10223626 1 Jan van Rijn 14967 Supervised Classification 9666 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(4) 8149058 copy true 9559 fill_value -1 9559 missing_values NaN 9559 strategy "constant" 9559 verbose 0 9559 n_jobs null 9606 remainder "passthrough" 9606 sparse_threshold 0.3 9606 transformer_weights null 9606 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1]}}] 9606 memory null 9607 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 9607 axis 0 9608 copy true 9608 missing_values "NaN" 9608 strategy "most_frequent" 9608 verbose 0 9608 copy true 9609 with_mean true 9609 with_std true 9609 memory null 9610 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 9610 categorical_features null 9611 categories null 9611 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 9611 handle_unknown "ignore" 9611 n_values null 9611 sparse true 9611 threshold 0.0 9612 memory null 9666 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 9666 criterion "friedman_mse" 9667 init null 9667 learning_rate 0.0006133435988241978 9667 loss "deviance" 9667 max_depth 26 9667 max_features 0.2435297987807048 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.252688373075712 9667 min_impurity_split null 9667 min_samples_leaf 18 9667 min_samples_split 2 9667 min_weight_fraction_leaf 0.28642932270223836 9667 n_estimators 145 9667 n_iter_no_change 587 9667 presort "auto" 9667 random_state 7508 9667 subsample 0.9995337351086007 9667 tol 0.009474525992204347 9667 validation_fraction 0.24090959291301617 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 23380 cjs https://www.openml.org/data/download/1910442/phpDAC5gS -1 21368168 description https://api.openml.org/data/download/21368168/description.xml -1 21368169 predictions https://api.openml.org/data/download/21368169/predictions.arff area_under_roc_curve 0.6135251034579936 [0.602213,0.584103,0.613045,0.502605,0.687249,0.770581] average_cost 0 kappa 0 kb_relative_information_score 102.67466358453105 mean_absolute_error 0.27604794267185995 mean_prior_absolute_error 0.27287997162595995 number_of_instances 2796 [576,341,680,511,414,274] predictive_accuracy 0.24320457796852646 prior_entropy 2.5206634795042744 recall 0.24320457796852646 [0,0,1,0,0,0] relative_absolute_error 1.0116093937822683 root_mean_prior_squared_error 0.3693707377543301 root_mean_squared_error 0.37055721732267605 root_relative_squared_error 1.0032121644923997 total_cost 0 area_under_roc_curve 0.6180021607529842 [0.637387,0.554818,0.62715,0.49011,0.651495,0.816256] area_under_roc_curve 0.5975159530267093 [0.587838,0.667683,0.566801,0.397808,0.70798,0.808957] area_under_roc_curve 0.6490552530481953 [0.70014,0.540112,0.628989,0.552145,0.721196,0.795139] area_under_roc_curve 0.6268135011175171 [0.588032,0.59248,0.655938,0.541014,0.673844,0.765519] area_under_roc_curve 0.5840608434336741 [0.565121,0.686932,0.531944,0.528973,0.581131,0.737008] area_under_roc_curve 0.6153448304355815 [0.584304,0.681691,0.606652,0.444173,0.730942,0.7657] area_under_roc_curve 0.6204627970793335 [0.554173,0.5509,0.673752,0.494238,0.794254,0.681878] area_under_roc_curve 0.6296987115921817 [0.679192,0.554382,0.613535,0.540119,0.62834,0.832084] area_under_roc_curve 0.6156621257149187 [0.586257,0.557983,0.655701,0.471448,0.721469,0.757349] area_under_roc_curve 0.6301665791718388 [0.606488,0.564586,0.624477,0.585569,0.66747,0.803277] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kappa 0 kb_relative_information_score 10.439742381245656 kb_relative_information_score 10.510319432528416 kb_relative_information_score 10.481657676772441 kb_relative_information_score 10.338028525251703 kb_relative_information_score 9.758599986333161 kb_relative_information_score 10.293627655383595 kb_relative_information_score 10.275148950478291 kb_relative_information_score 10.100222327860651 kb_relative_information_score 10.203801320775757 kb_relative_information_score 10.273515327901057 mean_absolute_error 0.2760155460898229 mean_absolute_error 0.2761099581149735 mean_absolute_error 0.2759603579138486 mean_absolute_error 0.27602055330443415 mean_absolute_error 0.27615838436234713 mean_absolute_error 0.2760668393553163 mean_absolute_error 0.27601545862649857 mean_absolute_error 0.27602956222588854 mean_absolute_error 0.27606674083405225 mean_absolute_error 0.2760358682458709 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272904982835389 mean_prior_absolute_error 0.272804289453111 mean_prior_absolute_error 0.27287651677373237 mean_prior_absolute_error 0.2728747259382053 mean_prior_absolute_error 0.2728747259382053 mean_prior_absolute_error 0.2728747259382053 mean_prior_absolute_error 0.2728747259382053 number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,51,41,28] number_of_instances 280 [58,34,68,52,41,27] number_of_instances 280 [58,35,68,51,41,27] number_of_instances 279 [57,34,68,51,42,27] number_of_instances 279 [57,34,68,51,42,27] number_of_instances 279 [57,34,68,51,42,27] number_of_instances 279 [57,34,68,51,42,27] predictive_accuracy 0.24285714285714285 predictive_accuracy 0.24285714285714285 predictive_accuracy 0.24285714285714285 predictive_accuracy 0.24285714285714285 predictive_accuracy 0.24285714285714285 predictive_accuracy 0.24285714285714285 predictive_accuracy 0.24372759856630824 predictive_accuracy 0.24372759856630824 predictive_accuracy 0.24372759856630824 predictive_accuracy 0.24372759856630824 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 prior_entropy 2.5206634795042744 recall 0.24285714285714285 [0,0,1,0,0,0] recall 0.24285714285714285 [0,0,1,0,0,0] recall 0.24285714285714285 [0,0,1,0,0,0] recall 0.24285714285714285 [0,0,1,0,0,0] recall 0.24285714285714285 [0,0,1,0,0,0] recall 0.24285714285714285 [0,0,1,0,0,0] recall 0.24372759856630824 [0,0,1,0,0,0] recall 0.24372759856630824 [0,0,1,0,0,0] recall 0.24372759856630824 [0,0,1,0,0,0] recall 0.24372759856630824 [0,0,1,0,0,0] relative_absolute_error 1.0113979716387596 relative_absolute_error 1.011743923640697 relative_absolute_error 1.0111957467640031 relative_absolute_error 1.011416319470152 relative_absolute_error 1.0122948759931893 relative_absolute_error 1.011691451574154 relative_absolute_error 1.0115097969498448 relative_absolute_error 1.0115614822033672 relative_absolute_error 1.0116977301026033 relative_absolute_error 1.01158459178217 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36940459271455434 root_mean_prior_squared_error 0.36926827610333357 root_mean_prior_squared_error 0.36936606105183667 root_mean_prior_squared_error 0.3693636368423697 root_mean_prior_squared_error 0.3693636368423697 root_mean_prior_squared_error 0.3693636368423697 root_mean_prior_squared_error 0.3693636368423697 root_mean_squared_error 0.3705076332040129 root_mean_squared_error 0.3706327735407058 root_mean_squared_error 0.3704389969195741 root_mean_squared_error 0.3705232581001053 root_mean_squared_error 0.37071723418216407 root_mean_squared_error 0.37058076757960073 root_mean_squared_error 0.37051412859239713 root_mean_squared_error 0.3705384939945349 root_mean_squared_error 0.3705804008380578 root_mean_squared_error 0.37053820952276395 root_relative_squared_error 1.0029859956026885 root_relative_squared_error 1.003324757868131 root_relative_squared_error 1.0028001931362533 root_relative_squared_error 1.0030282931171226 root_relative_squared_error 1.0039238628731406 root_relative_squared_error 1.00328862517662 root_relative_squared_error 1.0031147942982768 root_relative_squared_error 1.0031807601912544 root_relative_squared_error 1.0032942170650312 root_relative_squared_error 1.0031799900240193 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 usercpu_time_millis 1339.5688450036687 usercpu_time_millis 1308.165515998553 usercpu_time_millis 1289.0291410003556 usercpu_time_millis 1282.2335250020842 usercpu_time_millis 1280.0997470003495 usercpu_time_millis 1305.975497001782 usercpu_time_millis 1290.1439699999173 usercpu_time_millis 1315.8818660049292 usercpu_time_millis 1329.1815060001682 usercpu_time_millis 1281.7878860005294 usercpu_time_millis_testing 3.7520660007430706 usercpu_time_millis_testing 3.7629090002155863 usercpu_time_millis_testing 3.728792999027064 usercpu_time_millis_testing 3.6670369991043117 usercpu_time_millis_testing 3.772184001718415 usercpu_time_millis_testing 3.630338000220945 usercpu_time_millis_testing 3.8072520001151133 usercpu_time_millis_testing 3.7703420020989142 usercpu_time_millis_testing 3.8194919980014674 usercpu_time_millis_testing 3.686842999741202 usercpu_time_millis_training 1335.8167790029256 usercpu_time_millis_training 1304.4026069983374 usercpu_time_millis_training 1285.3003480013285 usercpu_time_millis_training 1278.56648800298 usercpu_time_millis_training 1276.327562998631 usercpu_time_millis_training 1302.3451590015611 usercpu_time_millis_training 1286.3367179998022 usercpu_time_millis_training 1312.1115240028303 usercpu_time_millis_training 1325.3620140021667 usercpu_time_millis_training 1278.1010430007882