10093632 1 Jan van Rijn 9976 Supervised Classification 8815 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,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1) 8018746 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "median" 8778 verbose 0 8778 copy true 8779 with_mean true 8779 with_std true 8779 memory null 8780 copy true 8781 fill_value -1 8781 missing_values NaN 8781 strategy "constant" 8781 verbose 0 8781 categorical_features null 8782 categories null 8782 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 8782 handle_unknown "ignore" 8782 n_values null 8782 sparse true 8782 class_weight null 8783 criterion "entropy" 8783 max_depth null 8783 max_features 1.0 8783 max_leaf_nodes null 8783 min_impurity_decrease 0.0 8783 min_impurity_split null 8783 min_samples_leaf 7 8783 min_samples_split 16 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 8472 8783 splitter "best" 8783 n_jobs null 8812 remainder "passthrough" 8812 sparse_threshold 0.3 8812 transformer_weights null 8812 memory null 8813 memory null 8815 threshold 0.0 8816 openml-python Sklearn_0.20.0. 1485 madelon https://www.openml.org/data/download/1590986/phpfLuQE4 -1 21107801 description https://api.openml.org/data/download/21107801/description.xml -1 21107802 predictions https://api.openml.org/data/download/21107802/predictions.arff area_under_roc_curve 0.8132860946745561 [0.813286,0.813286] average_cost 0 f_measure 0.7692295402756583 [0.768697,0.769762] kappa 0.5384615384615385 kb_relative_information_score 1375.9030742281861 mean_absolute_error 0.23673042769196614 mean_prior_absolute_error 0.5 number_of_instances 2600 [1300,1300] precision 0.7692365044462486 [0.770479,0.767994] predictive_accuracy 0.7692307692307692 prior_entropy 1 recall 0.7692307692307693 [0.766923,0.771538] relative_absolute_error 0.47346085538393223 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.44172671781654144 root_relative_squared_error 0.8834534356330829 total_cost 0 area_under_roc_curve 0.8747633136094675 [0.874763,0.874763] area_under_roc_curve 0.8175443786982248 [0.817544,0.817544] area_under_roc_curve 0.798284023668639 [0.798284,0.798284] area_under_roc_curve 0.8289349112426035 [0.828935,0.828935] area_under_roc_curve 0.8076627218934911 [0.807663,0.807663] area_under_roc_curve 0.8237278106508876 [0.823728,0.823728] area_under_roc_curve 0.785680473372781 [0.78568,0.78568] area_under_roc_curve 0.7527514792899408 [0.752751,0.752751] area_under_roc_curve 0.8064497041420118 [0.80645,0.80645] area_under_roc_curve 0.8329289940828403 [0.832929,0.832929] 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 0.8306088604596067 [0.825397,0.835821] f_measure 0.7499667115444363 [0.752852,0.747082] f_measure 0.7497000844206816 [0.741036,0.758364] f_measure 0.7921108742004264 [0.785714,0.798507] f_measure 0.7921970280030785 [0.796992,0.787402] f_measure 0.7960784313725489 [0.792157,0.8] f_measure 0.7191268960414353 [0.724528,0.713725] f_measure 0.696149351321765 [0.697318,0.694981] f_measure 0.7806102056224186 [0.786517,0.774704] f_measure 0.7846026392094209 [0.78626,0.782946] kappa 0.6615384615384616 kappa 0.5 kappa 0.5 kappa 0.5846153846153845 kappa 0.5846153846153845 kappa 0.5923076923076922 kappa 0.43846153846153846 kappa 0.39230769230769225 kappa 0.5615384615384615 kappa 0.5692307692307692 kb_relative_information_score 169.2545544079927 kb_relative_information_score 133.09370259993426 kb_relative_information_score 128.38654152866127 kb_relative_information_score 147.91373051536567 kb_relative_information_score 141.66269417269197 kb_relative_information_score 144.0911716595084 kb_relative_information_score 120.2196958201254 kb_relative_information_score 105.55574326671203 kb_relative_information_score 138.97538415786067 kb_relative_information_score 146.7498560993322 mean_absolute_error 0.1760650353919584 mean_absolute_error 0.24303806236498549 mean_absolute_error 0.2548450374411913 mean_absolute_error 0.21718446083830706 mean_absolute_error 0.23121501361885985 mean_absolute_error 0.22539505366428444 mean_absolute_error 0.2679061003099465 mean_absolute_error 0.2969927188196419 mean_absolute_error 0.23518452701145015 mean_absolute_error 0.21947826745903676 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 mean_prior_absolute_error 0.5 number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] number_of_instances 260 [130,130] precision 0.8320266096459967 [0.852459,0.811594] precision 0.7501332070333313 [0.744361,0.755906] precision 0.7512039954813009 [0.768595,0.733813] precision 0.7934188643383226 [0.811475,0.775362] precision 0.7929316888045541 [0.779412,0.806452] precision 0.7965925925925926 [0.808,0.785185] precision 0.7195555555555555 [0.711111,0.728] precision 0.6961654535771347 [0.694656,0.697674] precision 0.7815856625719542 [0.766423,0.796748] precision 0.7846827651515151 [0.780303,0.789062] predictive_accuracy 0.8307692307692308 predictive_accuracy 0.75 predictive_accuracy 0.75 predictive_accuracy 0.7923076923076923 predictive_accuracy 0.7923076923076923 predictive_accuracy 0.7961538461538461 predictive_accuracy 0.7192307692307692 predictive_accuracy 0.6961538461538461 predictive_accuracy 0.7807692307692308 predictive_accuracy 0.7846153846153847 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 prior_entropy 1 recall 0.8307692307692308 [0.8,0.861538] recall 0.75 [0.761538,0.738462] recall 0.75 [0.715385,0.784615] recall 0.7923076923076923 [0.761538,0.823077] recall 0.7923076923076923 [0.815385,0.769231] recall 0.7961538461538461 [0.776923,0.815385] recall 0.7192307692307692 [0.738462,0.7] recall 0.6961538461538461 [0.7,0.692308] recall 0.7807692307692308 [0.807692,0.753846] recall 0.7846153846153846 [0.792308,0.776923] relative_absolute_error 0.3521300707839168 relative_absolute_error 0.48607612472997097 relative_absolute_error 0.5096900748823826 relative_absolute_error 0.4343689216766141 relative_absolute_error 0.46243002723771975 relative_absolute_error 0.4507901073285689 relative_absolute_error 0.535812200619893 relative_absolute_error 0.5939854376392838 relative_absolute_error 0.4703690540229003 relative_absolute_error 0.4389565349180735 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.37589819676724184 root_mean_squared_error 0.4465050421519521 root_mean_squared_error 0.4530665313885269 root_mean_squared_error 0.424992045399015 root_mean_squared_error 0.4366505942751246 root_mean_squared_error 0.4278735067839117 root_mean_squared_error 0.4735282399455398 root_mean_squared_error 0.4997876089558506 root_mean_squared_error 0.4483310532033681 root_mean_squared_error 0.41942143980291013 root_relative_squared_error 0.7517963935344837 root_relative_squared_error 0.8930100843039042 root_relative_squared_error 0.9061330627770539 root_relative_squared_error 0.84998409079803 root_relative_squared_error 0.8733011885502492 root_relative_squared_error 0.8557470135678232 root_relative_squared_error 0.9470564798910796 root_relative_squared_error 0.9995752179117012 root_relative_squared_error 0.8966621064067362 root_relative_squared_error 0.8388428796058203 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 1014.7963890012761 usercpu_time_millis 941.860702001577 usercpu_time_millis 993.2217400018999 usercpu_time_millis 933.5409479972441 usercpu_time_millis 942.3483280006621 usercpu_time_millis 962.6925939992361 usercpu_time_millis 1002.6243219981552 usercpu_time_millis 1079.1713369981153 usercpu_time_millis 968.5756279977795 usercpu_time_millis 973.0436210011248 usercpu_time_millis_testing 5.370085000322433 usercpu_time_millis_testing 5.267378001008183 usercpu_time_millis_testing 5.262345999653917 usercpu_time_millis_testing 5.164453999896068 usercpu_time_millis_testing 5.219398000917863 usercpu_time_millis_testing 5.200527000852162 usercpu_time_millis_testing 5.218800997681683 usercpu_time_millis_testing 5.16732699907152 usercpu_time_millis_testing 5.238358000497101 usercpu_time_millis_testing 5.237319001025753 usercpu_time_millis_training 1009.4263040009537 usercpu_time_millis_training 936.5933240005688 usercpu_time_millis_training 987.959394002246 usercpu_time_millis_training 928.376493997348 usercpu_time_millis_training 937.1289299997443 usercpu_time_millis_training 957.492066998384 usercpu_time_millis_training 997.4055210004735 usercpu_time_millis_training 1074.0040099990438 usercpu_time_millis_training 963.3372699972824 usercpu_time_millis_training 967.8063020000991