10149306 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) 8074940 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 18 8783 min_samples_split 8 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 50539 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 21219151 description https://api.openml.org/data/download/21219151/description.xml -1 21219152 predictions https://api.openml.org/data/download/21219152/predictions.arff area_under_roc_curve 0.8289742603550296 [0.828974,0.828974] average_cost 0 f_measure 0.7572918588328025 [0.759252,0.755332] kappa 0.5146153846153847 kb_relative_information_score 1246.3261128362772 mean_absolute_error 0.264134475916909 mean_prior_absolute_error 0.5 number_of_instances 2600 [1300,1300] precision 0.7573748534380865 [0.753217,0.761532] predictive_accuracy 0.7573076923076922 prior_entropy 1 recall 0.7573076923076923 [0.765385,0.749231] relative_absolute_error 0.528268951833818 root_mean_prior_squared_error 0.5 root_mean_squared_error 0.4237147498554429 root_relative_squared_error 0.8474294997108858 total_cost 0 area_under_roc_curve 0.862869822485207 [0.86287,0.86287] area_under_roc_curve 0.8190236686390533 [0.819024,0.819024] area_under_roc_curve 0.8346153846153846 [0.834615,0.834615] area_under_roc_curve 0.8361242603550296 [0.836124,0.836124] area_under_roc_curve 0.8372485207100592 [0.837249,0.837249] area_under_roc_curve 0.8221597633136095 [0.82216,0.82216] area_under_roc_curve 0.8573076923076923 [0.857308,0.857308] area_under_roc_curve 0.7673372781065089 [0.767337,0.767337] area_under_roc_curve 0.7967455621301776 [0.796746,0.796746] area_under_roc_curve 0.8521005917159763 [0.852101,0.852101] 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 0.7807659876625392 [0.781609,0.779923] f_measure 0.7846026392094209 [0.782946,0.78626] f_measure 0.7495517123845937 [0.738956,0.760148] f_measure 0.7652978172401036 [0.760784,0.769811] f_measure 0.7422733795919575 [0.745247,0.7393] f_measure 0.7461388247825315 [0.744186,0.748092] f_measure 0.8153736907509319 [0.813953,0.816794] f_measure 0.6834164884770729 [0.702899,0.663934] f_measure 0.740924166034593 [0.759857,0.721992] f_measure 0.7614820075757577 [0.765152,0.757813] kappa 0.5615384615384615 kappa 0.5692307692307692 kappa 0.5 kappa 0.5307692307692307 kappa 0.48461538461538467 kappa 0.49230769230769234 kappa 0.6307692307692307 kappa 0.36923076923076925 kappa 0.48461538461538467 kappa 0.523076923076923 kb_relative_information_score 136.68791004886648 kb_relative_information_score 126.63984442392584 kb_relative_information_score 124.47798419951044 kb_relative_information_score 133.88347283826698 kb_relative_information_score 125.76190427927455 kb_relative_information_score 121.86812836101521 kb_relative_information_score 140.50383671468373 kb_relative_information_score 92.1567412247606 kb_relative_information_score 111.38232822333026 kb_relative_information_score 132.96396252264253 mean_absolute_error 0.23991967943737702 mean_absolute_error 0.2632418834965033 mean_absolute_error 0.26392191672564297 mean_absolute_error 0.24631807000850214 mean_absolute_error 0.261526812709691 mean_absolute_error 0.2681497085944705 mean_absolute_error 0.23594799304565672 mean_absolute_error 0.32564333524248434 mean_absolute_error 0.28983122224806407 mean_absolute_error 0.2468441376607095 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 0.7807858453162909 [0.778626,0.782946] precision 0.7846827651515151 [0.789062,0.780303] precision 0.7518028487990941 [0.773109,0.730496] precision 0.7657777777777778 [0.776,0.755556] precision 0.742436800663075 [0.736842,0.748031] precision 0.7462121212121211 [0.75,0.742424] precision 0.8154592803030303 [0.820312,0.810606] precision 0.6874549387166546 [0.664384,0.710526] precision 0.7475965898784691 [0.711409,0.783784] precision 0.761786306562426 [0.753731,0.769841] predictive_accuracy 0.7807692307692308 predictive_accuracy 0.7846153846153847 predictive_accuracy 0.75 predictive_accuracy 0.7653846153846153 predictive_accuracy 0.7423076923076922 predictive_accuracy 0.7461538461538462 predictive_accuracy 0.8153846153846154 predictive_accuracy 0.6846153846153846 predictive_accuracy 0.7423076923076922 predictive_accuracy 0.7615384615384616 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 0.7807692307692308 [0.784615,0.776923] recall 0.7846153846153846 [0.776923,0.792308] recall 0.75 [0.707692,0.792308] recall 0.7653846153846153 [0.746154,0.784615] recall 0.7423076923076923 [0.753846,0.730769] recall 0.7461538461538462 [0.738462,0.753846] recall 0.8153846153846154 [0.807692,0.823077] recall 0.6846153846153846 [0.746154,0.623077] recall 0.7423076923076923 [0.815385,0.669231] recall 0.7615384615384615 [0.776923,0.746154] relative_absolute_error 0.47983935887475404 relative_absolute_error 0.5264837669930066 relative_absolute_error 0.5278438334512859 relative_absolute_error 0.49263614001700434 relative_absolute_error 0.523053625419382 relative_absolute_error 0.536299417188941 relative_absolute_error 0.47189598609131345 relative_absolute_error 0.6512866704849687 relative_absolute_error 0.5796624444961281 relative_absolute_error 0.493688275321419 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 0.3958162808923427 root_mean_squared_error 0.42269963870676347 root_mean_squared_error 0.42446343870418624 root_mean_squared_error 0.40534194501953746 root_mean_squared_error 0.4157187039533587 root_mean_squared_error 0.4405869786412623 root_mean_squared_error 0.3923048369602668 root_mean_squared_error 0.47124268993389934 root_mean_squared_error 0.45282433484874496 root_mean_squared_error 0.4093452256529485 root_relative_squared_error 0.7916325617846854 root_relative_squared_error 0.8453992774135269 root_relative_squared_error 0.8489268774083725 root_relative_squared_error 0.8106838900390749 root_relative_squared_error 0.8314374079067174 root_relative_squared_error 0.8811739572825246 root_relative_squared_error 0.7846096739205336 root_relative_squared_error 0.9424853798677987 root_relative_squared_error 0.9056486696974899 root_relative_squared_error 0.818690451305897 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 902.4750019998464 usercpu_time_millis 843.2080009988567 usercpu_time_millis 846.3550360011141 usercpu_time_millis 773.6249090012279 usercpu_time_millis 732.3144089987181 usercpu_time_millis 750.8081610012596 usercpu_time_millis 775.8749050008191 usercpu_time_millis 790.0334330006444 usercpu_time_millis 776.4758350022021 usercpu_time_millis 789.9554560008255 usercpu_time_millis_testing 5.660511000314727 usercpu_time_millis_testing 5.723591999412747 usercpu_time_millis_testing 5.3661250003642635 usercpu_time_millis_testing 5.688317000021925 usercpu_time_millis_testing 5.023245999836945 usercpu_time_millis_testing 5.041086000346695 usercpu_time_millis_testing 5.027385001085349 usercpu_time_millis_testing 5.057458000010229 usercpu_time_millis_testing 5.416645000877907 usercpu_time_millis_testing 5.099993000840186 usercpu_time_millis_training 896.8144909995317 usercpu_time_millis_training 837.484408999444 usercpu_time_millis_training 840.9889110007498 usercpu_time_millis_training 767.936592001206 usercpu_time_millis_training 727.2911629988812 usercpu_time_millis_training 745.7670750009129 usercpu_time_millis_training 770.8475199997338 usercpu_time_millis_training 784.9759750006342 usercpu_time_millis_training 771.0591900013242 usercpu_time_millis_training 784.8554629999853