10576201 28997 Marc Boel 16 Supervised Classification 19037 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(1) 8292483 Python_3.8.10. Sklearn_0.24.2. NumPy_1.17.4. SciPy_1.3.3. add_indicator false 18819 copy true 18819 fill_value null 18819 missing_values NaN 18819 strategy "median" 18819 verbose 0 18819 n_jobs null 18996 remainder "drop" 18996 sparse_threshold 0.3 18996 transformer_weights null 18996 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}] 18996 verbose false 18996 categories "auto" 18997 drop null 18997 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 18997 handle_unknown "ignore" 18997 sparse true 18997 memory null 19037 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 19037 verbose false 19037 ccp_alpha 0.0 19038 criterion "friedman_mse" 19038 init null 19038 learning_rate 0.8242446628205421 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 748 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 173 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 19 19038 random_state 62813 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.025996571702342 19038 verbose 0 19038 warm_start false 19038 openml-python Sklearn_0.24.2. 16 mfeat-karhunen https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff -1 22078669 description https://api.openml.org/data/download/22078669/description.xml -1 22078670 predictions https://api.openml.org/data/download/22078670/predictions.arff area_under_roc_curve 0.9979025 [0.998853,0.998056,0.999819,0.996761,0.998475,0.995744,0.998258,0.997411,0.997989,0.997658] average_cost 0 f_measure 0.9585133688574824 [0.972431,0.945813,0.98,0.940299,0.97,0.931646,0.969697,0.97,0.955,0.950249] kappa 0.9538888888888889 kb_relative_information_score 0.9577516206515169 mean_absolute_error 0.008829021614701511 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.9585 [0.97,0.96,0.98,0.945,0.97,0.92,0.96,0.97,0.955,0.955] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9586282905947072 [0.974874,0.932039,0.98,0.935644,0.97,0.94359,0.979592,0.97,0.955,0.945545] predictive_accuracy 0.9584999999999999 prior_entropy 3.3219280948872383 relative_absolute_error 0.04905012008167355 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.08568944100811521 root_relative_squared_error 0.2856314700270463 total_cost 0 unweighted_recall 0.9584999999999999 [0.97,0.96,0.98,0.945,0.97,0.92,0.96,0.97,0.955,0.955] area_under_roc_curve 0.998388888888889 [0.998333,0.999167,1,1,1,0.9925,0.998889,1,0.995,1] area_under_roc_curve 0.9987777777777778 [1,0.998056,1,0.995833,1,0.996111,0.999722,0.999167,1,0.998889] area_under_roc_curve 0.99725 [0.999722,0.995833,1,1,1,0.996667,1,0.985833,0.999444,0.995] area_under_roc_curve 0.9987777777777777 [1,0.999444,1,0.995278,0.997222,0.996944,1,1,0.999444,0.999444] area_under_roc_curve 0.9980833333333333 [0.999722,1,0.999444,0.989444,1,0.993889,1,1,0.999444,0.998889] area_under_roc_curve 0.9987222222222222 [1,0.999167,1,0.999722,0.998056,0.995,1,1,0.998333,0.996944] area_under_roc_curve 0.9990000000000001 [0.9975,0.998889,0.999722,1,1,0.999167,1,1,0.998056,0.996667] area_under_roc_curve 0.9988611111111112 [1,1,1,1,0.998611,0.996944,0.996944,1,0.996944,0.999167] area_under_roc_curve 0.9989444444444444 [0.999444,1,0.999722,0.993333,0.999444,0.998333,0.999167,1,1,1] area_under_roc_curve 0.9975277777777779 [0.999722,0.999444,1,0.999444,0.994444,0.999722,0.986667,0.999167,0.9975,0.999167] 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 0.9699785580273386 [0.974359,0.923077,1,1,0.97561,0.95,0.974359,1,0.95,0.952381] f_measure 0.9549812382739212 [1,0.95,1,0.871795,0.974359,0.878049,0.97561,0.95,1,0.95] f_measure 0.9600386601785235 [0.95,0.947368,0.97561,0.947368,1,0.926829,1,0.947368,0.97561,0.930233] f_measure 0.9653246942129527 [0.974359,0.930233,0.97561,0.974359,0.974359,0.95,0.97561,0.974359,0.95,0.974359] f_measure 0.9500762395499236 [0.952381,0.909091,0.947368,0.894737,0.947368,0.923077,1,1,0.974359,0.952381] f_measure 0.9550364736615744 [0.97561,0.97561,0.974359,0.974359,0.95,0.923077,0.947368,0.930233,0.952381,0.947368] f_measure 0.9598097870049089 [0.974359,0.95,0.95,1,0.97561,0.95,1,0.952381,0.926829,0.918919] f_measure 0.9594449307016103 [0.97561,0.952381,1,0.930233,0.97561,0.947368,0.974359,1,0.888889,0.95] f_measure 0.9652754207609866 [0.974359,0.974359,0.97561,0.883721,0.97561,0.894737,0.974359,1,1,1] f_measure 0.9451772336290353 [0.974359,0.95,1,0.930233,0.95,0.974359,0.871795,0.947368,0.926829,0.926829] kappa 0.9666666666666667 kappa 0.95 kappa 0.9555555555555555 kappa 0.961111111111111 kappa 0.9444444444444444 kappa 0.95 kappa 0.9555555555555555 kappa 0.9555555555555555 kappa 0.961111111111111 kappa 0.9388888888888889 kb_relative_information_score 0.965545993465831 kb_relative_information_score 0.9535542393140715 kb_relative_information_score 0.9621662891544469 kb_relative_information_score 0.9667501590304337 kb_relative_information_score 0.9515072273206665 kb_relative_information_score 0.9499821356564065 kb_relative_information_score 0.957064289635003 kb_relative_information_score 0.9644951224550637 kb_relative_information_score 0.9628041668297554 kb_relative_information_score 0.9436465836531324 mean_absolute_error 0.007117084850981916 mean_absolute_error 0.009510297302295788 mean_absolute_error 0.007791193099913147 mean_absolute_error 0.006888809315453749 mean_absolute_error 0.010215022115501652 mean_absolute_error 0.010276619893616022 mean_absolute_error 0.008405119153684195 mean_absolute_error 0.007874674008648686 mean_absolute_error 0.008462356392955455 mean_absolute_error 0.011749040013964348 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.9708840282524495 [1,0.947368,1,1,0.952381,0.95,1,1,0.95,0.909091] precision 0.9554260651629072 [1,0.95,1,0.894737,1,0.857143,0.952381,0.95,1,0.95] precision 0.9629089026915113 [0.95,1,0.952381,1,1,0.904762,1,1,0.952381,0.869565] precision 0.9674327122153208 [1,0.869565,0.952381,1,1,0.95,0.952381,1,0.95,1] precision 0.9543328017012227 [0.909091,0.833333,1,0.944444,1,0.947368,1,1,1,0.909091] precision 0.958078645229675 [0.952381,0.952381,1,1,0.95,0.947368,1,0.869565,0.909091,1] precision 0.9616233766233766 [1,0.95,0.95,1,0.952381,0.95,1,0.909091,0.904762,1] precision 0.9633418031244119 [0.952381,0.909091,1,0.869565,0.952381,1,1,1,1,0.95] precision 0.9675293305728089 [1,1,0.952381,0.826087,0.952381,0.944444,1,1,1,1] precision 0.9473825869020378 [1,0.95,1,0.869565,0.95,1,0.894737,1,0.904762,0.904762] predictive_accuracy 0.97 predictive_accuracy 0.955 predictive_accuracy 0.96 predictive_accuracy 0.965 predictive_accuracy 0.95 predictive_accuracy 0.955 predictive_accuracy 0.96 predictive_accuracy 0.96 predictive_accuracy 0.965 predictive_accuracy 0.945 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 relative_absolute_error 0.03953936028323291 relative_absolute_error 0.05283498501275444 relative_absolute_error 0.04328440611062865 relative_absolute_error 0.03827116286363198 relative_absolute_error 0.05675012286389814 relative_absolute_error 0.0570923327423113 relative_absolute_error 0.04669510640935669 relative_absolute_error 0.043748188936937195 relative_absolute_error 0.0470130910719748 relative_absolute_error 0.06527244452202423 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.07542005963601604 root_mean_squared_error 0.09026930785305068 root_mean_squared_error 0.08295725556227827 root_mean_squared_error 0.0722599695440402 root_mean_squared_error 0.09320622540983207 root_mean_squared_error 0.0950354553907492 root_mean_squared_error 0.08774011757086932 root_mean_squared_error 0.07517969066098233 root_mean_squared_error 0.07963797690090105 root_mean_squared_error 0.10037430197793584 root_relative_squared_error 0.25140019878672026 root_relative_squared_error 0.30089769284350243 root_relative_squared_error 0.2765241852075944 root_relative_squared_error 0.2408665651468008 root_relative_squared_error 0.3106874180327738 root_relative_squared_error 0.31678485130249756 root_relative_squared_error 0.29246705856956456 root_relative_squared_error 0.25059896886994126 root_relative_squared_error 0.26545992300300364 root_relative_squared_error 0.3345810065931197 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 unweighted_recall 0.97 [0.95,0.9,1,1,1,0.95,0.95,1,0.95,1] unweighted_recall 0.9550000000000001 [1,0.95,1,0.85,0.95,0.9,1,0.95,1,0.95] unweighted_recall 0.9600000000000002 [0.95,0.9,1,0.9,1,0.95,1,0.9,1,1] unweighted_recall 0.9650000000000001 [0.95,1,1,0.95,0.95,0.95,1,0.95,0.95,0.95] unweighted_recall 0.95 [1,1,0.9,0.85,0.9,0.9,1,1,0.95,1] unweighted_recall 0.9550000000000003 [1,1,0.95,0.95,0.95,0.9,0.9,1,1,0.9] unweighted_recall 0.96 [0.95,0.95,0.95,1,1,0.95,1,1,0.95,0.85] unweighted_recall 0.96 [1,1,1,1,1,0.9,0.95,1,0.8,0.95] unweighted_recall 0.9649999999999999 [0.95,0.95,1,0.95,1,0.85,0.95,1,1,1] unweighted_recall 0.945 [0.95,0.95,1,1,0.95,0.95,0.85,0.9,0.95,0.95] usercpu_time_millis 20629.80985700051 usercpu_time_millis 20706.653059000928 usercpu_time_millis 17284.650915000384 usercpu_time_millis 16521.20840599946 usercpu_time_millis 16807.939309000176 usercpu_time_millis 17767.583215999366 usercpu_time_millis 16551.55849499988 usercpu_time_millis 11018.453038999724 usercpu_time_millis 8236.174804000257 usercpu_time_millis 13314.163662999817 usercpu_time_millis_testing 4.250799999681476 usercpu_time_millis_testing 4.334400000516325 usercpu_time_millis_testing 3.8561000001209322 usercpu_time_millis_testing 4.440800999873318 usercpu_time_millis_testing 3.958700000112003 usercpu_time_millis_testing 4.265399999894726 usercpu_time_millis_testing 4.039800000100513 usercpu_time_millis_testing 3.9465010004278156 usercpu_time_millis_testing 3.645001000222692 usercpu_time_millis_testing 3.4967999999935273 usercpu_time_millis_training 20625.559057000828 usercpu_time_millis_training 20702.31865900041 usercpu_time_millis_training 17280.794815000263 usercpu_time_millis_training 16516.767604999586 usercpu_time_millis_training 16803.980609000064 usercpu_time_millis_training 17763.31781599947 usercpu_time_millis_training 16547.51869499978 usercpu_time_millis_training 11014.506537999296 usercpu_time_millis_training 8232.529803000034 usercpu_time_millis_training 13310.666862999824 wall_clock_time_millis 20645.529985427856 wall_clock_time_millis 20727.927446365356 wall_clock_time_millis 17297.741651535034 wall_clock_time_millis 16528.145790100098 wall_clock_time_millis 16814.929485321045 wall_clock_time_millis 17771.379470825195 wall_clock_time_millis 16601.584672927856 wall_clock_time_millis 11047.981977462769 wall_clock_time_millis 8239.75133895874 wall_clock_time_millis 13327.873706817627 wall_clock_time_millis_testing 4.253864288330078 wall_clock_time_millis_testing 4.337072372436523 wall_clock_time_millis_testing 3.8597583770751953 wall_clock_time_millis_testing 4.446744918823242 wall_clock_time_millis_testing 3.9620399475097656 wall_clock_time_millis_testing 4.268884658813477 wall_clock_time_millis_testing 4.043817520141602 wall_clock_time_millis_testing 3.9505958557128906 wall_clock_time_millis_testing 3.6492347717285156 wall_clock_time_millis_testing 3.503561019897461 wall_clock_time_millis_training 20641.276121139526 wall_clock_time_millis_training 20723.59037399292 wall_clock_time_millis_training 17293.88189315796 wall_clock_time_millis_training 16523.699045181274 wall_clock_time_millis_training 16810.967445373535 wall_clock_time_millis_training 17767.110586166382 wall_clock_time_millis_training 16597.540855407715 wall_clock_time_millis_training 11044.031381607056 wall_clock_time_millis_training 8236.102104187012 wall_clock_time_millis_training 13324.37014579773 weighted_recall 0.97 [0.95,0.9,1,1,1,0.95,0.95,1,0.95,1] weighted_recall 0.955 [1,0.95,1,0.85,0.95,0.9,1,0.95,1,0.95] weighted_recall 0.96 [0.95,0.9,1,0.9,1,0.95,1,0.9,1,1] weighted_recall 0.965 [0.95,1,1,0.95,0.95,0.95,1,0.95,0.95,0.95] weighted_recall 0.95 [1,1,0.9,0.85,0.9,0.9,1,1,0.95,1] weighted_recall 0.955 [1,1,0.95,0.95,0.95,0.9,0.9,1,1,0.9] weighted_recall 0.96 [0.95,0.95,0.95,1,1,0.95,1,1,0.95,0.85] weighted_recall 0.96 [1,1,1,1,1,0.9,0.95,1,0.8,0.95] weighted_recall 0.965 [0.95,0.95,1,0.95,1,0.85,0.95,1,1,1] weighted_recall 0.945 [0.95,0.95,1,1,0.95,0.95,0.85,0.9,0.95,0.95]