10098532 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) 8023685 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 "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 13 8783 min_samples_split 7 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 10005 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 21117601 description https://api.openml.org/data/download/21117601/description.xml -1 21117602 predictions https://api.openml.org/data/download/21117602/predictions.arff area_under_roc_curve 0.8224020710059171 [0.822402,0.822402] average_cost 0 f_measure 0.7510503994929253 [0.756125,0.745976] kappa 0.5023076923076923 kb_relative_information_score 1271.587073385655 mean_absolute_error 0.2576328889016128 mean_prior_absolute_error 0.5 number_of_instances 2600 [1300,1300] precision 0.7515719915528236 [0.741316,0.761828] predictive_accuracy 0.7511538461538462 prior_entropy 1 recall 0.7511538461538462 [0.771538,0.730769] relative_absolute_error 0.5152657778032256 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.434280499007305 root_relative_squared_error 0.86856099801461 total_cost 0 area_under_roc_curve 0.8550591715976331 [0.855059,0.855059] area_under_roc_curve 0.7892011834319527 [0.789201,0.789201] area_under_roc_curve 0.8209763313609467 [0.820976,0.820976] area_under_roc_curve 0.8356508875739646 [0.835651,0.835651] area_under_roc_curve 0.8210355029585799 [0.821036,0.821036] area_under_roc_curve 0.824792899408284 [0.824793,0.824793] area_under_roc_curve 0.8601479289940829 [0.860148,0.860148] area_under_roc_curve 0.7437869822485207 [0.743787,0.743787] area_under_roc_curve 0.8197337278106509 [0.819734,0.819734] area_under_roc_curve 0.8511834319526628 [0.851183,0.851183] 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 0.7768702651515151 [0.780303,0.773438] f_measure 0.7384460618971538 [0.740458,0.736434] f_measure 0.7691761363636365 [0.772727,0.765625] f_measure 0.74609375 [0.742187,0.75] f_measure 0.7692307692307693 [0.769231,0.769231] f_measure 0.738322183411284 [0.744361,0.732283] f_measure 0.7999881649801763 [0.79845,0.801527] f_measure 0.675367144301088 [0.697842,0.652893] f_measure 0.7598188211454795 [0.780142,0.739496] f_measure 0.7345800476394785 [0.737643,0.731518] kappa 0.5538461538461539 kappa 0.476923076923077 kappa 0.5384615384615385 kappa 0.49230769230769234 kappa 0.5384615384615385 kappa 0.476923076923077 kappa 0.6000000000000001 kappa 0.3538461538461539 kappa 0.523076923076923 kappa 0.46923076923076934 kb_relative_information_score 143.3226529552088 kb_relative_information_score 115.19496027148662 kb_relative_information_score 130.22382788284608 kb_relative_information_score 131.79528854702 kb_relative_information_score 130.2875757350833 kb_relative_information_score 125.73025490852466 kb_relative_information_score 143.93127806139276 kb_relative_information_score 88.71022118670803 kb_relative_information_score 126.47143629890802 kb_relative_information_score 135.91957753847547 mean_absolute_error 0.22490791602454457 mean_absolute_error 0.2813253628604398 mean_absolute_error 0.25498039974540077 mean_absolute_error 0.2477293686432483 mean_absolute_error 0.2535847841468617 mean_absolute_error 0.25864521118923034 mean_absolute_error 0.22705600948316357 mean_absolute_error 0.33049562527652543 mean_absolute_error 0.25955481100360844 mean_absolute_error 0.2380494006431043 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 0.777185501066098 [0.768657,0.785714] precision 0.7385179924242424 [0.734848,0.742188] precision 0.769485903814262 [0.761194,0.777778] precision 0.7463871120587537 [0.753968,0.738806] precision 0.7692307692307693 [0.769231,0.769231] precision 0.738970588235294 [0.727941,0.75] precision 0.8000710227272727 [0.804688,0.795455] precision 0.6803812741312741 [0.655405,0.705357] precision 0.7692495126705653 [0.723684,0.814815] precision 0.7347403942928187 [0.729323,0.740157] predictive_accuracy 0.7769230769230769 predictive_accuracy 0.7384615384615384 predictive_accuracy 0.7692307692307692 predictive_accuracy 0.7461538461538462 predictive_accuracy 0.7692307692307692 predictive_accuracy 0.7384615384615384 predictive_accuracy 0.8 predictive_accuracy 0.676923076923077 predictive_accuracy 0.7615384615384616 predictive_accuracy 0.7346153846153847 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 0.7769230769230769 [0.792308,0.761538] recall 0.7384615384615385 [0.746154,0.730769] recall 0.7692307692307693 [0.784615,0.753846] recall 0.7461538461538462 [0.730769,0.761538] recall 0.7692307692307693 [0.769231,0.769231] recall 0.7384615384615385 [0.761538,0.715385] recall 0.8 [0.792308,0.807692] recall 0.676923076923077 [0.746154,0.607692] recall 0.7615384615384615 [0.846154,0.676923] recall 0.7346153846153847 [0.746154,0.723077] relative_absolute_error 0.44981583204908915 relative_absolute_error 0.5626507257208796 relative_absolute_error 0.5099607994908015 relative_absolute_error 0.4954587372864966 relative_absolute_error 0.5071695682937234 relative_absolute_error 0.5172904223784607 relative_absolute_error 0.45411201896632714 relative_absolute_error 0.6609912505530509 relative_absolute_error 0.5191096220072169 relative_absolute_error 0.4760988012862086 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 0.40954653057889107 root_mean_squared_error 0.4553525209811452 root_mean_squared_error 0.42888663886420225 root_mean_squared_error 0.42282649091813435 root_mean_squared_error 0.4328856193625356 root_mean_squared_error 0.43933097105307256 root_mean_squared_error 0.3974340635317087 root_mean_squared_error 0.5009572323007552 root_mean_squared_error 0.4316059817617544 root_mean_squared_error 0.4154490103120486 root_relative_squared_error 0.819093061157782 root_relative_squared_error 0.9107050419622904 root_relative_squared_error 0.8577732777284045 root_relative_squared_error 0.8456529818362687 root_relative_squared_error 0.8657712387250711 root_relative_squared_error 0.8786619421061451 root_relative_squared_error 0.7948681270634174 root_relative_squared_error 1.0019144646015103 root_relative_squared_error 0.8632119635235088 root_relative_squared_error 0.8308980206240971 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 2026.251620001858 usercpu_time_millis 1918.299670000124 usercpu_time_millis 1920.9222580029746 usercpu_time_millis 1879.6195240029192 usercpu_time_millis 1908.8779850026185 usercpu_time_millis 1922.8603099982138 usercpu_time_millis 1933.2737420008925 usercpu_time_millis 1958.344083999691 usercpu_time_millis 1914.9881029989047 usercpu_time_millis 1891.8792659969768 usercpu_time_millis_testing 5.201433999900473 usercpu_time_millis_testing 5.0856630005000625 usercpu_time_millis_testing 5.410214002040448 usercpu_time_millis_testing 5.013589001464425 usercpu_time_millis_testing 4.96432300133165 usercpu_time_millis_testing 5.042863998824032 usercpu_time_millis_testing 5.001995999919018 usercpu_time_millis_testing 5.167896000784822 usercpu_time_millis_testing 4.937573998176958 usercpu_time_millis_testing 5.034316000092076 usercpu_time_millis_training 2021.0501860019576 usercpu_time_millis_training 1913.214006999624 usercpu_time_millis_training 1915.512044000934 usercpu_time_millis_training 1874.6059350014548 usercpu_time_millis_training 1903.9136620012869 usercpu_time_millis_training 1917.8174459993897 usercpu_time_millis_training 1928.2717460009735 usercpu_time_millis_training 1953.1761879989062 usercpu_time_millis_training 1910.0505290007277 usercpu_time_millis_training 1886.8449499968847