10101475 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) 8026659 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "most_frequent" 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 "gini" 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 9 8783 min_samples_split 17 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 6798 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 21123488 description https://api.openml.org/data/download/21123488/description.xml -1 21123489 predictions https://api.openml.org/data/download/21123489/predictions.arff area_under_roc_curve 0.8358772189349113 [0.835877,0.835877] average_cost 0 f_measure 0.777307395823456 [0.777564,0.77705] kappa 0.5546153846153845 kb_relative_information_score 1393.891058462065 mean_absolute_error 0.23433658793443826 mean_prior_absolute_error 0.5 number_of_instances 2600 [1300,1300] precision 0.777309169102084 [0.776669,0.777949] predictive_accuracy 0.7773076923076923 prior_entropy 1 recall 0.7773076923076923 [0.778462,0.776154] relative_absolute_error 0.4686731758688765 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.4186506280236463 root_relative_squared_error 0.8373012560472926 total_cost 0 area_under_roc_curve 0.8528994082840237 [0.852899,0.852899] area_under_roc_curve 0.8413313609467455 [0.841331,0.841331] area_under_roc_curve 0.8218639053254437 [0.821864,0.821864] area_under_roc_curve 0.8806804733727811 [0.88068,0.88068] area_under_roc_curve 0.8789644970414201 [0.878964,0.878964] area_under_roc_curve 0.8290532544378698 [0.829053,0.829053] area_under_roc_curve 0.8222485207100592 [0.822249,0.822249] area_under_roc_curve 0.7714497041420119 [0.77145,0.77145] area_under_roc_curve 0.8172781065088758 [0.817278,0.817278] area_under_roc_curve 0.8435502958579881 [0.84355,0.84355] 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 0.7960059806664594 [0.801498,0.790514] f_measure 0.7768702651515151 [0.773438,0.780303] f_measure 0.7880822181715793 [0.779116,0.797048] f_measure 0.8036108354685348 [0.796813,0.810409] f_measure 0.8307291666666669 [0.833333,0.828125] f_measure 0.7884333713068308 [0.790875,0.785992] f_measure 0.7576026637069921 [0.752941,0.762264] f_measure 0.7076750103556423 [0.709924,0.705426] f_measure 0.7456119544592031 [0.757353,0.733871] f_measure 0.7768702651515151 [0.780303,0.773438] kappa 0.5923076923076922 kappa 0.5538461538461539 kappa 0.5769230769230769 kappa 0.6076923076923078 kappa 0.6615384615384616 kappa 0.5769230769230769 kappa 0.5153846153846153 kappa 0.41538461538461546 kappa 0.49230769230769234 kappa 0.5538461538461539 kb_relative_information_score 145.1896086893156 kb_relative_information_score 141.56789803376122 kb_relative_information_score 135.8429260681678 kb_relative_information_score 157.52634797787357 kb_relative_information_score 162.50871286319733 kb_relative_information_score 141.3462812446326 kb_relative_information_score 134.3419508257261 kb_relative_information_score 107.86583829908768 kb_relative_information_score 126.69795919819336 kb_relative_information_score 141.00353526211146 mean_absolute_error 0.22443843549612788 mean_absolute_error 0.22901178603950093 mean_absolute_error 0.24229255535816624 mean_absolute_error 0.19891519491067006 mean_absolute_error 0.19249952033888693 mean_absolute_error 0.23146006582658177 mean_absolute_error 0.24251299982069224 mean_absolute_error 0.29283897537856807 mean_absolute_error 0.25893854542893 mean_absolute_error 0.23045780074626238 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 0.7970150139457599 [0.781022,0.813008] precision 0.777185501066098 [0.785714,0.768657] precision 0.7905417486143395 [0.815126,0.765957] precision 0.8053094714311196 [0.826446,0.784173] precision 0.8310826818289504 [0.820896,0.84127] precision 0.7886152388846132 [0.781955,0.795276] precision 0.7580740740740741 [0.768,0.748148] precision 0.7077414772727273 [0.704545,0.710938] precision 0.7482692766770113 [0.725352,0.771186] precision 0.777185501066098 [0.768657,0.785714] predictive_accuracy 0.7961538461538461 predictive_accuracy 0.7769230769230769 predictive_accuracy 0.7884615384615384 predictive_accuracy 0.8038461538461539 predictive_accuracy 0.8307692307692308 predictive_accuracy 0.7884615384615384 predictive_accuracy 0.7576923076923078 predictive_accuracy 0.7076923076923077 predictive_accuracy 0.7461538461538462 predictive_accuracy 0.7769230769230769 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 0.7961538461538461 [0.823077,0.769231] recall 0.7769230769230769 [0.761538,0.792308] recall 0.7884615384615384 [0.746154,0.830769] recall 0.8038461538461539 [0.769231,0.838462] recall 0.8307692307692308 [0.846154,0.815385] recall 0.7884615384615384 [0.8,0.776923] recall 0.7576923076923077 [0.738462,0.776923] recall 0.7076923076923077 [0.715385,0.7] recall 0.7461538461538462 [0.792308,0.7] recall 0.7769230769230769 [0.792308,0.761538] relative_absolute_error 0.4488768709922557 relative_absolute_error 0.45802357207900185 relative_absolute_error 0.4845851107163325 relative_absolute_error 0.3978303898213401 relative_absolute_error 0.38499904067777385 relative_absolute_error 0.46292013165316354 relative_absolute_error 0.4850259996413845 relative_absolute_error 0.5856779507571361 relative_absolute_error 0.51787709085786 relative_absolute_error 0.46091560149252475 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 0.4013305885671066 root_mean_squared_error 0.4158292156341199 root_mean_squared_error 0.43145933083099647 root_mean_squared_error 0.37736694586244607 root_mean_squared_error 0.367901873095585 root_mean_squared_error 0.41769427412233723 root_mean_squared_error 0.4343888271594606 root_mean_squared_error 0.48367126242035946 root_mean_squared_error 0.4320626451921398 root_mean_squared_error 0.4135340035308004 root_relative_squared_error 0.8026611771342133 root_relative_squared_error 0.8316584312682397 root_relative_squared_error 0.8629186616619929 root_relative_squared_error 0.7547338917248922 root_relative_squared_error 0.73580374619117 root_relative_squared_error 0.8353885482446745 root_relative_squared_error 0.8687776543189212 root_relative_squared_error 0.9673425248407189 root_relative_squared_error 0.8641252903842797 root_relative_squared_error 0.8270680070616008 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 1762.4238050002532 usercpu_time_millis 1599.3167579990768 usercpu_time_millis 1589.7242350001761 usercpu_time_millis 1559.893620999901 usercpu_time_millis 1557.702438000888 usercpu_time_millis 1578.210575000412 usercpu_time_millis 1577.0733720000862 usercpu_time_millis 1595.9211820008932 usercpu_time_millis 1595.9299169999213 usercpu_time_millis 1613.4653529998104 usercpu_time_millis_testing 4.452510000191978 usercpu_time_millis_testing 4.363119999652554 usercpu_time_millis_testing 4.437116000190144 usercpu_time_millis_testing 4.407377999996243 usercpu_time_millis_testing 4.33459300074901 usercpu_time_millis_testing 4.401669000799302 usercpu_time_millis_testing 4.35135000043374 usercpu_time_millis_testing 4.35030500011635 usercpu_time_millis_testing 4.919713999697706 usercpu_time_millis_testing 4.349821999312553 usercpu_time_millis_training 1757.9712950000612 usercpu_time_millis_training 1594.9536379994242 usercpu_time_millis_training 1585.287118999986 usercpu_time_millis_training 1555.4862429999048 usercpu_time_millis_training 1553.367845000139 usercpu_time_millis_training 1573.8089059996128 usercpu_time_millis_training 1572.7220219996525 usercpu_time_millis_training 1591.5708770007768 usercpu_time_millis_training 1591.0102030002236 usercpu_time_millis_training 1609.1155310004979