model(estimator=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'), plot=residuals, save=False, verbose=True, system=True)\"]\n", "['2020-07-31 08', '47', '31,223', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '31,224', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '31,224', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '31,239', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '31,240', 'INFO', 'plot type', 'residuals']\n", "['2020-07-31 08', '47', '31,385', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '31,427', 'INFO', 'Scoring test/hold-out set']\n", "['2020-07-31 08', '47', '32,278', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '32,279', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '32,288', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '32,289', 'INFO', \"plot_model(estimator=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'), plot=error, save=False, verbose=True, system=True)\"]\n", "['2020-07-31 08', '47', '32,289', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '32,289', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '32,290', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '32,300', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '32,301', 'INFO', 'plot type', 'error']\n", "['2020-07-31 08', '47', '32,302', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '32,303', 'INFO', 'Scoring test/hold-out set']\n", "['2020-07-31 08', '47', '32,533', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '32,533', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '32,540', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '32,541', 'INFO', \"plot_model(estimator=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'), plot=feature, save=False, verbose=True, system=True)\"]\n", "['2020-07-31 08', '47', '32,541', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '32,541', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '32,541', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '32,551', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '32,552', 'INFO', 'plot type', 'feature']\n", "['2020-07-31 08', '47', '32,696', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '32,697', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '32,721', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '32,722', 'INFO', \"plot_model(estimator=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'), plot=parameter, save=False, verbose=True, system=True)\"]\n", "['2020-07-31 08', '47', '32,722', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '32,722', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '32,722', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '32,731', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '32,732', 'INFO', 'plot type', 'parameter']\n", "['2020-07-31 08', '47', '32,740', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '32,740', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '32,751', 'INFO', 'Initializing interpret_model()']\n", "['2020-07-31 08', '47', '32,752', 'INFO', \"interpret_model(estimator=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), plot=summary, feature=None, observation=None)']\n", "['2020-07-31 08', '47', '32,752', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '32,946', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '32,946', 'INFO', 'plot type', 'summary']\n", "['2020-07-31 08', '47', '32,946', 'INFO', 'Creating TreeExplainer']\n", "['2020-07-31 08', '47', '33,221', 'INFO', 'Compiling shap values']\n", "['2020-07-31 08', '47', '33,761', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '33,761', 'INFO', 'interpret_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '33,767', 'INFO', 'Initializing interpret_model()']\n", "['2020-07-31 08', '47', '33,768', 'INFO', \"interpret_model(estimator=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), plot=correlation, feature=None, observation=None)']\n", "['2020-07-31 08', '47', '33,768', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '33,769', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '33,769', 'INFO', 'plot type', 'correlation']\n", "['2020-07-31 08', '47', '33,769', 'WARNING', 'No feature passed. Default value of feature used for correlation plot', 'age']\n", "['2020-07-31 08', '47', '33,769', 'INFO', 'Creating TreeExplainer']\n", "['2020-07-31 08', '47', '34,080', 'INFO', 'Compiling shap values']\n", "['2020-07-31 08', '47', '34,387', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '34,387', 'INFO', 'interpret_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '34,395', 'INFO', 'Initializing interpret_model()']\n", "['2020-07-31 08', '47', '34,396', 'INFO', \"interpret_model(estimator=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), plot=reason, feature=None, observation=12)']\n", "['2020-07-31 08', '47', '34,396', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '34,397', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '34,397', 'INFO', 'plot type', 'reason']\n", "['2020-07-31 08', '47', '34,398', 'INFO', 'Creating TreeExplainer']\n", "['2020-07-31 08', '47', '34,661', 'INFO', 'Compiling shap values']\n", "['2020-07-31 08', '47', '34,753', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '34,754', 'INFO', 'interpret_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '34,811', 'INFO', 'Initializing automl()']\n", "['2020-07-31 08', '47', '34,812', 'INFO', 'automl(optimize=MAE, use_holdout=False)']\n", "['2020-07-31 08', '47', '34,812', 'INFO', 'Model Selection Basis', 'CV Results on Training set']\n", "['2020-07-31 08', '47', '34,820', 'INFO', 'SubProcess finalize_model() called ==================================']\n", "['2020-07-31 08', '47', '34,821', 'INFO', 'Initializing finalize_model()']\n", "['2020-07-31 08', '47', '34,822', 'INFO', 'finalize_model(estimator=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123))']\n", "['2020-07-31 08', '47', '34,822', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '34,822', 'INFO', 'Getting model name']\n", "['2020-07-31 08', '47', '34,823', 'INFO', 'Finalizing AdaBoost Regressor']\n", "['2020-07-31 08', '47', '34,883', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '47', '34,935', 'INFO', 'SubProcess create_model() called ==================================']\n", "['2020-07-31 08', '47', '34,936', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '47', '34,937', 'INFO', 'create_model(estimator=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), ensemble=False, method=None, fold=10, round=4, cross_validation=True, verbose=False, system=False)']\n", "['2020-07-31 08', '47', '34,937', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '34,937', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '34,937', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '34,953', 'INFO', 'Copying training dataset']\n", "['2020-07-31 08', '47', '34,954', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '34,954', 'INFO', 'Defining folds']\n", "['2020-07-31 08', '47', '34,954', 'INFO', 'Declaring metric variables']\n", "['2020-07-31 08', '47', '34,955', 'INFO', 'Declaring custom model']\n", "['2020-07-31 08', '47', '34,956', 'INFO', 'AdaBoost Regressor Imported succesfully']\n", "['2020-07-31 08', '47', '34,957', 'INFO', 'Checking ensemble method']\n", "['2020-07-31 08', '47', '34,958', 'INFO', 'Initializing Fold 1']\n", "['2020-07-31 08', '47', '34,961', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,005', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,008', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,008', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,015', 'INFO', 'Initializing Fold 2']\n", "['2020-07-31 08', '47', '35,016', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,074', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,078', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,079', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,088', 'INFO', 'Initializing Fold 3']\n", "['2020-07-31 08', '47', '35,089', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,141', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,145', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,146', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,153', 'INFO', 'Initializing Fold 4']\n", "['2020-07-31 08', '47', '35,154', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,201', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,204', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,204', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,211', 'INFO', 'Initializing Fold 5']\n", "['2020-07-31 08', '47', '35,213', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,259', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,262', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,262', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,269', 'INFO', 'Initializing Fold 6']\n", "['2020-07-31 08', '47', '35,270', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,312', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,316', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,316', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,322', 'INFO', 'Initializing Fold 7']\n", "['2020-07-31 08', '47', '35,324', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,365', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,369', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,369', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,375', 'INFO', 'Initializing Fold 8']\n", "['2020-07-31 08', '47', '35,376', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,417', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,420', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,420', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,426', 'INFO', 'Initializing Fold 9']\n", "['2020-07-31 08', '47', '35,427', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,468', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,471', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,471', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,477', 'INFO', 'Initializing Fold 10']\n", "['2020-07-31 08', '47', '35,478', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '35,518', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '35,521', 'INFO', 'No inverse transformation']\n", "['2020-07-31 08', '47', '35,521', 'INFO', 'Compiling Metrics']\n", "['2020-07-31 08', '47', '35,527', 'INFO', 'Calculating mean and std']\n", "['2020-07-31 08', '47', '35,528', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-31 08', '47', '35,532', 'INFO', 'Finalizing model']\n", "['2020-07-31 08', '47', '35,575', 'INFO', 'Uploading results into container']\n", "['2020-07-31 08', '47', '35,575', 'INFO', 'Uploading model into container']\n", "['2020-07-31 08', '47', '35,575', 'INFO', 'create_model_container', '23']\n", "['2020-07-31 08', '47', '35,575', 'INFO', 'master_model_container', '23']\n", "['2020-07-31 08', '47', '35,575', 'INFO', 'display_container', '25']\n", "['2020-07-31 08', '47', '35,576', 'INFO', 'AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123)']\n", "['2020-07-31 08', '47', '35,576', 'INFO', 'create_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '35,576', 'INFO', 'SubProcess create_model() end ==================================']\n", "['2020-07-31 08', '47', '35,635', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '47', '35,636', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '47', '35,637', 'INFO', 'save_model(model=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-31 08', '47', '35,637', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '47', '35,647', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '47', '35,653', '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", 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"['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), None]']\n", "['2020-07-31 08', '47', '35,653', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '35,653', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '47', '35,712', 'INFO', 'create_model_container', '23']\n", "['2020-07-31 08', '47', '35,712', 'INFO', 'master_model_container', '23']\n", "['2020-07-31 08', '47', '35,712', 'INFO', 'display_container', '25']\n", "['2020-07-31 08', '47', '35,713', 'INFO', 'AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123)']\n", "['2020-07-31 08', '47', '35,713', 'INFO', 'finalize_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '35,713', 'INFO', 'SubProcess finalize_model() end ==================================']\n", "['2020-07-31 08', '47', '35,714', 'INFO', 'AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123)']\n", "['2020-07-31 08', '47', '35,715', 'INFO', 'automl() succesfully completed......................................']\n", "['2020-07-31 08', '47', '35,914', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '47', '35,916', 'INFO', 'save_model(model=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), model_name=best-model, verbose=True)']\n", "['2020-07-31 08', '47', '35,916', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '47', '35,932', 'INFO', 'best-model.pkl saved in current working directory']\n", "['2020-07-31 08', '47', '35,942', '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=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), None]']\n", "['2020-07-31 08', '47', '35,942', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '36,014', 'INFO', 'Initializing deploy_model()']\n", "['2020-07-31 08', '47', '36,016', 'INFO', 'deploy_model(model=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "[\"random_state=123), model_name=best-aws, authentication={'bucket'\", \"'pycaret-test'}, platform=aws)\"]\n", "['2020-07-31 08', '47', '36,019', 'INFO', 'Platform', 'AWS S3']\n", "['2020-07-31 08', '47', '36,202', 'INFO', 'Saving model in active working directory']\n", "['2020-07-31 08', '47', '36,202', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '47', '36,203', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '47', '36,204', 'INFO', 'save_model(model=AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), model_name=best-aws, verbose=False)']\n", "['2020-07-31 08', '47', '36,204', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '47', '36,214', 'INFO', 'best-aws.pkl saved in current working directory']\n", "['2020-07-31 08', '47', '36,220', '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=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123), None]']\n", "['2020-07-31 08', '47', '36,220', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '36,220', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '47', '36,220', 'INFO', 'Initializing S3 client']\n", "['2020-07-31 08', '47', '36,853', 'INFO', 'PyCaret Clustering Module']\n", "['2020-07-31 08', '47', '36,853', 'INFO', 'version 2.0']\n", "['2020-07-31 08', '47', '36,853', 'INFO', 'Initializing setup()']\n", "['2020-07-31 08', '47', '36,853', 'INFO', 'USI', '872d']\n", "['2020-07-31 08', '47', '36,853', '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", "['2020-07-31 08', '47', '36,854', 'INFO', 'Checking environment']\n", "['2020-07-31 08', '47', '36,854', 'INFO', 'python_version', '3.7.4']\n", "['2020-07-31 08', '47', '36,854', 'INFO', 'python_build', \"('default', 'Aug 9 2019 18\", '34', \"13')\"]\n", "['2020-07-31 08', '47', '36,854', 'INFO', 'machine', 'AMD64']\n", "['2020-07-31 08', '47', '36,854', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-31 08', '47', '36,864', 'INFO', 'Memory', 'svmem(total=17032478720, available=10622828544, percent=37.6, used=6409650176, free=10622828544)']\n", "['2020-07-31 08', '47', '36,864', 'INFO', 'Physical Core', '4']\n", "['2020-07-31 08', '47', '36,864', 'INFO', 'Logical Core', '8']\n", "['2020-07-31 08', '47', '36,864', 'INFO', 'Checking libraries']\n", "['2020-07-31 08', '47', '36,864', 'INFO', 'pd==1.0.5']\n", "['2020-07-31 08', '47', '36,864', 'INFO', 'numpy==1.18.5']\n", "['2020-07-31 08', '47', '37,218', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-31 08', '47', '37,223', 'INFO', 'kmodes==0.10.1']\n", "['2020-07-31 08', '47', '37,758', 'INFO', 'AdaBoostRegressor(base_estimator=DecisionTreeRegressor(ccp_alpha=0.0,']\n", "[\"criterion='mse',\"]\n", "['max_depth=None,']\n", "['max_features=None,']\n", "['max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0,']\n", "['min_impurity_split=None,']\n", "['min_samples_leaf=1,']\n", "['min_samples_split=2,']\n", "['min_weight_fraction_leaf=0.0,']\n", "[\"presort='deprecated',\"]\n", "['random_state=123,']\n", "[\"splitter='best'),\"]\n", "[\"learning_rate=1.0, loss='linear', n_estimators=10,\"]\n", "['random_state=123)']\n", "['2020-07-31 08', '47', '37,758', 'INFO', 'deploy_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '37,765', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 08', '47', '37,765', 'INFO', 'get_config(variable=X_train)']\n", "['2020-07-31 08', '47', '37,765', 'INFO', 'Global variable', 'X_train returned']\n", "['2020-07-31 08', '47', '37,765', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 08', '47', '37,788', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 08', '47', '37,788', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-31 08', '47', '37,788', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-31 08', '47', '37,788', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 08', '47', '37,795', 'INFO', 'Initializing set_config()']\n", "['2020-07-31 08', '47', '37,795', 'INFO', 'set_config(variable=seed, value=999)']\n", "['2020-07-31 08', '47', '37,795', 'INFO', 'Global variable', 'seed updated']\n", "['2020-07-31 08', '47', '37,796', 'INFO', 'set_config() succesfully completed......................................']\n", "['2020-07-31 08', '47', '37,801', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 08', '47', '37,801', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-31 08', '47', '37,801', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-31 08', '47', '37,801', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 08', '47', '38,740', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-31 08', '47', '38,741', 'INFO', 'Checking Exceptions']\n", "['2020-07-31 08', '47', '38,741', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '38,741', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '38,760', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '38,761', 'INFO', 'Declaring global variables']\n", "['2020-07-31 08', '47', '38,761', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-31 08', '47', '38,767', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-31 08', '47', '38,767', 'INFO', 'Importing preprocessing module']\n", "['2020-07-31 08', '47', '40,016', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-31 08', '47', '40,955', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-31 08', '47', '40,955', 'INFO', 'Creating grid variables']\n", "['2020-07-31 08', '47', '40,957', 'INFO', 'Creating global containers']\n", "['2020-07-31 08', '47', '41,398', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-31 08', '47', '41,542', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '47', '41,543', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '47', '41,555', '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", "['2020-07-31 08', '47', '41,555', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '47', '41,565', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-31 08', '47', '41,580', '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", "['2020-07-31 08', '47', '41,580', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '41,580', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '47', '41,699', '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", "['2020-07-31 08', '47', '41,699', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-31 08', '47', '41,768', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '47', '41,768', 'INFO', 'create_model(model=kmeans, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-31 08', '47', '41,769', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '41,769', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '41,769', 'INFO', 'Setting num_cluster param']\n", "['2020-07-31 08', '47', '41,769', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '41,790', 'INFO', 'Importing untrained model']\n", "['2020-07-31 08', '47', '41,790', 'INFO', 'K-Means Clustering Imported succesfully']\n", "['2020-07-31 08', '47', '41,796', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '41,892', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '41,915', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-31 08', '47', '41,917', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '47', '42,047', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-31 08', '47', '42,047', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '42,048', '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", "['2020-07-31 08', '47', '42,048', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '42,048', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '43,583', 'INFO', 'plot type', 'cluster']\n", "['2020-07-31 08', '47', '43,583', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '47', '43,584', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '47', '43,584', '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", "['2020-07-31 08', '47', '43,585', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '43,585', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '43,585', 'INFO', 'Copying data']\n", "['2020-07-31 08', '47', '43,585', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-31 08', '47', '43,585', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '43,602', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '47', '43,603', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '47', '43,603', 'INFO', '(224, 21)']\n", "['2020-07-31 08', '47', '43,603', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '43,603', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '47', '43,612', 'INFO', 'Fitting PCA()']\n", "['2020-07-31 08', '47', '43,620', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '47', '43,623', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '47', '47,566', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-31 08', '47', '47,566', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '47,566', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '47,921', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '47,921', '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", "['2020-07-31 08', '47', '47,921', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '47,921', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '47,932', 'INFO', 'plot type', 'distribution']\n", "['2020-07-31 08', '47', '47,932', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '47', '47,932', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '47', '47,933', '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", "['2020-07-31 08', '47', '47,933', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '47,933', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '47,933', 'INFO', 'Copying data']\n", "['2020-07-31 08', '47', '47,933', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '47,946', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '47', '47,946', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '47', '47,946', 'INFO', '(224, 22)']\n", "['2020-07-31 08', '47', '47,947', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '47,947', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '47', '47,947', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '47', '47,953', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '47', '48,750', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-31 08', '47', '48,750', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '48,750', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '49,086', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '49,087', '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", "['2020-07-31 08', '47', '49,087', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '49,087', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '49,099', 'INFO', 'plot type', 'elbow']\n", "['2020-07-31 08', '47', '49,361', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-31 08', '47', '49,949', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '47', '50,717', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-31 08', '47', '50,717', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '50,717', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '50,729', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-31 08', '47', '50,730', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '47', '50,730', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '47', '50,731', '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", "['2020-07-31 08', '47', '50,731', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '47', '50,737', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '47', '50,744', '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", "['2020-07-31 08', '47', '50,744', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '50,744', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '47', '50,783', '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", "['2020-07-31 08', '47', '50,784', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-31 08', '47', '50,796', 'INFO', 'Initializing create_model()']\n", "['2020-07-31 08', '47', '50,796', 'INFO', 'create_model(model=kmodes, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-31 08', '47', '50,796', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '50,797', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '50,797', 'INFO', 'Setting num_cluster param']\n", "['2020-07-31 08', '47', '50,797', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '50,827', 'INFO', 'Importing untrained model']\n", "['2020-07-31 08', '47', '50,834', 'INFO', 'K-Modes Clustering Imported succesfully']\n", "['2020-07-31 08', '47', '50,842', 'INFO', 'Fitting Model']\n", "['2020-07-31 08', '47', '52,734', 'INFO', 'Evaluating Metrics']\n", "['2020-07-31 08', '47', '52,751', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-31 08', '47', '52,753', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-31 08', '47', '52,890', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-31 08', '47', '52,891', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '52,891', '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", "['2020-07-31 08', '47', '52,892', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '52,892', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '52,905', 'INFO', 'plot type', 'cluster']\n", "['2020-07-31 08', '47', '52,905', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '47', '52,906', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '47', '52,907', '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", "['2020-07-31 08', '47', '52,907', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '52,907', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '52,907', 'INFO', 'Copying data']\n", "['2020-07-31 08', '47', '52,908', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-31 08', '47', '52,908', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '52,926', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '47', '52,927', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-31 08', '47', '52,927', 'INFO', '(224, 21)']\n", "['2020-07-31 08', '47', '52,927', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '52,928', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '47', '52,935', 'INFO', 'Fitting PCA()']\n", "['2020-07-31 08', '47', '52,945', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '47', '52,949', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '47', '53,559', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-31 08', '47', '53,559', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '53,559', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '53,925', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '53,926', '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", "['2020-07-31 08', '47', '53,926', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '53,926', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '53,939', 'INFO', 'plot type', 'distribution']\n", "['2020-07-31 08', '47', '53,939', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '47', '53,939', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '47', '53,940', '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", "['2020-07-31 08', '47', '53,940', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '53,940', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '47', '53,940', 'INFO', 'Copying data']\n", "['2020-07-31 08', '47', '53,940', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '47', '53,958', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '47', '53,959', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-31 08', '47', '53,959', 'INFO', '(224, 22)']\n", "['2020-07-31 08', '47', '53,959', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '53,959', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '47', '53,960', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '47', '53,967', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '47', '54,761', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-31 08', '47', '54,761', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '47', '54,761', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '47', '55,112', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '47', '55,113', '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", "['2020-07-31 08', '47', '55,113', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '47', '55,113', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '47', '55,125', 'INFO', 'plot type', 'elbow']\n", "['2020-07-31 08', '47', '55,145', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-31 08', '48', '00,303', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '00,447', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-31 08', '48', '00,447', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '00,447', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '00,458', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-31 08', '48', '00,458', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-31 08', '48', '00,459', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '48', '00,459', '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", "['2020-07-31 08', '48', '00,459', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '48', '00,581', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-31 08', '48', '00,586', '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", "['2020-07-31 08', '48', '00,587', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '00,587', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-31 08', '48', '00,619', '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", "['2020-07-31 08', '48', '00,619', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-31 08', '48', '03,231', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '48', '03,231', '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", "['2020-07-31 08', '48', '03,232', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '03,232', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '48', '03,232', 'INFO', 'Copying data']\n", "['2020-07-31 08', '48', '03,232', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '48', '03,262', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '48', '03,262', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '48', '03,263', 'INFO', '(224, 22)']\n", "['2020-07-31 08', '48', '03,264', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '04,898', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '04,898', '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", "['2020-07-31 08', '48', '04,899', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '04,899', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '04,909', 'INFO', 'plot type', 'cluster']\n", "['2020-07-31 08', '48', '04,909', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '48', '04,909', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '48', '04,910', '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", "['2020-07-31 08', '48', '04,910', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '04,910', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '48', '04,910', 'INFO', 'Copying data']\n", "['2020-07-31 08', '48', '04,911', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-31 08', '48', '04,911', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '48', '04,927', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '48', '04,927', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '48', '04,927', 'INFO', '(224, 21)']\n", "['2020-07-31 08', '48', '04,927', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '04,928', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '48', '04,931', 'INFO', 'Fitting PCA()']\n", "['2020-07-31 08', '48', '04,936', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '48', '04,938', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '05,369', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '05,369', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '07,179', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '07,180', '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", "['2020-07-31 08', '48', '07,180', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '07,180', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '07,187', 'INFO', 'plot type', 'cluster']\n", "['2020-07-31 08', '48', '07,187', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '48', '07,188', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '48', '07,188', '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", "['2020-07-31 08', '48', '07,188', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '07,189', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '48', '07,189', 'INFO', 'Copying data']\n", "['2020-07-31 08', '48', '07,189', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-31 08', '48', '07,189', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '48', '07,199', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '48', '07,200', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '48', '07,200', 'INFO', '(224, 21)']\n", "['2020-07-31 08', '48', '07,200', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '07,200', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '48', '07,204', 'INFO', 'Fitting PCA()']\n", "['2020-07-31 08', '48', '07,207', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '48', '07,209', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '07,466', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '07,466', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '08,323', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '08,324', '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", "['2020-07-31 08', '48', '08,324', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '08,324', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '08,334', 'INFO', 'plot type', 'tsne']\n", "['2020-07-31 08', '48', '08,334', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '48', '08,334', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '48', '08,335', '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", "['2020-07-31 08', '48', '08,335', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '08,335', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '48', '08,335', 'INFO', 'Copying data']\n", "['2020-07-31 08', '48', '08,335', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-31 08', '48', '08,335', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '48', '08,343', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '48', '08,344', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '48', '08,344', 'INFO', '(224, 21)']\n", "['2020-07-31 08', '48', '08,344', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '08,344', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '48', '08,345', 'INFO', 'Fitting TSNE()']\n", "['2020-07-31 08', '48', '10,591', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '48', '10,600', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '11,151', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '11,151', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '11,158', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '11,159', '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", "['2020-07-31 08', '48', '11,159', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '11,159', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '11,168', 'INFO', 'plot type', 'elbow']\n", "['2020-07-31 08', '48', '11,169', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-31 08', '48', '11,704', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '11,875', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '11,875', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '11,882', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '11,883', '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", "['2020-07-31 08', '48', '11,883', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '11,883', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '11,893', 'INFO', 'plot type', 'silhouette']\n", "['2020-07-31 08', '48', '11,893', 'INFO', 'Fitting SilhouetteVisualizer()']\n", "['2020-07-31 08', '48', '11,976', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '12,124', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '12,124', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '12,130', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '12,131', '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", "['2020-07-31 08', '48', '12,131', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '12,132', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '12,142', 'INFO', 'plot type', 'distance']\n", "['2020-07-31 08', '48', '12,163', 'INFO', 'Fitting InterclusterDistance()']\n", "['2020-07-31 08', '48', '12,187', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '12,317', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '12,317', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '12,325', 'INFO', 'Initializing plot_model()']\n", "['2020-07-31 08', '48', '12,325', '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", "['2020-07-31 08', '48', '12,325', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '12,325', 'INFO', 'Importing libraries']\n", "['2020-07-31 08', '48', '12,334', 'INFO', 'plot type', 'distribution']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-31 08', '48', '12,335', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-31 08', '48', '12,335', 'INFO', 'Initializing assign_model()']\n", "['2020-07-31 08', '48', '12,336', '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", "['2020-07-31 08', '48', '12,336', 'INFO', 'Checking exceptions']\n", "['2020-07-31 08', '48', '12,336', 'INFO', 'Preloading libraries']\n", "['2020-07-31 08', '48', '12,336', 'INFO', 'Copying data']\n", "['2020-07-31 08', '48', '12,336', 'INFO', 'Preparing display monitor']\n", "['2020-07-31 08', '48', '12,347', 'INFO', 'Determining Trained Model']\n", "['2020-07-31 08', '48', '12,347', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-31 08', '48', '12,347', 'INFO', '(224, 22)']\n", "['2020-07-31 08', '48', '12,347', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '12,347', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-31 08', '48', '12,347', 'INFO', 'Sorting dataframe']\n", "['2020-07-31 08', '48', '12,351', 'INFO', 'Rendering Visual']\n", "['2020-07-31 08', '48', '12,781', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-31 08', '48', '12,781', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '16,227', 'INFO', 'Initializing save_model()']\n", "['2020-07-31 08', '48', '16,228', '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", "['2020-07-31 08', '48', '16,228', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '48', '16,239', 'INFO', 'kmeans.pkl saved in current working directory']\n", "['2020-07-31 08', '48', '16,246', '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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'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", "['2020-07-31 08', '48', '19,265', 'INFO', 'Appending prep pipeline']\n", "['2020-07-31 08', '48', '19,269', 'INFO', 'kmeans-aws.pkl saved in current working directory']\n", "['2020-07-31 08', '48', '19,273', '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", 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'Initializing S3 client']\n", "['2020-07-31 08', '48', '20,241', '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", "['2020-07-31 08', '48', '20,242', 'INFO', 'deploy_model() succesfully completed......................................']\n", "['2020-07-31 08', '48', '20,588', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 08', '48', '20,588', 'INFO', 'get_config(variable=X)']\n", "['2020-07-31 08', '48', '20,589', 'INFO', 'Global variable', 'X returned']\n", "['2020-07-31 08', '48', '20,589', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 08', '48', '21,288', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 08', '48', '21,288', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-31 08', '48', '21,288', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-31 08', '48', '21,289', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-31 08', '48', '21,687', 'INFO', 'Initializing set_config()']\n", "['2020-07-31 08', '48', '21,687', 'INFO', 'set_config(variable=seed, value=999)']\n", "['2020-07-31 08', '48', '21,687', 'INFO', 'Global variable', 'seed updated']\n", "['2020-07-31 08', '48', '21,687', 'INFO', 'set_config() succesfully completed......................................']\n", "['2020-07-31 08', '48', '22,013', 'INFO', 'Initializing get_config()']\n", "['2020-07-31 08', '48', '22,013', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-31 08', '48', '22,013', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-31 08', '48', '22,013', 'INFO', 'get_config() succesfully completed......................................']\n" ] } ], "source": [ "get_system_logs()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 11. MLFlow UI" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "^C\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": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.4" } }, "nbformat": 4, "nbformat_minor": 2 }