10576538 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) 8292820 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 0.6700200803375781 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 1026 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 94 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 14 19038 random_state 45180 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.34720605076359207 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 22079343 description https://api.openml.org/data/download/22079343/description.xml -1 22079344 predictions https://api.openml.org/data/download/22079344/predictions.arff area_under_roc_curve 0.9971008333333333 [0.998333,0.995578,0.999511,0.996544,0.9969,0.995761,0.997547,0.997711,0.996431,0.996692] average_cost 0 f_measure 0.9470547509053177 [0.958231,0.933333,0.984925,0.942065,0.950495,0.905941,0.954082,0.965,0.941476,0.935] kappa 0.941111111111111 kb_relative_information_score 0.9440652196747815 mean_absolute_error 0.012736926113880685 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.947 [0.975,0.945,0.98,0.935,0.96,0.915,0.935,0.965,0.925,0.935] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9473860623847543 [0.942029,0.921951,0.989899,0.949239,0.941176,0.897059,0.973958,0.965,0.958549,0.935] predictive_accuracy 0.9470000000000001 prior_entropy 3.3219280948872383 relative_absolute_error 0.07076070063266829 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.09381146154420977 root_relative_squared_error 0.31270487181402773 total_cost 0 unweighted_recall 0.9470000000000001 [0.975,0.945,0.98,0.935,0.96,0.915,0.935,0.965,0.925,0.935] area_under_roc_curve 0.9954999999999998 [0.988333,0.995556,1,0.999167,1,0.989444,0.998333,0.999444,0.985,0.999722] area_under_roc_curve 0.9985833333333335 [1,0.995556,1,0.998056,1,0.995556,0.998889,0.998611,1,0.999167] area_under_roc_curve 0.9966944444444443 [0.999722,0.988611,1,1,1,0.996667,1,0.985833,0.999444,0.996667] area_under_roc_curve 0.9984999999999999 [0.999167,0.998611,1,0.995556,0.994444,0.998056,1,1,0.999444,0.999722] area_under_roc_curve 0.9954722222222222 [1,0.995278,0.994167,0.984444,0.991389,0.9925,0.999167,1,0.998889,0.998889] area_under_roc_curve 0.997 [1,0.9975,1,1,0.995833,0.997222,0.996389,0.996944,0.998889,0.987222] area_under_roc_curve 0.9975 [0.995833,0.998333,0.998611,0.999167,0.998056,0.997778,1,0.999444,0.996111,0.991667] area_under_roc_curve 0.9981111111111108 [1,0.9925,1,1,0.997778,0.998333,0.997222,1,0.995556,0.999722] area_under_roc_curve 0.9985833333333334 [0.999722,1,1,0.991389,1,0.995278,0.999444,1,1,1] area_under_roc_curve 0.9966111111111112 [0.998611,0.999167,1,0.998056,0.993333,0.998333,0.986111,0.998889,0.995556,0.998056] 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 0.9396574596574596 [0.9,0.923077,1,0.974359,0.952381,0.9,0.923077,0.952381,0.918919,0.952381] f_measure 0.9498592870544088 [1,0.9,1,0.9,1,0.871795,0.974359,0.926829,0.97561,0.95] f_measure 0.9653765212109242 [0.97561,0.947368,1,1,0.97561,0.95,0.974359,0.947368,0.974359,0.909091] f_measure 0.9499286112700746 [0.926829,0.9,0.952381,0.95,0.974359,0.926829,1,0.974359,0.97561,0.918919] f_measure 0.9351019570830299 [0.97561,0.883721,0.947368,0.894737,0.894737,0.878049,0.97561,1,0.974359,0.926829] f_measure 0.9391009729841564 [0.952381,0.952381,1,0.974359,0.95,0.926829,0.864865,0.952381,0.923077,0.894737] f_measure 0.9500228195863626 [0.95,0.97561,0.974359,0.947368,0.952381,0.904762,1,0.95,0.926829,0.918919] f_measure 0.9602086906258921 [1,0.95,0.974359,0.952381,0.909091,0.918919,0.974359,1,0.947368,0.97561] f_measure 0.9600995688094532 [0.97561,0.97561,1,0.9,0.974359,0.878049,0.95,1,0.947368,1] f_measure 0.9200431895874772 [0.926829,0.926829,1,0.926829,0.923077,0.904762,0.894737,0.947368,0.85,0.9] kappa 0.9333333333333332 kappa 0.9444444444444444 kappa 0.961111111111111 kappa 0.9444444444444444 kappa 0.9277777777777778 kappa 0.9333333333333332 kappa 0.9444444444444444 kappa 0.9555555555555555 kappa 0.9555555555555555 kappa 0.9111111111111112 kb_relative_information_score 0.9324527096280462 kb_relative_information_score 0.9498493893879085 kb_relative_information_score 0.9561840038342381 kb_relative_information_score 0.9549792865462663 kb_relative_information_score 0.9234253324414636 kb_relative_information_score 0.9408813165051404 kb_relative_information_score 0.9386923296417039 kb_relative_information_score 0.9541804750123533 kb_relative_information_score 0.9652056853875004 kb_relative_information_score 0.9248016683628919 mean_absolute_error 0.015391819381704565 mean_absolute_error 0.010878495333718463 mean_absolute_error 0.010142911715528717 mean_absolute_error 0.01048338137456633 mean_absolute_error 0.018053367867068584 mean_absolute_error 0.013424261521314396 mean_absolute_error 0.014804499420308807 mean_absolute_error 0.009918728752039287 mean_absolute_error 0.00860030412108464 mean_absolute_error 0.015671491651473028 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 0.9422009569377992 [0.9,0.947368,1,1,0.909091,0.9,0.947368,0.909091,1,0.909091] precision 0.950187969924812 [1,0.9,1,0.9,1,0.894737,1,0.904762,0.952381,0.95] precision 0.9688095238095238 [0.952381,1,1,1,0.952381,0.95,1,1,1,0.833333] precision 0.952099567099567 [0.904762,0.9,0.909091,0.95,1,0.904762,1,1,0.952381,1] precision 0.9381642512077295 [0.952381,0.826087,1,0.944444,0.944444,0.857143,0.952381,1,1,0.904762] precision 0.9415023968119942 [0.909091,0.909091,1,1,0.95,0.904762,0.941176,0.909091,0.947368,0.944444] precision 0.952987012987013 [0.95,0.952381,1,1,0.909091,0.863636,1,0.95,0.904762,1] precision 0.9644805194805195 [1,0.95,1,0.909091,0.833333,1,1,1,1,0.952381] precision 0.9611904761904762 [0.952381,0.952381,1,0.9,1,0.857143,0.95,1,1,1] precision 0.9219734943419153 [0.904762,0.904762,1,0.904762,0.947368,0.863636,0.944444,1,0.85,0.9] predictive_accuracy 0.94 predictive_accuracy 0.95 predictive_accuracy 0.965 predictive_accuracy 0.95 predictive_accuracy 0.935 predictive_accuracy 0.94 predictive_accuracy 0.95 predictive_accuracy 0.96 predictive_accuracy 0.96 predictive_accuracy 0.92 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 0.08551010767613658 relative_absolute_error 0.060436085187324864 relative_absolute_error 0.05634950953071516 relative_absolute_error 0.05824100763647968 relative_absolute_error 0.10029648815038113 relative_absolute_error 0.07457923067396895 relative_absolute_error 0.08224721900171568 relative_absolute_error 0.05510404862244054 relative_absolute_error 0.047779467339359165 relative_absolute_error 0.08706384250818358 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 0.10027133059134888 root_mean_squared_error 0.09099886499615349 root_mean_squared_error 0.08168971431516067 root_mean_squared_error 0.08350394653584023 root_mean_squared_error 0.10768145548485146 root_mean_squared_error 0.09749297330497896 root_mean_squared_error 0.09598597795176679 root_mean_squared_error 0.08545936209112548 root_mean_squared_error 0.07480411596121393 root_mean_squared_error 0.113191030975106 root_relative_squared_error 0.33423776863782984 root_relative_squared_error 0.3033295499871785 root_relative_squared_error 0.27229904771720237 root_relative_squared_error 0.2783464884528009 root_relative_squared_error 0.3589381849495051 root_relative_squared_error 0.32497657768326343 root_relative_squared_error 0.31995325983922285 root_relative_squared_error 0.28486454030375175 root_relative_squared_error 0.2493470532040466 root_relative_squared_error 0.3773034365836868 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 0.9400000000000001 [0.9,0.9,1,0.95,1,0.9,0.9,1,0.85,1] unweighted_recall 0.95 [1,0.9,1,0.9,1,0.85,0.95,0.95,1,0.95] unweighted_recall 0.9650000000000001 [1,0.9,1,1,1,0.95,0.95,0.9,0.95,1] unweighted_recall 0.95 [0.95,0.9,1,0.95,0.95,0.95,1,0.95,1,0.85] unweighted_recall 0.9349999999999999 [1,0.95,0.9,0.85,0.85,0.9,1,1,0.95,0.95] unweighted_recall 0.9400000000000001 [1,1,1,0.95,0.95,0.95,0.8,1,0.9,0.85] unweighted_recall 0.95 [0.95,1,0.95,0.9,1,0.95,1,0.95,0.95,0.85] unweighted_recall 0.96 [1,0.95,0.95,1,1,0.85,0.95,1,0.9,1] unweighted_recall 0.96 [1,1,1,0.9,0.95,0.9,0.95,1,0.9,1] unweighted_recall 0.9200000000000002 [0.95,0.95,1,0.95,0.9,0.95,0.85,0.9,0.85,0.9] usercpu_time_millis 4114.334752002833 usercpu_time_millis 4772.937457999433 usercpu_time_millis 4479.532554999423 usercpu_time_millis 4770.227558998158 usercpu_time_millis 3806.5242470001976 usercpu_time_millis 4359.012756000084 usercpu_time_millis 3805.232647999219 usercpu_time_millis 5034.014463000858 usercpu_time_millis 4909.646963000341 usercpu_time_millis 4618.082558001333 usercpu_time_millis_testing 3.439900001467322 usercpu_time_millis_testing 2.619101000163937 usercpu_time_millis_testing 3.1333999995695194 usercpu_time_millis_testing 3.3850999989226693 usercpu_time_millis_testing 3.534699999363511 usercpu_time_millis_testing 3.387099999599741 usercpu_time_millis_testing 3.4297000001970446 usercpu_time_millis_testing 2.678999000636395 usercpu_time_millis_testing 2.7733000006264774 usercpu_time_millis_testing 2.694001001145807 usercpu_time_millis_training 4110.8948520013655 usercpu_time_millis_training 4770.318356999269 usercpu_time_millis_training 4476.399154999854 usercpu_time_millis_training 4766.8424589992355 usercpu_time_millis_training 3802.989547000834 usercpu_time_millis_training 4355.625656000484 usercpu_time_millis_training 3801.802947999022 usercpu_time_millis_training 5031.335464000222 usercpu_time_millis_training 4906.873662999715 usercpu_time_millis_training 4615.388557000188 wall_clock_time_millis 4117.8107261657715 wall_clock_time_millis 4790.0073528289795 wall_clock_time_millis 4481.820344924927 wall_clock_time_millis 4788.896799087524 wall_clock_time_millis 3813.1957054138184 wall_clock_time_millis 4366.838455200195 wall_clock_time_millis 3812.3040199279785 wall_clock_time_millis 5037.172555923462 wall_clock_time_millis 4913.449048995972 wall_clock_time_millis 4623.697519302368 wall_clock_time_millis_testing 3.4422874450683594 wall_clock_time_millis_testing 2.622842788696289 wall_clock_time_millis_testing 3.136873245239258 wall_clock_time_millis_testing 3.389120101928711 wall_clock_time_millis_testing 3.5386085510253906 wall_clock_time_millis_testing 3.3922195434570312 wall_clock_time_millis_testing 3.433704376220703 wall_clock_time_millis_testing 2.682209014892578 wall_clock_time_millis_testing 2.775430679321289 wall_clock_time_millis_testing 2.6977062225341797 wall_clock_time_millis_training 4114.368438720703 wall_clock_time_millis_training 4787.384510040283 wall_clock_time_millis_training 4478.6834716796875 wall_clock_time_millis_training 4785.507678985596 wall_clock_time_millis_training 3809.657096862793 wall_clock_time_millis_training 4363.446235656738 wall_clock_time_millis_training 3808.870315551758 wall_clock_time_millis_training 5034.490346908569 wall_clock_time_millis_training 4910.67361831665 wall_clock_time_millis_training 4620.999813079834 weighted_recall 0.94 [0.9,0.9,1,0.95,1,0.9,0.9,1,0.85,1] weighted_recall 0.95 [1,0.9,1,0.9,1,0.85,0.95,0.95,1,0.95] weighted_recall 0.965 [1,0.9,1,1,1,0.95,0.95,0.9,0.95,1] weighted_recall 0.95 [0.95,0.9,1,0.95,0.95,0.95,1,0.95,1,0.85] weighted_recall 0.935 [1,0.95,0.9,0.85,0.85,0.9,1,1,0.95,0.95] weighted_recall 0.94 [1,1,1,0.95,0.95,0.95,0.8,1,0.9,0.85] weighted_recall 0.95 [0.95,1,0.95,0.9,1,0.95,1,0.95,0.95,0.85] weighted_recall 0.96 [1,0.95,0.95,1,1,0.85,0.95,1,0.9,1] weighted_recall 0.96 [1,1,1,0.9,0.95,0.9,0.95,1,0.9,1] weighted_recall 0.92 [0.95,0.95,1,0.95,0.9,0.95,0.85,0.9,0.85,0.9]