{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# PyCaret 2 Anomaly Example\n", "This notebook is created using PyCaret 2.0. Last updated : 28-07-2020" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pycaret-nightly-0.39\n" ] } ], "source": [ "# check version\n", "from pycaret.utils import version\n", "version()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 1. Loading Dataset" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Col1Col2Col3Col4Col5Col6Col7Col8Col9Col10
00.2639950.7649290.1384240.9352420.6058670.5187900.9122250.6082340.7237820.733591
10.5460920.6539750.0655750.2277720.8452690.8370660.2723790.3316790.4292970.367422
20.3367140.5388420.1928010.5535630.0745150.3329930.3657920.8613090.8990170.088600
30.0921080.9950170.0144650.1763710.2415300.5147240.5622080.1589630.0737150.208463
40.3252610.8059680.9570330.3316650.3079230.3553150.5018990.5584490.8851690.182754
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" ], "text/plain": [ " Col1 Col2 Col3 Col4 Col5 Col6 Col7 \\\n", "0 0.263995 0.764929 0.138424 0.935242 0.605867 0.518790 0.912225 \n", "1 0.546092 0.653975 0.065575 0.227772 0.845269 0.837066 0.272379 \n", "2 0.336714 0.538842 0.192801 0.553563 0.074515 0.332993 0.365792 \n", "3 0.092108 0.995017 0.014465 0.176371 0.241530 0.514724 0.562208 \n", "4 0.325261 0.805968 0.957033 0.331665 0.307923 0.355315 0.501899 \n", "\n", " Col8 Col9 Col10 \n", "0 0.608234 0.723782 0.733591 \n", "1 0.331679 0.429297 0.367422 \n", "2 0.861309 0.899017 0.088600 \n", "3 0.158963 0.073715 0.208463 \n", "4 0.558449 0.885169 0.182754 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pycaret.datasets import get_data\n", "data = get_data('anomaly')" ] }, { "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 (1000, 10)
2Missing Values False
3Numeric Features 10
4Categorical Features 0
5Ordinal Features False
6High Cardinality Features False
7Transformed Data (1000, 10)
8Numeric Imputer mean
9Categorical Imputer constant
10Normalize False
11Normalize Method None
12Transformation False
13Transformation Method None
14PCA False
15PCA Method None
16PCA components None
17Ignore Low Variance False
18Combine Rare Levels False
19Rare Level Threshold None
20Numeric Binning False
21Remove Multicollinearity False
22Multicollinearity Threshold None
23Group Features False
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from pycaret.anomaly import *\n", "ano1 = setup(data, session_id=123, log_experiment=True, experiment_name='anomaly1')" ] }, { "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
abodAngle-base Outlier Detectionpyod.models.abod.ABOD
iforestIsolation Forestpyod.models.iforest
clusterClustering-Based Local Outlierpyod.models.cblof
cofConnectivity-Based Outlier Factorpyod.models.cof
histogramHistogram-based Outlier Detectionpyod.models.hbos
knnk-Nearest Neighbors Detectorpyod.models.knn
lofLocal Outlier Factorpyod.models.lof
svmOne-class SVM detectorpyod.models.ocsvm
pcaPrincipal Component Analysispyod.models.pca
mcdMinimum Covariance Determinantpyod.models.mcd
sodSubspace Outlier Detectionpyod.models.sod
sosStochastic Outlier Selectionpyod.models.sos
\n", "
" ], "text/plain": [ " Name Reference\n", "ID \n", "abod Angle-base Outlier Detection pyod.models.abod.ABOD\n", "iforest Isolation Forest pyod.models.iforest\n", "cluster Clustering-Based Local Outlier pyod.models.cblof\n", "cof Connectivity-Based Outlier Factor pyod.models.cof\n", "histogram Histogram-based Outlier Detection pyod.models.hbos\n", "knn k-Nearest Neighbors Detector pyod.models.knn\n", "lof Local Outlier Factor pyod.models.lof\n", "svm One-class SVM detector pyod.models.ocsvm\n", "pca Principal Component Analysis pyod.models.pca\n", "mcd Minimum Covariance Determinant pyod.models.mcd\n", "sod Subspace Outlier Detection pyod.models.sod\n", "sos Stochastic Outlier Selection pyod.models.sos" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "models()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "iforest = create_model('iforest')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "knn = create_model('knn', fraction = 0.1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 4. Assign Labels" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Col1Col2Col3Col4Col5Col6Col7Col8Col9Col10LabelScore
00.2639950.7649290.1384240.9352420.6058670.5187900.9122250.6082340.7237820.7335910-0.035865
10.5460920.6539750.0655750.2277720.8452690.8370660.2723790.3316790.4292970.3674220-0.084927
20.3367140.5388420.1928010.5535630.0745150.3329930.3657920.8613090.8990170.08860010.025356
30.0921080.9950170.0144650.1763710.2415300.5147240.5622080.1589630.0737150.20846310.042415
40.3252610.8059680.9570330.3316650.3079230.3553150.5018990.5584490.8851690.1827540-0.023408
\n", "
" ], "text/plain": [ " Col1 Col2 Col3 Col4 Col5 Col6 Col7 \\\n", "0 0.263995 0.764929 0.138424 0.935242 0.605867 0.518790 0.912225 \n", "1 0.546092 0.653975 0.065575 0.227772 0.845269 0.837066 0.272379 \n", "2 0.336714 0.538842 0.192801 0.553563 0.074515 0.332993 0.365792 \n", "3 0.092108 0.995017 0.014465 0.176371 0.241530 0.514724 0.562208 \n", "4 0.325261 0.805968 0.957033 0.331665 0.307923 0.355315 0.501899 \n", "\n", " Col8 Col9 Col10 Label Score \n", "0 0.608234 0.723782 0.733591 0 -0.035865 \n", "1 0.331679 0.429297 0.367422 0 -0.084927 \n", "2 0.861309 0.899017 0.088600 1 0.025356 \n", "3 0.158963 0.073715 0.208463 1 0.042415 \n", "4 0.558449 0.885169 0.182754 0 -0.023408 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iforest_results = assign_model(iforest)\n", "iforest_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": [ [ 0.263995357 ], [ 0.546092303 ], [ 0.33671410399999996 ], [ 0.092107835 ], [ 0.325261175 ], [ 0.212464853 ], [ 0.258565714 ], [ 0.869236755 ], [ 0.197077957 ], [ 0.292984504 ], [ 0.82178316 ], [ 0.796622959 ], [ 0.045577010999999994 ], [ 0.613660351 ], [ 0.9507445659999999 ], [ 0.33634633700000005 ], [ 0.034440667 ], [ 0.741544275 ], [ 0.18443265 ], [ 0.664514943 ], [ 0.16282485800000002 ], [ 0.729838445 ], [ 0.62837389 ], [ 0.057883660999999996 ], [ 0.445534827 ], [ 0.80183695 ], [ 0.27709612 ], [ 0.228634015 ], [ 0.834860657 ], [ 0.6697665110000001 ], [ 0.532527349 ], [ 0.17045907100000002 ], [ 0.5102884679999999 ], [ 0.977561989 ], [ 0.249775993 ], [ 0.9755006820000001 ], [ 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_model(iforest, plot = 'umap')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 6. Predict Model" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Col1Col2Col3Col4Col5Col6Col7Col8Col9Col10LabelScore
00.2639950.7649290.1384240.9352420.6058670.5187900.9122250.6082340.7237820.7335910-0.035865
10.5460920.6539750.0655750.2277720.8452690.8370660.2723790.3316790.4292970.3674220-0.084927
20.3367140.5388420.1928010.5535630.0745150.3329930.3657920.8613090.8990170.08860010.025356
30.0921080.9950170.0144650.1763710.2415300.5147240.5622080.1589630.0737150.20846310.042415
40.3252610.8059680.9570330.3316650.3079230.3553150.5018990.5584490.8851690.1827540-0.023408
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" ], "text/plain": [ " Col1 Col2 Col3 Col4 Col5 Col6 Col7 \\\n", "0 0.263995 0.764929 0.138424 0.935242 0.605867 0.518790 0.912225 \n", "1 0.546092 0.653975 0.065575 0.227772 0.845269 0.837066 0.272379 \n", "2 0.336714 0.538842 0.192801 0.553563 0.074515 0.332993 0.365792 \n", "3 0.092108 0.995017 0.014465 0.176371 0.241530 0.514724 0.562208 \n", "4 0.325261 0.805968 0.957033 0.331665 0.307923 0.355315 0.501899 \n", "\n", " Col8 Col9 Col10 Label Score \n", "0 0.608234 0.723782 0.733591 0 -0.035865 \n", "1 0.331679 0.429297 0.367422 0 -0.084927 \n", "2 0.861309 0.899017 0.088600 1 0.025356 \n", "3 0.158963 0.073715 0.208463 1 0.042415 \n", "4 0.558449 0.885169 0.182754 0 -0.023408 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pred_new = predict_model(iforest, data=data)\n", "pred_new.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 7. Save / Load Model" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Transformation Pipeline and Model Succesfully Saved\n" ] } ], "source": [ "save_model(iforest, model_name='iforest')" ] }, { "cell_type": "code", "execution_count": 12, "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, features_todrop=[],\n", " ml_usecase='regression',\n", " numerical_features=[],\n", " target='dummy_target',\n", " time_features=[])),\n", " ('imputer',\n", " Simple_Imputer(categorical_strategy='not_available',\n", " numeric_strategy='mean',\n", " target_variable=None)),\n", " ('new_levels1',\n", " New_Catagorical_L...\n", " target='dummy_target')),\n", " ('feature_time',\n", " Make_Time_Features(list_of_features=None, time_feature=[])),\n", " ('group', Empty()), ('scaling', Empty()),\n", " ('P_transform', Empty()), ('binn', Empty()),\n", " ('fix_perfect', Empty()), ('rem_outliers', Empty()),\n", " ('dummy', Dummify(target='dummy_target')),\n", " ('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\n", " ('pca', Empty())],\n", " verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\n", " max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\n", " random_state=123, verbose=0)]\n" ] } ], "source": [ "loaded_iforest = load_model('iforest')\n", "print(loaded_iforest)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Pipeline(memory=None,\n",
       "         steps=[('dtypes',\n",
       "                 DataTypes_Auto_infer(categorical_features=[],\n",
       "                                      display_types=True, features_todrop=[],\n",
       "                                      ml_usecase='regression',\n",
       "                                      numerical_features=[],\n",
       "                                      target='dummy_target',\n",
       "                                      time_features=[])),\n",
       "                ('imputer',\n",
       "                 Simple_Imputer(categorical_strategy='not_available',\n",
       "                                numeric_strategy='mean',\n",
       "                                target_variable=None)),\n",
       "                ('new_levels1',\n",
       "                 New_Catagorical_L...\n",
       "                                                    target='dummy_target')),\n",
       "                ('feature_time',\n",
       "                 Make_Time_Features(list_of_features=None, time_feature=[])),\n",
       "                ('group', Empty()), ('scaling', Empty()),\n",
       "                ('P_transform', Empty()), ('binn', Empty()),\n",
       "                ('fix_perfect', Empty()), ('rem_outliers', Empty()),\n",
       "                ('dummy', Dummify(target='dummy_target')),\n",
       "                ('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\n",
       "                ('pca', Empty())],\n",
       "         verbose=False)
DataTypes_Auto_infer(ml_usecase='regression', 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, features_todrop=[],\n", " ml_usecase='regression',\n", " numerical_features=[],\n", " target='dummy_target',\n", " time_features=[])),\n", " ('imputer',\n", " Simple_Imputer(categorical_strategy='not_available',\n", " numeric_strategy='mean',\n", " target_variable=None)),\n", " ('new_levels1',\n", " New_Catagorical_L...\n", " target='dummy_target')),\n", " ('feature_time',\n", " Make_Time_Features(list_of_features=None, time_feature=[])),\n", " ('group', Empty()), ('scaling', Empty()),\n", " ('P_transform', Empty()), ('binn', Empty()),\n", " ('fix_perfect', Empty()), ('rem_outliers', Empty()),\n", " ('dummy', Dummify(target='dummy_target')),\n", " ('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\n", " ('pca', Empty())],\n", " verbose=False)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn import set_config\n", "set_config(display='diagram')\n", "loaded_iforest[0]" ] }, { "cell_type": "code", "execution_count": 14, "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": 15, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model Succesfully Deployed on AWS S3\n" ] } ], "source": [ "deploy_model(iforest, model_name = 'iforest-aws', authentication = {'bucket' : 'pycaret-test'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 9. Get Config / Set Config" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Col1Col2Col3Col4Col5Col6Col7Col8Col9Col10
00.2639950.7649290.1384240.9352420.6058670.5187900.9122250.6082340.7237820.733591
10.5460920.6539750.0655750.2277720.8452690.8370660.2723790.3316790.4292970.367422
20.3367140.5388420.1928010.5535630.0745150.3329930.3657920.8613090.8990170.088600
30.0921080.9950170.0144650.1763710.2415300.5147240.5622080.1589630.0737150.208463
40.3252610.8059680.9570330.3316650.3079230.3553150.5018990.5584490.8851690.182754
\n", "
" ], "text/plain": [ " Col1 Col2 Col3 Col4 Col5 Col6 Col7 \\\n", "0 0.263995 0.764929 0.138424 0.935242 0.605867 0.518790 0.912225 \n", "1 0.546092 0.653975 0.065575 0.227772 0.845269 0.837066 0.272379 \n", "2 0.336714 0.538842 0.192801 0.553563 0.074515 0.332993 0.365792 \n", "3 0.092108 0.995017 0.014465 0.176371 0.241530 0.514724 0.562208 \n", "4 0.325261 0.805968 0.957033 0.331665 0.307923 0.355315 0.501899 \n", "\n", " Col8 Col9 Col10 \n", "0 0.608234 0.723782 0.733591 \n", "1 0.331679 0.429297 0.367422 \n", "2 0.861309 0.899017 0.088600 \n", "3 0.158963 0.073715 0.208463 \n", "4 0.558449 0.885169 0.182754 " ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X = get_config('X')\n", "X.head()" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "123" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_config('seed')" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "from pycaret.anomaly import set_config\n", "set_config('seed', 999)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "999" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "get_config('seed')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 10. Get System Logs" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '47', '14,652', 'INFO', 'PyCaret Regression Module']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'USI', 'e640']\n", "['2020-07-29 09', '47', '14,652', 'INFO', 'setup(data=(1338, 7), target=charges, train_size=0.7, sampling=True, sample_estimator=None, categorical_features=None, categorical_imputation=constant, ordinal_features=None,']\n", "['high_cardinality_features=None, high_cardinality_method=frequency, numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=None, normalize=False,']\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None, remove_outliers=False, outliers_threshold=0.05,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, remove_perfect_collinearity=False, create_clusters=False, cluster_iter=20,']\n", "['polynomial_features=False, polynomial_degree=2, trigonometry_features=False, polynomial_threshold=0.1, group_features=None,']\n", "['group_names=None, feature_selection=False, feature_selection_threshold=0.8, feature_interaction=False, feature_ratio=False, interaction_threshold=0.01, transform_target=False,']\n", "['transform_target_method=box-cox, data_split_shuffle=True, folds_shuffle=False, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=insurance1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '14,653', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Memory', 'svmem(total=17032478720, available=5530103808, percent=67.5, used=11502374912, free=5530103808)']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '14,674', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '15,120', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '47', '15,204', 'INFO', 'xgboost==1.1.1']\n", "['2020-07-29 09', '47', '15,259', 'INFO', 'lightgbm==2.3.1']\n", "['2020-07-29 09', '47', '15,310', 'INFO', 'catboost==0.23.2']\n", "['2020-07-29 09', '47', '15,876', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '15,877', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '15,877', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '15,877', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '15,900', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '18,284', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '47', '18,285', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '18,296', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '47', '18,296', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '47', '19,149', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '47', '20,310', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '47', '20,310', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '20,310', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '47', '20,311', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '47', '20,410', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '47', '20,692', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '20,693', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '20,702', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '47', '20,702', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '20,710', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '20,721', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), None]']\n", "['2020-07-29 09', '47', '20,721', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '20,722', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'create_model_container', '0']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'master_model_container', '0']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'display_container', '0']\n", "['2020-07-29 09', '47', '20,809', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Initializing compare_models()']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'compare_models(blacklist=None, whitelist=None, fold=5, round=4, sort=R2, n_select=1, turbo=True, verbose=True)']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '32,141', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '32,174', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '47', '32,176', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '32,186', 'INFO', 'Importing untrained models']\n", "['2020-07-29 09', '47', '32,187', 'INFO', 'Import successful']\n", "['2020-07-29 09', '47', '32,191', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '47', '32,192', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '47', '32,192', 'INFO', 'Initializing Linear Regression']\n", "['2020-07-29 09', '47', '32,198', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '32,206', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,210', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,212', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,212', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,229', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '32,235', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,239', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,240', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,241', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,248', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '32,254', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,257', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,259', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,260', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,266', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '32,271', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,275', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,276', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,277', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,282', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '32,288', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,291', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,293', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,293', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,302', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '32,302', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '32,313', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '32,365', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '32,366', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '32,366', 'INFO', 'save_model(model=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '32,366', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '32,371', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '32,376', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), None]']\n", "['2020-07-29 09', '47', '32,376', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '32,376', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '32,731', 'INFO', 'Initializing Lasso Regression']\n", "['2020-07-29 09', '47', '32,736', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '32,742', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,747', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,749', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,749', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,756', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '32,762', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,766', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,768', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,768', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,775', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '32,781', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,786', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,788', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,788', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,795', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '32,801', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,804', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,805', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,805', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,812', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '32,818', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,820', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,822', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,822', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,829', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '32,829', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '32,841', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'save_model(model=Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '32,901', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '32,907', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '32,912', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '47', '32,912', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '32,912', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '32,961', 'INFO', 'Initializing Ridge Regression']\n", "['2020-07-29 09', '47', '32,967', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '32,972', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,974', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '32,976', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,976', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '32,983', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '32,988', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '32,991', 'INFO', 'Evaluating Metrics']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '47', '32,993', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '32,993', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,001', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,006', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,008', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,010', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,010', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,017', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,022', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,025', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,027', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,027', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,035', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,041', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,043', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,045', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,045', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,051', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,051', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,062', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'save_model(model=Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '33,129', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,134', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,139', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), None]\"]\n", "['2020-07-29 09', '47', '33,139', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,139', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,188', 'INFO', 'Initializing Elastic Net']\n", "['2020-07-29 09', '47', '33,194', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,200', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,203', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,205', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,205', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,212', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,219', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,222', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,225', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,225', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,232', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,237', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,241', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,243', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,243', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,251', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,255', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,260', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,262', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,262', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,270', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,277', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,280', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,283', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,283', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,291', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,291', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,302', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,367', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,368', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,368', 'INFO', 'save_model(model=ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,']\n", "['max_iter=1000, normalize=False, positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '33,368', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,373', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,379', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,']\n", "['max_iter=1000, normalize=False, positive=False, precompute=False,']\n", "[\"random_state=123, selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '47', '33,379', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,379', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,465', 'INFO', 'Initializing Least Angle Regression']\n", "['2020-07-29 09', '47', '33,470', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,476', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,482', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,483', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,484', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,490', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,496', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,502', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,504', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,504', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,510', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,517', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,522', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,523', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,523', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,531', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,536', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,542', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,543', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,544', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,552', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,564', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,572', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,574', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,574', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,580', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,581', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,593', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,653', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,654', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,654', 'INFO', 'save_model(model=Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '33,654', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,658', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,664', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), None]']\n", "['2020-07-29 09', '47', '33,664', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,664', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,714', 'INFO', 'Initializing Lasso Least Angle Regression']\n", "['2020-07-29 09', '47', '33,720', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,728', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,733', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,734', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,734', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,739', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,745', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,750', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,752', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,752', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,758', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '33,764', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,768', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,770', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,770', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,775', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '33,780', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,784', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,786', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,786', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,792', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '33,798', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,802', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,803', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,803', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,809', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '33,810', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '33,821', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'save_model(model=LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '33,878', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '33,884', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '33,889', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), None]\"]\n", "['2020-07-29 09', '47', '33,889', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '33,890', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '33,946', 'INFO', 'Initializing Orthogonal Matching Pursuit']\n", "['2020-07-29 09', '47', '33,952', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '33,961', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,964', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,966', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,966', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,974', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '33,983', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '33,985', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '33,987', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '33,988', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '33,997', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '34,002', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,006', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,008', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,008', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,017', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '34,023', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,026', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,029', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,029', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,037', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '34,044', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,048', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,051', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,051', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,058', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '34,058', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '34,073', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '34,193', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '34,193', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '34,194', 'INFO', 'save_model(model=OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,']\n", "[\"normalize=True, precompute='auto', tol=None), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '34,194', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '34,202', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '34,211', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,']\n", "[\"normalize=True, precompute='auto', tol=None), None]\"]\n", "['2020-07-29 09', '47', '34,211', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '34,211', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '34,263', 'INFO', 'Initializing Bayesian Ridge']\n", "['2020-07-29 09', '47', '34,269', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '34,277', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,284', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,286', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,287', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,295', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '34,304', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,311', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,314', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,314', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,323', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '34,331', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,339', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,341', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,342', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,350', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '34,357', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,364', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,367', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,367', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,375', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '34,383', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,391', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,393', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,393', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,402', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '34,402', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '34,420', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '34,507', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '34,507', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '34,508', 'INFO', 'save_model(model=BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,']\n", "['compute_score=False, copy_X=True, fit_intercept=True,']\n", "['lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,']\n", "['normalize=False, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '34,508', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '34,516', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '34,523', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,']\n", "['compute_score=False, copy_X=True, fit_intercept=True,']\n", "['lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,']\n", "['normalize=False, tol=0.001, verbose=False), None]']\n", "['2020-07-29 09', '47', '34,524', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '34,524', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '34,625', 'INFO', 'Initializing Passive Aggressive Regressor']\n", "['2020-07-29 09', '47', '34,633', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '34,640', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,651', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,654', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,654', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,664', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '34,672', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,683', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,685', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,686', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,696', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '34,705', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,715', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,717', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,717', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,726', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '34,735', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,746', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,749', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,749', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,759', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '34,767', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '34,777', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '34,779', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '34,779', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '34,790', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '34,790', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '34,808', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '34,904', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '34,904', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '34,905', 'INFO', 'save_model(model=PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,']\n", "['epsilon=0.1, fit_intercept=True,']\n", "[\"loss='epsilon_insensitive', max_iter=1000,\"]\n", "['n_iter_no_change=5, random_state=123, shuffle=True,']\n", "['tol=0.001, validation_fraction=0.1, verbose=0,']\n", "['warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '34,905', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '34,914', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '34,922', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,']\n", "['epsilon=0.1, fit_intercept=True,']\n", "[\"loss='epsilon_insensitive', max_iter=1000,\"]\n", "['n_iter_no_change=5, random_state=123, shuffle=True,']\n", "['tol=0.001, validation_fraction=0.1, verbose=0,']\n", "['warm_start=False), None]']\n", "['2020-07-29 09', '47', '34,922', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '34,922', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '35,002', 'INFO', 'Initializing Random Sample Consensus']\n", "['2020-07-29 09', '47', '35,011', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '35,023', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,179', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,182', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,183', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,194', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '35,203', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,358', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,361', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,361', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,371', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '35,381', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,533', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,535', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,535', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,547', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '35,556', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,711', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,714', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,715', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,727', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '35,737', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '35,875', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '35,878', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '35,878', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '35,889', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '35,889', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '35,911', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'save_model(model=RANSACRegressor(base_estimator=None, is_data_valid=None, is_model_valid=None,']\n", "[\"loss='absolute_loss', max_skips=inf, max_trials=100,\"]\n", "['min_samples=0.5, random_state=123, residual_threshold=None,']\n", "['stop_n_inliers=inf, stop_probability=0.99, stop_score=inf), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '36,020', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '36,029', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '36,039', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), RANSACRegressor(base_estimator=None, is_data_valid=None, is_model_valid=None,']\n", "[\"loss='absolute_loss', max_skips=inf, max_trials=100,\"]\n", "['min_samples=0.5, random_state=123, residual_threshold=None,']\n", "['stop_n_inliers=inf, stop_probability=0.99, stop_score=inf), None]']\n", "['2020-07-29 09', '47', '36,039', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '36,039', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '36,159', 'INFO', 'Initializing TheilSen Regressor']\n", "['2020-07-29 09', '47', '36,168', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '36,178', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '42,054', 'INFO', 'PyCaret Clustering Module']\n", "['2020-07-29 09', '47', '42,054', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '42,055', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '42,055', 'INFO', 'USI', 'e74c']\n", "['2020-07-29 09', '47', '42,056', 'INFO', 'setup(data=(224, 21), categorical_features=None, categorical_imputation=constant, ordinal_features=None, high_cardinality_features=None,']\n", "[\"numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=['Country Name'], normalize=False,\"]\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, group_features=None,']\n", "['group_names=None, supervised=False, supervised_target=None, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=health1, log_plots=True, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '47', '42,057', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '42,058', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '42,058', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '42,059', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '42,060', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '42,272', 'INFO', 'Memory', 'svmem(total=17032478720, available=5177511936, percent=69.6, used=11854966784, free=5177511936)']\n", "['2020-07-29 09', '47', '42,272', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '42,273', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '42,273', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '42,273', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '42,283', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '43,243', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '43,252', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '43,252', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '43,276', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '43,295', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '43,989', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '47', '43,991', 'INFO', 'kmodes==0.10.2']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'PyCaret Anomaly Detection Module']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '45,076', 'INFO', 'USI', '9b51']\n", "['2020-07-29 09', '47', '45,077', 'INFO', 'setup(data=(1000, 10), categorical_features=None, categorical_imputation=constant, ordinal_features=None, high_cardinality_features=None,']\n", "['numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=None, normalize=False,']\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, group_features=None,']\n", "['group_names=None, supervised=False, supervised_target=None, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=anomaly1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '47', '45,077', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '45,078', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '45,078', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '47', '45,078', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '47', '45,079', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '47', '45,083', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '45,089', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '45,090', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '45,113', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '45,133', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '45,136', 'INFO', 'Memory', 'svmem(total=17032478720, available=5155127296, percent=69.7, used=11877351424, free=5155127296)']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '45,137', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '45,138', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '45,767', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '45,768', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '45,769', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '45,850', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '45,903', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '45,903', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '45,904', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '47', '45,920', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '47', '45,921', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '47', '47,044', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '47,054', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '47,055', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '47,083', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '47,108', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '48,011', 'WARNING', 'pyod not found']\n", "['2020-07-29 09', '47', '48,500', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '47', '49,140', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '49,146', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '49,146', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '49,170', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '49,194', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '49,891', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '47', '49,892', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '47', '49,896', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '47', '49,930', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '49,931', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '49,931', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '50,035', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '50,094', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '50,094', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '50,094', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '47', '50,112', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '47', '50,112', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '47', '51,064', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '51,070', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '47', '51,071', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '51,071', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '51,100', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '51,101', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '51,167', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '51,238', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '47', '51,321', 'INFO', 'PyCaret NLP Module']\n", "['2020-07-29 09', '47', '51,321', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '47', '51,322', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '47', '51,322', 'INFO', 'USI', 'ab65']\n", "['2020-07-29 09', '47', '51,322', 'INFO', 'setup(data=(6818, 7), target=en, custom_stopwords=None, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=kiva1, log_plots=True, log_data=False, verbose=True)']\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '47', '51,323', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', 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09', '47', '51,412', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '47', '51,412', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '47', '51,413', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '47', '51,431', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '51,463', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', 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save_model() called ==================================']\n", "['2020-07-29 09', '47', '51,870', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '51,897', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), 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"['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)']\n", "['2020-07-29 09', '47', '52,132', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '47', '52,142', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '52,165', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,296', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,301', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,302', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,321', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '52,340', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,469', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,473', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,473', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,491', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '52,507', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '52,632', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '52,638', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '52,638', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '52,653', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '52,654', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '52,688', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '52,825', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '52,825', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '52,826', 'INFO', 'save_model(model=HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,']\n", "['tol=1e-05, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '52,826', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '52,841', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '52,854', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,']\n", "['tol=1e-05, warm_start=False), None]']\n", "['2020-07-29 09', '47', '52,854', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '52,854', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '53,009', 'INFO', 'Initializing Support Vector Machine']\n", "['2020-07-29 09', '47', '53,023', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '53,040', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,106', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,120', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,120', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,135', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '53,149', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,211', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,223', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,223', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,237', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '53,250', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,304', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,313', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,314', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,326', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '53,341', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,367', 'INFO', 'gensim==3.8.3']\n", "['2020-07-29 09', '47', '53,398', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,410', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,410', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,424', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '53,436', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,489', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,500', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,500', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,513', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '53,513', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '53,544', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '53,668', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '53,668', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '53,669', 'INFO', \"save_model(model=SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\"]\n", "[\"kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '53,669', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '53,680', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '53,690', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='scale',\"]\n", "[\"kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False), None]\"]\n", "['2020-07-29 09', '47', '53,690', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '53,690', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '53,805', 'INFO', 'Initializing K Neighbors Regressor']\n", "['2020-07-29 09', '47', '53,817', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '53,831', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,838', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '53,953', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '53,953', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '53,968', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '53,981', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '53,989', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,057', 'INFO', 'spacy==2.2.4']\n", "['2020-07-29 09', '47', '54,099', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,100', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,115', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '54,126', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,134', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,243', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,243', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,256', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '54,266', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,275', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,384', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,384', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,395', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '54,405', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,414', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,524', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,525', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,538', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '54,539', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '54,572', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '54,705', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '54,705', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '54,706', 'INFO', \"save_model(model=KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform'), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '54,707', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '54,723', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '54,740', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\"]\n", "['metric_params=None, n_jobs=-1, n_neighbors=5, p=2,']\n", "[\"weights='uniform'), None]\"]\n", "['2020-07-29 09', '47', '54,740', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '54,740', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '54,857', 'INFO', 'nltk==3.5']\n", "['2020-07-29 09', '47', '54,892', 'INFO', 'Initializing Decision Tree']\n", "['2020-07-29 09', '47', '54,902', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '54,921', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,924', 'INFO', 'textblob==0.15.3']\n", "['2020-07-29 09', '47', '54,932', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,935', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,935', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '54,949', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '54,965', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '54,978', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '54,983', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '54,984', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,005', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '55,021', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,032', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,036', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '47', '55,036', 'INFO', 'create_model(model=kmeans, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-29 09', '47', '55,036', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '55,037', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '55,037', 'INFO', 'Setting num_cluster param']\n", "['2020-07-29 09', '47', '55,037', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '55,038', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '55,038', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,057', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '55,077', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,078', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '47', '55,078', 'INFO', 'K-Means Clustering Imported succesfully']\n", "['2020-07-29 09', '47', '55,094', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,098', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,102', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '55,102', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,122', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '55,141', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '55,158', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,163', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '55,163', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '55,189', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '55,190', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '55,214', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '55,232', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '55,236', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-29 09', '47', '55,245', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '55,417', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '55,417', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '55,419', 'INFO', \"save_model(model=DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "[\"min_weight_fraction_leaf=0.0, presort='deprecated',\"]\n", "[\"random_state=123, splitter='best'), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '47', '55,419', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '55,437', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-29 09', '47', '55,437', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '47', '55,438', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '47', '55,439', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '55,439', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '55,439', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '55,465', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,\"]\n", "['max_features=None, max_leaf_nodes=None,']\n", "['min_impurity_decrease=0.0, min_impurity_split=None,']\n", "['min_samples_leaf=1, min_samples_split=2,']\n", "[\"min_weight_fraction_leaf=0.0, presort='deprecated',\"]\n", "[\"random_state=123, splitter='best'), None]\"]\n", "['2020-07-29 09', '47', '55,466', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '55,466', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '55,656', 'INFO', 'Initializing Random Forest']\n", "['2020-07-29 09', '47', '55,675', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '47', '55,694', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '56,059', 'INFO', 'pyLDAvis==2.1.2']\n", "['2020-07-29 09', '47', '56,271', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '56,275', 'INFO', 'wordcloud==1.7.0']\n", "['2020-07-29 09', '47', '56,383', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '56,384', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '56,401', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '47', '56,417', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '56,825', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '47', '56,826', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '47', '56,829', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '47', '56,945', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '57,059', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '57,060', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '57,086', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '47', '57,104', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '57,516', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '47', '57,516', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '47', '57,718', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '57,739', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '47', '57,833', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '57,834', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '57,859', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '47', '57,881', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '58,479', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '58,479', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '58,508', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '47', '58,508', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '58,521', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '58,552', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False), Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)]']\n", "['2020-07-29 09', '47', '58,552', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '58,552', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '58,578', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '58,692', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '58,693', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '58,708', 'INFO', 'Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "['verbose=False)']\n", "['2020-07-29 09', '47', '58,708', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '47', '58,714', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '47', '58,735', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '47', '59,302', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '47', '59,421', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '47', '59,422', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '47', '59,443', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '47', '59,444', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '47', '59,489', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '47', '59,672', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '47', '59,672', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '47', '59,674', 'INFO', \"save_model(model=RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '47', '59,674', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '47', '59,703', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '59,789', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '47', '59,796', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '59,811', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '47', '59,812', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '47', '59,812', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '47', '59,812', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '47', '59,813', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '47', '59,813', 'INFO', 'Copying data']\n", "['2020-07-29 09', '47', '59,813', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '47', '59,814', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '47', '59,849', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '47', '59,850', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '47', '59,850', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '47', '59,851', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '47', '59,851', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '47', '59,858', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '47', '59,859', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '47', '59,860', 'INFO', 'Input provided', 'dataframe']\n", "['2020-07-29 09', '47', '59,860', 'INFO', 'session_id set to', '123']\n", "['2020-07-29 09', '47', '59,860', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '47', '59,864', 'INFO', 'Importing stopwords from nltk']\n", "['2020-07-29 09', '47', '59,876', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '47', '59,891', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '47', '59,897', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '47', '59,977', 'INFO', 'Initializing Extra Trees Regressor']\n", "['2020-07-29 09', '47', '59,992', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '48', '00,014', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '00,280', 'INFO', 'No custom stopwords defined']\n", "['2020-07-29 09', '48', '00,282', 'INFO', 'Removing numeric characters from the text']\n", "['2020-07-29 09', '48', '00,441', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '00,553', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '00,554', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '00,576', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '48', '00,594', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '00,820', 'INFO', 'Removing special characters from the text']\n", "['2020-07-29 09', '48', '01,075', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '01,191', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '01,192', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '01,219', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '48', '01,241', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '01,696', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '01,807', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '01,807', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '01,823', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '48', '01,836', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '02,159', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '02,269', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '02,270', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '02,285', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '48', '02,305', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '02,353', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '48', '02,353', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '02,353', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '02,354', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '02,421', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '48', '02,422', 'INFO', 'Isolation Forest Imported succesfully']\n", "['2020-07-29 09', '48', '02,449', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '02,813', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '02,928', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '02,929', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '02,953', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '48', '02,954', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '48', '03,011', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '03,241', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '03,242', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '03,244', 'INFO', \"save_model(model=ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '03,244', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '03,413', 'INFO', 'Trained Model.pkl saved in current working 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Empty())],\"]\n", "[\"verbose=False), ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',\"]\n", "[\"max_depth=None, max_features='auto', max_leaf_nodes=None,\"]\n", "['max_samples=None, min_impurity_decrease=0.0,']\n", "['min_impurity_split=None, min_samples_leaf=1,']\n", "['min_samples_split=2, min_weight_fraction_leaf=0.0,']\n", "['n_estimators=100, n_jobs=-1, oob_score=False,']\n", "['random_state=123, verbose=0, warm_start=False), None]']\n", "['2020-07-29 09', '48', '03,441', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '03,442', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '03,744', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '03,753', 'INFO', 'Initializing AdaBoost Regressor']\n", "['2020-07-29 09', '48', '03,780', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '48', '03,810', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '03,946', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '03,960', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '03,961', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '03,961', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '03,961', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '03,962', 'INFO', \"save_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '03,962', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '03,999', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '48', '04,028', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,118', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,126', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,127', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,146', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '48', '04,165', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,169', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '04,188', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)]']\n", "['2020-07-29 09', '48', '04,188', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,189', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '04,228', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,238', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,238', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,265', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '48', '04,290', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,301', 'INFO', \"IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)']\n", "['2020-07-29 09', '48', '04,301', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,317', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '48', '04,318', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '04,318', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '04,318', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '04,350', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,360', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,360', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,389', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '48', '04,395', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '48', '04,396', 'INFO', 'k-Nearest Neighbors Detector Imported succesfully']\n", "['2020-07-29 09', '48', '04,412', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,415', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '04,484', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '04,484', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '04,494', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '48', '04,494', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '48', '04,518', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '48', '04,519', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '48', '04,583', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '04,697', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '04,698', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '04,699', 'INFO', \"save_model(model=KNN(algorithm='auto', contamination=0.1, leaf_size=30, method='largest',\"]\n", "[\"metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2,\"]\n", "['radius=1.0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '04,700', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '04,725', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '04,747', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KNN(algorithm='auto', contamination=0.1, leaf_size=30, method='largest',\"]\n", "[\"metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2,\"]\n", "['radius=1.0)]']\n", "['2020-07-29 09', '48', '04,747', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,748', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '04,794', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '04,794', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '04,795', 'INFO', \"save_model(model=AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',\"]\n", "['n_estimators=50, random_state=123), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '04,796', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '04,831', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '04,855', 'INFO', \"KNN(algorithm='auto', contamination=0.1, leaf_size=30, method='largest',\"]\n", "[\"metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2,\"]\n", "['radius=1.0)']\n", "['2020-07-29 09', '48', '04,855', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,856', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "[\"verbose=False), AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',\"]\n", "['n_estimators=50, random_state=123), None]']\n", "['2020-07-29 09', '48', '04,856', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '04,856', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '04,871', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '04,873', 'INFO', \"assign_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), transformation=False, score=True, verbose=True)']\n", "['2020-07-29 09', '48', '04,873', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '04,874', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '04,876', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '04,952', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '04,953', 'INFO', 'Trained Model', 'Assigned Isolation Forest']\n", "['2020-07-29 09', '48', '04,956', 'INFO', '(1000, 12)']\n", "['2020-07-29 09', '48', '04,957', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '05,009', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '05,010', 'INFO', \"plot_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), plot=tsne, feature=None, save=False, system=True)']\n", "['2020-07-29 09', '48', '05,011', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '05,011', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '05,796', 'INFO', 'Tokenizing Words']\n", "['2020-07-29 09', '48', '06,772', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-29 09', '48', '06,773', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '06,773', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '07,650', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '07,651', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=distribution, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '07,652', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '07,652', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '07,672', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '48', '07,672', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '07,672', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '07,674', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '48', '07,674', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '07,675', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '07,675', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '07,676', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '07,711', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '07,713', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '07,714', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '48', '07,714', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '07,715', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '07,715', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '07,732', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '08,329', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-29 09', '48', '08,329', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '08,329', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '08,812', 'INFO', 'plot type', 'tsne']\n", "['2020-07-29 09', '48', '08,813', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '08,813', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '08,814', 'INFO', \"assign_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), transformation=True, score=False, verbose=False)']\n", "['2020-07-29 09', '48', '08,814', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '08,815', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '08,815', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '08,849', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '08,850', 'INFO', 'Trained Model', 'Assigned Isolation Forest']\n", "['2020-07-29 09', '48', '08,851', 'INFO', '(1000, 11)']\n", "['2020-07-29 09', '48', '08,851', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '08,852', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '08,870', 'INFO', 'Getting dummies to cast categorical variables']\n", "['2020-07-29 09', '48', '08,885', 'INFO', 'Fitting TSNE()']\n", "['2020-07-29 09', '48', '09,534', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '09,535', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=elbow, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '09,535', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '09,536', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '09,562', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '48', '09,834', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '48', '11,999', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '13,890', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-29 09', '48', '13,890', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '13,891', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '13,931', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-29 09', '48', '13,932', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '13,932', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '13,934', 'INFO', \"save_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '13,934', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '13,953', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '13,975', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)]']\n", "['2020-07-29 09', '48', '13,975', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '13,976', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '14,077', 'INFO', \"KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0)']\n", "['2020-07-29 09', '48', '14,078', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '14,099', 'INFO', 'Initializing create_model()']\n", "['2020-07-29 09', '48', '14,100', 'INFO', 'create_model(model=kmodes, num_clusters=4, ground_truth=None, verbose=True, system=True)']\n", "['2020-07-29 09', '48', '14,100', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '14,101', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '14,102', 'INFO', 'Setting num_cluster param']\n", "['2020-07-29 09', '48', '14,102', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '14,162', 'INFO', 'Importing untrained model']\n", "['2020-07-29 09', '48', '14,178', 'INFO', 'K-Modes Clustering Imported succesfully']\n", "['2020-07-29 09', '48', '14,201', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '48', '20,873', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '48', '20,911', 'INFO', 'Creating Metrics dataframe']\n", "['2020-07-29 09', '48', '20,919', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '48', '21,190', 'INFO', 'SubProcess plot_model() called ==================================']\n", "['2020-07-29 09', '48', '21,190', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '21,192', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=cluster, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '21,192', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '21,192', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '21,221', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '48', '21,221', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '21,221', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '21,223', 'INFO', \"assign_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '21,223', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '21,223', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '21,224', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '21,224', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '21,225', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '21,271', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '21,273', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-29 09', '48', '21,274', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '21,274', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '21,275', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '21,292', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '48', '21,315', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '21,323', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '21,784', 'INFO', \"Saving 'Cluster.html' in current active directory\"]\n", "['2020-07-29 09', '48', '21,784', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '21,785', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '21,905', 'INFO', 'Removing stopwords']\n", "['2020-07-29 09', '48', '23,356', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '23,357', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=distribution, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '23,357', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '23,357', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '23,386', 'INFO', 'plot type', 'distribution']\n", "['2020-07-29 09', '48', '23,387', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '23,387', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '23,388', 'INFO', \"assign_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), transformation=False, verbose=False)']\n", "['2020-07-29 09', '48', '23,388', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '23,388', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '23,388', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '23,391', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '23,427', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '23,428', 'INFO', 'Trained Model', 'K-Modes Clustering']\n", "['2020-07-29 09', '48', '23,429', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '48', '23,429', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '23,429', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '23,430', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '23,439', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '24,069', 'INFO', \"Saving 'Distribution.html' in current active directory\"]\n", "['2020-07-29 09', '48', '24,069', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '24,070', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '25,580', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '25,582', 'INFO', \"plot_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), plot=elbow, feature=None, label=False, save=True, system=False)']\n", "['2020-07-29 09', '48', '25,582', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '25,582', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '25,604', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '48', '25,658', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '48', '32,253', 'INFO', 'Extracting Bigrams']\n", "['2020-07-29 09', '48', '41,062', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '41,646', 'INFO', \"Saving 'Elbow.png' in current active directory\"]\n", "['2020-07-29 09', '48', '41,646', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '41,646', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '41,692', 'INFO', 'SubProcess plot_model() end ==================================']\n", "['2020-07-29 09', '48', '41,692', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '48', '41,693', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '48', '41,694', 'INFO', \"save_model(model=KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '48', '41,694', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '48', '42,305', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '48', '42,330', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True,']\n", "[\"features_todrop=['Country Name'],\"]\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0)]']\n", "['2020-07-29 09', '48', '42,330', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,330', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '48', '42,451', 'INFO', \"KModes(cat_dissim=, init='Cao',\"]\n", "['max_iter=100, n_clusters=4, n_init=1, n_jobs=-1, random_state=123,']\n", "['verbose=0)']\n", "['2020-07-29 09', '48', '42,451', 'INFO', 'create_models() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,468', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '42,469', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=False, verbose=True)']\n", "['2020-07-29 09', '48', '42,470', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '42,470', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '42,470', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '42,472', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '42,563', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '42,573', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '42,576', 'INFO', '(224, 22)']\n", "['2020-07-29 09', '48', '42,577', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,694', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '42,695', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '48', '42,696', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '42,696', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '42,737', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '48', '42,737', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '42,738', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '42,739', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '42,740', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '42,740', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '42,740', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '42,741', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '42,741', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '42,782', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '42,788', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '42,789', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '42,789', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '42,790', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '42,805', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '48', '42,824', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '42,833', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '43,140', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '43,140', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,154', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '43,156', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=cluster, feature=Country Name, label=True, save=False, system=True)']\n", "['2020-07-29 09', '48', '43,156', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,157', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '43,186', 'INFO', 'plot type', 'cluster']\n", "['2020-07-29 09', '48', '43,188', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '43,188', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '43,192', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '43,192', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,193', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '43,193', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '43,194', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '43,194', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '43,230', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '43,232', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '43,233', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '43,233', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,233', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '43,246', 'INFO', 'Fitting PCA()']\n", "['2020-07-29 09', '48', '43,268', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '43,274', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '43,585', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '43,585', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,599', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '43,601', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=tsne, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '48', '43,602', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,602', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '43,658', 'INFO', 'plot type', 'tsne']\n", "['2020-07-29 09', '48', '43,659', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '48', '43,659', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '48', '43,661', 'INFO', \"assign_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), transformation=True, verbose=False)']\n", "['2020-07-29 09', '48', '43,662', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '43,662', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '48', '43,663', 'INFO', 'Copying data']\n", "['2020-07-29 09', '48', '43,664', 'INFO', 'Transformation param set to True. Assigned clusters are attached on transformed dataset.']\n", "['2020-07-29 09', '48', '43,664', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '48', '43,711', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '48', '43,713', 'INFO', 'Trained Model', 'K-Means Clustering']\n", "['2020-07-29 09', '48', '43,714', 'INFO', '(224, 21)']\n", "['2020-07-29 09', '48', '43,714', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '43,714', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '48', '43,718', 'INFO', 'Fitting TSNE()']\n", "['2020-07-29 09', '48', '49,461', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '59,261', 'INFO', 'Sorting dataframe']\n", "['2020-07-29 09', '48', '59,268', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '48', '59,625', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '48', '59,626', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '48', '59,656', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '48', '59,658', 'INFO', \"plot_model(model=KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\"]\n", "[\"n_clusters=4, n_init=10, n_jobs=-1, precompute_distances='deprecated',\"]\n", "['random_state=123, tol=0.0001, verbose=0), plot=elbow, feature=None, label=False, save=False, system=True)']\n", "['2020-07-29 09', '48', '59,658', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '48', '59,658', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '48', '59,688', 'INFO', 'plot type', 'elbow']\n", "['2020-07-29 09', '48', '59,688', 'INFO', 'Fitting KElbowVisualizer()']\n", "['2020-07-29 09', '49', '01,501', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '49', '01,501', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '01,532', 'INFO', 'Initializing plot_model()']\n", "['2020-07-29 09', '49', '01,533', 'INFO', \"plot_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), plot=umap, feature=None, save=False, system=True)']\n", "['2020-07-29 09', '49', '01,533', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '49', '01,533', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '49', '01,555', 'INFO', 'plot type', 'umap']\n", "['2020-07-29 09', '49', '01,556', 'INFO', 'SubProcess assign_model() called ==================================']\n", "['2020-07-29 09', '49', '01,556', 'INFO', 'Initializing assign_model()']\n", "['2020-07-29 09', '49', '01,556', 'INFO', \"assign_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), transformation=True, score=False, verbose=False)']\n", "['2020-07-29 09', '49', '01,557', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '49', '01,557', 'INFO', 'Copying data']\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "['2020-07-29 09', '49', '01,558', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '49', '01,588', 'INFO', 'Determining Trained Model']\n", "['2020-07-29 09', '49', '01,589', 'INFO', 'Trained Model', 'Assigned Isolation Forest']\n", "['2020-07-29 09', '49', '01,590', 'INFO', '(1000, 11)']\n", "['2020-07-29 09', '49', '01,590', 'INFO', 'assign_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '01,590', 'INFO', 'SubProcess assign_model() end ==================================']\n", "['2020-07-29 09', '49', '01,598', 'INFO', 'Getting dummies to cast categorical variables']\n", "['2020-07-29 09', '49', '02,407', 'INFO', 'Extracting Trigrams']\n", "['2020-07-29 09', '49', '05,305', 'INFO', 'Fitting UMAP()']\n", "['2020-07-29 09', '49', '14,048', 'INFO', 'PyCaret Regression Module']\n", "['2020-07-29 09', '49', '14,048', 'INFO', 'version pycaret-nightly-0.39']\n", "['2020-07-29 09', '49', '14,048', 'INFO', 'Initializing setup()']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'USI', 'd354']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'setup(data=(1338, 7), target=charges, train_size=0.7, sampling=True, sample_estimator=None, categorical_features=None, categorical_imputation=constant, ordinal_features=None,']\n", "['high_cardinality_features=None, high_cardinality_method=frequency, numeric_features=None, numeric_imputation=mean, date_features=None, ignore_features=None, normalize=False,']\n", "['normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear,']\n", "['pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None, remove_outliers=False, outliers_threshold=0.05,']\n", "['remove_multicollinearity=False, multicollinearity_threshold=0.9, remove_perfect_collinearity=False, create_clusters=False, cluster_iter=20,']\n", "['polynomial_features=False, polynomial_degree=2, trigonometry_features=False, polynomial_threshold=0.1, group_features=None,']\n", "['group_names=None, feature_selection=False, feature_selection_threshold=0.8, feature_interaction=False, feature_ratio=False, interaction_threshold=0.01, transform_target=False,']\n", "['transform_target_method=box-cox, data_split_shuffle=True, folds_shuffle=False, n_jobs=-1, html=True, session_id=123, log_experiment=True,']\n", "['experiment_name=insurance1, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False)']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'Checking environment']\n", "['2020-07-29 09', '49', '14,049', 'INFO', 'python_version', '3.6.10']\n", "['2020-07-29 09', '49', '14,050', 'INFO', 'python_build', \"('default', 'May 7 2020 19\", '46', \"08')\"]\n", "['2020-07-29 09', '49', '14,050', 'INFO', 'machine', 'AMD64']\n", "['2020-07-29 09', '49', '14,050', 'INFO', 'platform', 'Windows-10-10.0.18362-SP0']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Memory', 'svmem(total=17032478720, available=5629382656, percent=66.9, used=11403096064, free=5629382656)']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Physical Core', '4']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Logical Core', '8']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'Checking libraries']\n", "['2020-07-29 09', '49', '14,097', 'INFO', 'pd==1.0.4']\n", "['2020-07-29 09', '49', '14,098', 'INFO', 'numpy==1.18.5']\n", "['2020-07-29 09', '49', '14,935', 'INFO', 'sklearn==0.23.1']\n", "['2020-07-29 09', '49', '15,080', 'INFO', 'xgboost==1.1.1']\n", "['2020-07-29 09', '49', '15,220', 'INFO', 'lightgbm==2.3.1']\n", "['2020-07-29 09', '49', '15,339', 'INFO', 'catboost==0.23.2']\n", "['2020-07-29 09', '49', '16,374', 'INFO', 'mlflow==1.8.0']\n", "['2020-07-29 09', '49', '16,375', 'INFO', 'Checking Exceptions']\n", "['2020-07-29 09', '49', '16,375', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '49', '16,375', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '49', '16,408', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '49', '19,757', 'INFO', 'Copying data for preprocessing']\n", "['2020-07-29 09', '49', '19,758', 'INFO', 'Declaring global variables']\n", "['2020-07-29 09', '49', '19,777', 'INFO', 'Declaring preprocessing parameters']\n", "['2020-07-29 09', '49', '19,777', 'INFO', 'Importing preprocessing module']\n", "['2020-07-29 09', '49', '21,005', 'INFO', 'Creating preprocessing pipeline']\n", "['2020-07-29 09', '49', '22,813', 'INFO', 'Preprocessing pipeline created successfully']\n", "['2020-07-29 09', '49', '22,813', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '22,814', 'INFO', 'Creating grid variables']\n", "['2020-07-29 09', '49', '22,818', 'INFO', 'Creating global containers']\n", "['2020-07-29 09', '49', '22,997', 'INFO', 'Logging experiment in MLFlow']\n", "['2020-07-29 09', '49', '23,497', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '23,497', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '23,514', 'INFO', 'save_model(model=Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), model_name=Transformation Pipeline, verbose=False)']\n", "['2020-07-29 09', '49', '23,514', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '23,528', 'INFO', 'Transformation Pipeline.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '23,556', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", 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"[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), None]']\n", "['2020-07-29 09', '49', '23,557', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '23,557', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'create_model_container', '0']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'master_model_container', '0']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'display_container', '0']\n", "['2020-07-29 09', '49', '24,045', 'INFO', 'setup() succesfully completed......................................']\n", "['2020-07-29 09', '49', '25,845', 'INFO', 'Initializing compare_models()']\n", "['2020-07-29 09', '49', '25,845', 'INFO', 'compare_models(blacklist=None, whitelist=None, fold=5, round=4, sort=R2, n_select=1, turbo=True, verbose=True)']\n", "['2020-07-29 09', '49', '25,845', 'INFO', 'Checking exceptions']\n", "['2020-07-29 09', '49', '25,846', 'INFO', 'Preloading libraries']\n", "['2020-07-29 09', '49', '25,846', 'INFO', 'Preparing display monitor']\n", "['2020-07-29 09', '49', '25,953', 'INFO', 'Copying training dataset']\n", "['2020-07-29 09', '49', '25,957', 'INFO', 'Importing libraries']\n", "['2020-07-29 09', '49', '25,997', 'INFO', 'Importing untrained models']\n", "['2020-07-29 09', '49', '26,001', 'INFO', 'Import successful']\n", "['2020-07-29 09', '49', '26,023', 'INFO', 'Defining folds']\n", "['2020-07-29 09', '49', '26,023', 'INFO', 'Declaring metric variables']\n", "['2020-07-29 09', '49', '26,023', 'INFO', 'Initializing Linear Regression']\n", "['2020-07-29 09', '49', '26,050', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '26,072', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,081', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,097', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,098', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,243', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '26,280', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,291', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,298', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,298', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,372', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '26,407', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,424', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,430', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,430', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,489', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '26,529', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,542', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,547', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,547', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,627', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '26,685', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '26,695', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '26,701', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '26,702', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '26,784', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '26,787', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '26,947', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '27,492', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '27,492', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '27,496', 'INFO', 'save_model(model=LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '27,496', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '27,584', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '27,637', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", 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completed......................................']\n", "['2020-07-29 09', '49', '27,638', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '27,641', 'INFO', 'Rendering Visual']\n", "['2020-07-29 09', '49', '27,775', 'INFO', 'Initializing Lasso Regression']\n", "['2020-07-29 09', '49', '27,790', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '27,809', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '27,819', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '27,824', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '27,824', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '27,842', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '27,862', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '27,871', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '27,876', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '27,876', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '27,899', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '27,909', 'INFO', 'Visual Rendered Successfully']\n", "['2020-07-29 09', '49', '27,910', 'INFO', 'plot_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '27,921', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '27,931', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '27,939', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '27,939', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '27,968', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '27,993', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,006', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,013', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,014', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,044', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '28,072', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,083', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,091', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,091', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,118', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '28,119', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '28,162', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '28,366', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '28,367', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '28,367', 'INFO', 'save_model(model=Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '28,368', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '28,392', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '28,410', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,']\n", "['normalize=False, positive=False, precompute=False, random_state=123,']\n", "[\"selection='cyclic', tol=0.0001, warm_start=False), None]\"]\n", "['2020-07-29 09', '49', '28,410', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '28,410', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '28,583', 'INFO', 'Initializing Ridge Regression']\n", "['2020-07-29 09', '49', '28,598', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '28,599', 'INFO', \"save_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), model_name=iforest, verbose=True)']\n", "['2020-07-29 09', '49', '28,600', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '28,607', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '28,630', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,638', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,645', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,645', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,663', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '28,682', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,692', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,697', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,697', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,720', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '28,744', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,752', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,758', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,759', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,766', 'INFO', 'iforest.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '28,782', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '28,787', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "['numerical_features=[],']\n", "[\"target='dummy_target',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_L...']\n", "[\"target='dummy_target')),\"]\n", "[\"('feature_time',\"]\n", "['Make_Time_Features(list_of_features=None, time_feature=[])),']\n", "[\"('group', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('binn', Empty()),\"]\n", "[\"('fix_perfect', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('dummy', Dummify(target='dummy_target')),\"]\n", "[\"('clean_names', Clean_Colum_Names()), ('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)]']\n", "['2020-07-29 09', '49', '28,788', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '28,808', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,818', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,826', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,826', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,853', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '28,878', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '28,886', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '28,893', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '28,893', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '28,917', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '28,918', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '28,963', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '29,109', 'INFO', 'Initializing deploy_model()']\n", "['2020-07-29 09', '49', '29,111', 'INFO', \"deploy_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "[\"random_state=123, verbose=0), model_name=iforest-aws, authentication={'bucket'\", \"'pycaret-test'}, platform=aws)\"]\n", "['2020-07-29 09', '49', '29,111', 'INFO', 'Platform', 'AWS S3']\n", "['2020-07-29 09', '49', '29,245', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '29,245', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '29,246', 'INFO', 'save_model(model=Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,']\n", "[\"normalize=False, random_state=123, solver='auto', tol=0.001), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '29,247', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '29,272', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '29,288', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], 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completed......................................']\n", "['2020-07-29 09', '49', '29,289', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '29,429', 'INFO', 'Saving model in current working directory']\n", "['2020-07-29 09', '49', '29,430', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '29,430', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '29,430', 'INFO', \"save_model(model=IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0), model_name=iforest-aws, verbose=False)']\n", "['2020-07-29 09', '49', '29,431', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '29,481', 'INFO', 'Initializing Elastic Net']\n", "['2020-07-29 09', '49', '29,503', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '29,528', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,540', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,545', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,546', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,573', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '29,595', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,606', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,614', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,615', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,654', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '29,677', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,689', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,697', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,697', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,698', 'INFO', 'iforest-aws.pkl 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('fix_multi', Empty()),\"]\n", "[\"('pca', Empty())],\"]\n", "[\"verbose=False), IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)]']\n", "['2020-07-29 09', '49', '29,722', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '29,723', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '29,723', 'INFO', 'Initializing S3 client']\n", "['2020-07-29 09', '49', '29,729', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '29,755', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '29,767', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '29,776', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '29,776', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '29,804', 'INFO', 'Initializing Fold 5']\n", 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Metrics']\n", "['2020-07-29 09', '49', '30,521', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,521', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,546', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '30,571', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,595', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,600', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,600', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,630', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '30,652', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,670', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,677', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,678', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,704', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '30,731', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,752', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,759', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,759', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,783', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '30,813', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '30,830', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '30,838', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '30,839', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '30,858', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '30,859', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '30,898', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '31,084', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '31,084', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '31,085', 'INFO', 'save_model(model=Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), model_name=Trained Model, verbose=False)']\n", "['2020-07-29 09', '49', '31,085', 'INFO', 'Appending prep pipeline']\n", "['2020-07-29 09', '49', '31,100', 'INFO', 'Trained Model.pkl saved in current working directory']\n", "['2020-07-29 09', '49', '31,113', 'INFO', '[Pipeline(memory=None,']\n", "[\"steps=[('dtypes',\"]\n", "['DataTypes_Auto_infer(categorical_features=[],']\n", "['display_types=True, features_todrop=[],']\n", "[\"ml_usecase='regression',\"]\n", "[\"numerical_features=[], target='charges',\"]\n", "['time_features=[])),']\n", "[\"('imputer',\"]\n", "[\"Simple_Imputer(categorical_strategy='not_available',\"]\n", "[\"numeric_strategy='mean',\"]\n", "['target_variable=None)),']\n", "[\"('new_levels1',\"]\n", "['New_Catagorical_Levels...']\n", "[\"('group', Empty()), ('nonliner', Empty()), ('scaling', Empty()),\"]\n", "[\"('P_transform', Empty()), ('pt_target', Empty()),\"]\n", "[\"('binn', Empty()), ('rem_outliers', Empty()),\"]\n", "[\"('cluster_all', Empty()), ('dummy', Dummify(target='charges')),\"]\n", "[\"('fix_perfect', Empty()), ('clean_names', Clean_Colum_Names()),\"]\n", "[\"('feature_select', Empty()), ('fix_multi', Empty()),\"]\n", "[\"('dfs', Empty()), ('pca', Empty())],\"]\n", "['verbose=False), Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,']\n", "[\"jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',\"]\n", "['random_state=None, verbose=False), None]']\n", "['2020-07-29 09', '49', '31,114', 'INFO', 'save_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,114', 'INFO', 'SubProcess save_model() end ==================================']\n", "['2020-07-29 09', '49', '31,259', 'INFO', 'Initializing Lasso Least Angle Regression']\n", "['2020-07-29 09', '49', '31,273', 'INFO', 'Initializing Fold 1']\n", "['2020-07-29 09', '49', '31,290', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,303', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,307', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,307', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,322', 'INFO', 'Initializing Fold 2']\n", "['2020-07-29 09', '49', '31,337', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,349', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,353', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,354', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,371', 'INFO', 'Initializing Fold 3']\n", "['2020-07-29 09', '49', '31,385', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,397', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,401', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,401', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,418', 'INFO', 'Initializing Fold 4']\n", "['2020-07-29 09', '49', '31,435', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,447', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,454', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,454', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,476', 'INFO', 'Initializing Fold 5']\n", "['2020-07-29 09', '49', '31,493', 'INFO', 'Fitting Model']\n", "['2020-07-29 09', '49', '31,505', 'INFO', 'Evaluating Metrics']\n", "['2020-07-29 09', '49', '31,510', 'INFO', 'No inverse transformer found']\n", "['2020-07-29 09', '49', '31,510', 'INFO', 'Compiling Metrics']\n", "['2020-07-29 09', '49', '31,533', 'INFO', 'Calculating mean and std']\n", "['2020-07-29 09', '49', '31,535', 'INFO', 'Creating metrics dataframe']\n", "['2020-07-29 09', '49', '31,571', 'INFO', 'Creating MLFlow logs']\n", "['2020-07-29 09', '49', '31,659', 'INFO', \"IForest(behaviour='new', bootstrap=False, contamination=0.05,\"]\n", "[\"max_features=1.0, max_samples='auto', n_estimators=100, n_jobs=1,\"]\n", "['random_state=123, verbose=0)']\n", "['2020-07-29 09', '49', '31,660', 'INFO', 'deploy_model() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,676', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '49', '31,677', 'INFO', 'get_config(variable=X)']\n", "['2020-07-29 09', '49', '31,677', 'INFO', 'Global variable', 'X returned']\n", "['2020-07-29 09', '49', '31,678', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,728', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '49', '31,729', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-29 09', '49', '31,729', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-29 09', '49', '31,729', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,747', 'INFO', 'Initializing set_config()']\n", "['2020-07-29 09', '49', '31,748', 'INFO', 'set_config(variable=seed, value=999)']\n", "['2020-07-29 09', '49', '31,748', 'INFO', 'Global variable', 'seed updated']\n", "['2020-07-29 09', '49', '31,748', 'INFO', 'set_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,762', 'INFO', 'Initializing get_config()']\n", "['2020-07-29 09', '49', '31,763', 'INFO', 'get_config(variable=seed)']\n", "['2020-07-29 09', '49', '31,764', 'INFO', 'Global variable', 'seed returned']\n", "['2020-07-29 09', '49', '31,764', 'INFO', 'get_config() succesfully completed......................................']\n", "['2020-07-29 09', '49', '31,768', 'INFO', 'SubProcess save_model() called ==================================']\n", "['2020-07-29 09', '49', '31,768', 'INFO', 'Initializing save_model()']\n", "['2020-07-29 09', '49', '31,770', 'INFO', 'save_model(model=LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,']\n", "['fit_path=True, jitter=None, max_iter=500, normalize=True,']\n", "[\"positive=False, precompute='auto', random_state=None, verbose=False), model_name=Trained Model, verbose=False)\"]\n", "['2020-07-29 09', '49', '31,770', 'INFO', 'Appending prep pipeline']\n" ] } ], "source": [ "get_system_logs()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 11. MLFlow UI" ] }, { "cell_type": "code", "execution_count": 21, "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": "pycaret-nightly-env", "language": "python", "name": "pycaret-nightly-env" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.10" } }, "nbformat": 4, "nbformat_minor": 2 }