10218703 1 Jan van Rijn 3494 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) 8144135 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": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5]}}] 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 0.0006357157695232822 9667 loss "deviance" 9667 max_depth 3 9667 max_features 0.8996129746250127 9667 max_leaf_nodes null 9667 min_impurity_decrease 0.6728327267849243 9667 min_impurity_split null 9667 min_samples_leaf 18 9667 min_samples_split 10 9667 min_weight_fraction_leaf 0.08859115990192873 9667 n_estimators 1152 9667 n_iter_no_change 1734 9667 presort "auto" 9667 random_state 28507 9667 subsample 0.7391341058428973 9667 tol 9.462018835380364e-05 9667 validation_fraction 0.11977705666514249 9667 verbose 0 9667 warm_start false 9667 openml-python Sklearn_0.20.3. 335 monks-problems-3 https://www.openml.org/data/download/52238/phphZierv -1 21358322 description https://api.openml.org/data/download/21358322/description.xml -1 21358323 predictions https://api.openml.org/data/download/21358323/predictions.arff area_under_roc_curve 0.9853866436925648 [0.985387,0.985387] average_cost 0 f_measure 0.9639130386277776 [0.9631,0.964664] kappa 0.9277874814254804 kb_relative_information_score 296.6178548519409 mean_absolute_error 0.2713594937023081 mean_prior_absolute_error 0.4992143469340059 number_of_instances 554 [266,288] precision 0.9645552746313386 [0.945652,0.982014] predictive_accuracy 0.9638989169675091 prior_entropy 0.9988703245161819 recall 0.9638989169675091 [0.981203,0.947917] relative_absolute_error 0.5435731071610823 root_mean_prior_squared_error 0.49960560487440536 root_mean_squared_error 0.28330122177861455 root_relative_squared_error 0.5670497268537108 total_cost 0 area_under_roc_curve 0.979565772669221 [0.979566,0.979566] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.9907161803713528 [0.990716,0.990716] area_under_roc_curve 0.9754641909814323 [0.975464,0.975464] area_under_roc_curve 1 [1,1] 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 f_measure 0.9642857142857143 [0.962963,0.965517] f_measure 0.9821485532011848 [0.981818,0.982456] f_measure 0.9642857142857143 [0.964286,0.964286] f_measure 0.9642857142857143 [0.964286,0.964286] f_measure 0.9818181818181818 [0.981818,0.981818] f_measure 0.9636123136123137 [0.964286,0.962963] f_measure 0.9636604136604137 [0.962963,0.964286] f_measure 0.9453820357110487 [0.941176,0.949153] f_measure 0.9091510938581445 [0.90566,0.912281] f_measure 1 [1,1] kappa 0.9284802043422733 kappa 0.9642857142857142 kappa 0.9286624203821655 kappa 0.9286624203821655 kappa 0.9636483807005949 kappa 0.927344782034346 kappa 0.927344782034346 kappa 0.8903654485049833 kappa 0.8180013236267372 kappa 1 kb_relative_information_score 30.475669259494957 kb_relative_information_score 30.66374846294996 kb_relative_information_score 30.498349466283607 kb_relative_information_score 30.322203637947425 kb_relative_information_score 30.832053657881403 kb_relative_information_score 29.370364227236706 kb_relative_information_score 29.331986729261402 kb_relative_information_score 28.60148234336759 kb_relative_information_score 26.028942971611315 kb_relative_information_score 30.493054095906768 mean_absolute_error 0.2669440120669787 mean_absolute_error 0.26695340201929124 mean_absolute_error 0.2671476712583837 mean_absolute_error 0.26870451269405365 mean_absolute_error 0.2609551849407833 mean_absolute_error 0.2727230234521702 mean_absolute_error 0.2720434286759578 mean_absolute_error 0.2769668966200138 mean_absolute_error 0.29726539100392513 mean_absolute_error 0.2641766575055311 mean_prior_absolute_error 0.4992934224049325 mean_prior_absolute_error 0.4992934224049325 mean_prior_absolute_error 0.4992934224049325 mean_prior_absolute_error 0.4992934224049325 mean_prior_absolute_error 0.4996402877697835 mean_prior_absolute_error 0.4996402877697835 mean_prior_absolute_error 0.49892086330935187 mean_prior_absolute_error 0.49892086330935187 mean_prior_absolute_error 0.49892086330935187 mean_prior_absolute_error 0.49892086330935187 number_of_instances 56 [27,29] number_of_instances 56 [27,29] number_of_instances 56 [27,29] number_of_instances 56 [27,29] number_of_instances 55 [27,28] number_of_instances 55 [27,28] number_of_instances 55 [26,29] number_of_instances 55 [26,29] number_of_instances 55 [26,29] number_of_instances 55 [26,29] precision 0.9642857142857143 [0.962963,0.965517] precision 0.982780612244898 [0.964286,1] precision 0.9667487684729065 [0.931034,1] precision 0.9667487684729065 [0.931034,1] precision 0.9824675324675325 [0.964286,1] precision 0.9661442006269593 [0.931034,1] precision 0.9662337662337661 [0.928571,1] precision 0.945939393939394 [0.96,0.933333] precision 0.90981240981241 [0.888889,0.928571] precision 1 [1,1] predictive_accuracy 0.9642857142857143 predictive_accuracy 0.9821428571428571 predictive_accuracy 0.9642857142857143 predictive_accuracy 0.9642857142857143 predictive_accuracy 0.9818181818181819 predictive_accuracy 0.9636363636363636 predictive_accuracy 0.9636363636363636 predictive_accuracy 0.9454545454545454 predictive_accuracy 0.9090909090909091 predictive_accuracy 1 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 prior_entropy 0.9988703245161819 recall 0.9642857142857143 [0.962963,0.965517] recall 0.9821428571428571 [1,0.965517] recall 0.9642857142857143 [1,0.931034] recall 0.9642857142857143 [1,0.931034] recall 0.9818181818181818 [1,0.964286] recall 0.9636363636363636 [1,0.928571] recall 0.9636363636363636 [1,0.931034] recall 0.9454545454545454 [0.923077,0.965517] recall 0.9090909090909091 [0.923077,0.896552] recall 1 [1,1] relative_absolute_error 0.5346435584534581 relative_absolute_error 0.5346623649345595 relative_absolute_error 0.5350514532549238 relative_absolute_error 0.5381695424702216 relative_absolute_error 0.5222861152882495 relative_absolute_error 0.5458387366429333 relative_absolute_error 0.5452636854500098 relative_absolute_error 0.5551319196853924 relative_absolute_error 0.5958167173690793 relative_absolute_error 0.529496112375903 root_mean_prior_squared_error 0.49968473650177464 root_mean_prior_squared_error 0.49968473650177464 root_mean_prior_squared_error 0.49968473650177464 root_mean_prior_squared_error 0.49968473650177464 root_mean_prior_squared_error 0.5000317002527929 root_mean_prior_squared_error 0.5000317002527929 root_mean_prior_squared_error 0.49931180318240753 root_mean_prior_squared_error 0.49931180318240753 root_mean_prior_squared_error 0.49931180318240753 root_mean_prior_squared_error 0.49931180318240753 root_mean_squared_error 0.2825856654061621 root_mean_squared_error 0.2722753673675748 root_mean_squared_error 0.27584779917281765 root_mean_squared_error 0.2776850623393433 root_mean_squared_error 0.2666543887749207 root_mean_squared_error 0.28283431812062293 root_mean_squared_error 0.2824050305799303 root_mean_squared_error 0.2975478880593648 root_mean_squared_error 0.3244903959130759 root_mean_squared_error 0.2664149097544448 root_relative_squared_error 0.5655279114277257 root_relative_squared_error 0.5448943053048566 root_relative_squared_error 0.5520436767870694 root_relative_squared_error 0.5557205214699551 root_relative_squared_error 0.5332749676472764 root_relative_squared_error 0.5656327748373453 root_relative_squared_error 0.5655885336176656 root_relative_squared_error 0.595915991095979 root_relative_squared_error 0.6498752760197294 root_relative_squared_error 0.5335642138968598 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 1003.9532490009151 usercpu_time_millis 941.3277690000541 usercpu_time_millis 941.7302879955969 usercpu_time_millis 935.2583479994792 usercpu_time_millis 930.7182809970982 usercpu_time_millis 933.2291189966782 usercpu_time_millis 925.9927699968102 usercpu_time_millis 928.9386050004396 usercpu_time_millis 923.1227269992814 usercpu_time_millis 941.1096570038353 usercpu_time_millis_testing 2.6190380012849346 usercpu_time_millis_testing 2.5929240000550635 usercpu_time_millis_testing 2.606099998956779 usercpu_time_millis_testing 2.62238499999512 usercpu_time_millis_testing 2.5660439969215076 usercpu_time_millis_testing 2.5113359988608863 usercpu_time_millis_testing 2.5425519997952506 usercpu_time_millis_testing 2.627718000439927 usercpu_time_millis_testing 2.6470339980733115 usercpu_time_millis_testing 2.6353620014560875 usercpu_time_millis_training 1001.3342109996302 usercpu_time_millis_training 938.734844999999 usercpu_time_millis_training 939.1241879966401 usercpu_time_millis_training 932.635962999484 usercpu_time_millis_training 928.1522370001767 usercpu_time_millis_training 930.7177829978173 usercpu_time_millis_training 923.450217997015 usercpu_time_millis_training 926.3108869999996 usercpu_time_millis_training 920.4756930012081 usercpu_time_millis_training 938.4742950023792