10576461 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) 8292743 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 "most_frequent" 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 0.670485691026719 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 19 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 117 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 11 19038 random_state 25836 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.1702918585002705 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 22079189 description https://api.openml.org/data/download/22079189/description.xml -1 22079190 predictions https://api.openml.org/data/download/22079190/predictions.arff area_under_roc_curve 0.9977658333333334 [0.999347,0.997453,0.999669,0.995939,0.996761,0.996314,0.996881,0.999236,0.998197,0.997861] average_cost 0 f_measure 0.9520531510693372 [0.982544,0.923457,0.982278,0.935323,0.962779,0.912281,0.959184,0.967901,0.952141,0.942643] kappa 0.9466666666666667 kb_relative_information_score 0.9492142408451437 mean_absolute_error 0.011242481745344179 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.952 [0.985,0.935,0.97,0.94,0.97,0.91,0.94,0.98,0.945,0.945] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9523050975618783 [0.9801,0.912195,0.994872,0.930693,0.955665,0.914573,0.979167,0.956098,0.959391,0.940299] predictive_accuracy 0.9520000000000001 prior_entropy 3.3219280948872383 relative_absolute_error 0.06245823191857685 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.08933282377504116 root_relative_squared_error 0.29777607925013266 total_cost 0 unweighted_recall 0.9520000000000002 [0.985,0.935,0.97,0.94,0.97,0.91,0.94,0.98,0.945,0.945] area_under_roc_curve 0.998 [0.9975,0.996389,1,0.999444,1,0.991111,0.999444,1,0.996111,1] area_under_roc_curve 0.998638888888889 [1,0.996389,1,0.996111,1,0.996389,0.999167,0.998889,1,0.999444] area_under_roc_curve 0.9987222222222223 [1,0.9975,1,0.998889,1,0.9975,1,0.995833,1,0.9975] area_under_roc_curve 0.9983888888888889 [1,0.998056,1,0.991111,0.9975,0.999167,1,0.999722,1,0.998333] area_under_roc_curve 0.9951111111111112 [1,0.993611,0.999444,0.987778,0.985833,0.989444,0.999444,0.999722,0.998889,0.996944] area_under_roc_curve 0.9969166666666667 [1,0.998056,1,1,0.985556,0.995278,0.997222,1,0.9975,0.995556] area_under_roc_curve 0.9989166666666667 [0.998056,0.998333,0.998056,0.999444,1,0.998333,1,1,0.998611,0.998333] area_under_roc_curve 0.9986666666666667 [1,0.998611,0.999444,0.998889,0.999167,0.998333,0.998889,1,0.993333,1] area_under_roc_curve 0.9985 [1,1,1,0.989722,1,0.996389,0.999167,1,1,0.999722] area_under_roc_curve 0.9972222222222222 [1,0.998611,1,0.999722,1,0.999167,0.979722,0.999167,0.998333,0.9975] 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 0.9549521082255354 [0.974359,0.878049,1,0.974359,0.97561,0.926829,0.974359,0.97561,0.894737,0.97561] f_measure 0.9551031894934334 [1,0.923077,1,0.923077,1,0.878049,0.95,0.926829,1,0.95] f_measure 0.9602118175802388 [1,0.918919,1,0.947368,0.952381,0.9,1,0.974359,1,0.909091] f_measure 0.9601875232170481 [0.974359,0.904762,0.97561,0.947368,0.974359,0.926829,1,0.97561,0.97561,0.947368] f_measure 0.9202701641533476 [0.952381,0.857143,0.947368,0.85,0.947368,0.871795,0.926829,0.952381,0.974359,0.923077] f_measure 0.9498004061418694 [0.97561,0.95,0.974359,1,0.926829,0.926829,0.918919,0.952381,0.95,0.923077] f_measure 0.9550447552886577 [0.974359,0.95,0.974359,0.95,0.97561,0.926829,1,0.97561,0.904762,0.918919] f_measure 0.954780478400504 [1,0.926829,0.947368,0.952381,0.952381,0.947368,0.974359,1,0.894737,0.952381] f_measure 0.9698462855073895 [0.97561,1,1,0.926829,0.97561,0.923077,0.947368,1,0.974359,0.97561] f_measure 0.9403331973344212 [1,0.930233,1,0.888889,0.947368,0.894737,0.894737,0.947368,0.95,0.95] kappa 0.95 kappa 0.95 kappa 0.9555555555555555 kappa 0.9555555555555555 kappa 0.9111111111111112 kappa 0.9444444444444444 kappa 0.95 kappa 0.95 kappa 0.9666666666666667 kappa 0.9333333333333332 kb_relative_information_score 0.9466312206732167 kb_relative_information_score 0.949841951950108 kb_relative_information_score 0.9579117509031602 kb_relative_information_score 0.958301157358337 kb_relative_information_score 0.9188854768975737 kb_relative_information_score 0.9453699501016914 kb_relative_information_score 0.953043811168798 kb_relative_information_score 0.9499846826720253 kb_relative_information_score 0.9679778551816658 kb_relative_information_score 0.9441945515445264 mean_absolute_error 0.011907968670867224 mean_absolute_error 0.010320130373079628 mean_absolute_error 0.00960348470330515 mean_absolute_error 0.009145495966192766 mean_absolute_error 0.018565581418628976 mean_absolute_error 0.012395251349455925 mean_absolute_error 0.009886817258170913 mean_absolute_error 0.01139455414477229 mean_absolute_error 0.007165558255949416 mean_absolute_error 0.01203997531301993 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 0.9563492063492062 [1,0.857143,1,1,0.952381,0.904762,1,0.952381,0.944444,0.952381] precision 0.9556641604010025 [1,0.947368,1,0.947368,1,0.857143,0.95,0.904762,1,0.95] precision 0.9642424242424242 [1,1,1,1,0.909091,0.9,1,1,1,0.833333] precision 0.9625541125541125 [1,0.863636,0.952381,1,1,0.904762,1,0.952381,0.952381,1] precision 0.9233230804283435 [0.909091,0.818182,1,0.85,1,0.894737,0.904762,0.909091,1,0.947368] precision 0.9518364092048303 [0.952381,0.95,1,1,0.904762,0.904762,1,0.909091,0.95,0.947368] precision 0.9573160173160172 [1,0.95,1,0.95,0.952381,0.904762,1,0.952381,0.863636,1] precision 0.9576479076479076 [1,0.904762,1,0.909091,0.909091,1,1,1,0.944444,0.909091] precision 0.9709273182957392 [0.952381,1,1,0.904762,0.952381,0.947368,1,1,1,0.952381] precision 0.9458454106280193 [1,0.869565,1,0.8,1,0.944444,0.944444,1,0.95,0.95] predictive_accuracy 0.955 predictive_accuracy 0.955 predictive_accuracy 0.96 predictive_accuracy 0.96 predictive_accuracy 0.92 predictive_accuracy 0.95 predictive_accuracy 0.955 predictive_accuracy 0.955 predictive_accuracy 0.97 predictive_accuracy 0.94 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 0.06615538150481798 relative_absolute_error 0.05733405762822022 relative_absolute_error 0.05335269279613977 relative_absolute_error 0.0508083109232932 relative_absolute_error 0.10314211899238332 relative_absolute_error 0.06886250749697743 relative_absolute_error 0.054926762545394026 relative_absolute_error 0.06330307858206835 relative_absolute_error 0.0398086569774968 relative_absolute_error 0.06688875173899969 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 0.0891555138223396 root_mean_squared_error 0.08771149389357397 root_mean_squared_error 0.08161479870416413 root_mean_squared_error 0.08165880906069715 root_mean_squared_error 0.10876964812394263 root_mean_squared_error 0.09466641226960495 root_mean_squared_error 0.08484131437836336 root_mean_squared_error 0.08884118503044504 root_mean_squared_error 0.07336172117963836 root_mean_squared_error 0.09781141489120314 root_relative_squared_error 0.29718504607446555 root_relative_squared_error 0.2923716463119134 root_relative_squared_error 0.27204932901388057 root_relative_squared_error 0.27219603020232397 root_relative_squared_error 0.3625654937464756 root_relative_squared_error 0.31555470756535003 root_relative_squared_error 0.2828043812612114 root_relative_squared_error 0.296137283434817 root_relative_squared_error 0.2445390705987947 root_relative_squared_error 0.32603804963734395 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 0.9550000000000001 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1] unweighted_recall 0.9550000000000001 [1,0.9,1,0.9,1,0.9,0.95,0.95,1,0.95] unweighted_recall 0.9600000000000002 [1,0.85,1,0.9,1,0.9,1,0.95,1,1] unweighted_recall 0.96 [0.95,0.95,1,0.9,0.95,0.95,1,1,1,0.9] unweighted_recall 0.9199999999999999 [1,0.9,0.9,0.85,0.9,0.85,0.95,1,0.95,0.9] unweighted_recall 0.95 [1,0.95,0.95,1,0.95,0.95,0.85,1,0.95,0.9] unweighted_recall 0.9549999999999998 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85] unweighted_recall 0.9550000000000001 [1,0.95,0.9,1,1,0.9,0.95,1,0.85,1] unweighted_recall 0.9700000000000001 [1,1,1,0.95,1,0.9,0.9,1,0.95,1] unweighted_recall 0.9399999999999998 [1,1,1,1,0.9,0.85,0.85,0.9,0.95,0.95] usercpu_time_millis 7048.855287000151 usercpu_time_millis 5904.632373999448 usercpu_time_millis 7010.590791000141 usercpu_time_millis 7645.189594999465 usercpu_time_millis 6107.012374000078 usercpu_time_millis 7636.952495000514 usercpu_time_millis 7625.694089999342 usercpu_time_millis 8002.38179400003 usercpu_time_millis 7003.635084000052 usercpu_time_millis 6840.498884999761 usercpu_time_millis_testing 3.1018999998195795 usercpu_time_millis_testing 3.579100000024482 usercpu_time_millis_testing 2.919399999882444 usercpu_time_millis_testing 3.276899999946181 usercpu_time_millis_testing 3.5649999999805004 usercpu_time_millis_testing 3.1294999998863204 usercpu_time_millis_testing 3.7930999997115578 usercpu_time_millis_testing 2.884999999878346 usercpu_time_millis_testing 3.605500000048778 usercpu_time_millis_testing 3.5471000001052744 usercpu_time_millis_training 7045.753387000332 usercpu_time_millis_training 5901.053273999423 usercpu_time_millis_training 7007.671391000258 usercpu_time_millis_training 7641.912694999519 usercpu_time_millis_training 6103.447374000098 usercpu_time_millis_training 7633.822995000628 usercpu_time_millis_training 7621.900989999631 usercpu_time_millis_training 7999.496794000152 usercpu_time_millis_training 7000.0295840000035 usercpu_time_millis_training 6836.9517849996555 wall_clock_time_millis 7057.488441467285 wall_clock_time_millis 5905.267238616943 wall_clock_time_millis 7013.207912445068 wall_clock_time_millis 7655.723333358765 wall_clock_time_millis 6115.411043167114 wall_clock_time_millis 7637.702226638794 wall_clock_time_millis 7638.560771942139 wall_clock_time_millis 8037.270545959473 wall_clock_time_millis 7008.188247680664 wall_clock_time_millis 6843.835830688477 wall_clock_time_millis_testing 3.1049251556396484 wall_clock_time_millis_testing 3.584146499633789 wall_clock_time_millis_testing 2.923250198364258 wall_clock_time_millis_testing 3.2792091369628906 wall_clock_time_millis_testing 3.569364547729492 wall_clock_time_millis_testing 3.135204315185547 wall_clock_time_millis_testing 3.7963390350341797 wall_clock_time_millis_testing 2.8886795043945312 wall_clock_time_millis_testing 3.6118030548095703 wall_clock_time_millis_testing 3.5512447357177734 wall_clock_time_millis_training 7054.3835163116455 wall_clock_time_millis_training 5901.68309211731 wall_clock_time_millis_training 7010.284662246704 wall_clock_time_millis_training 7652.444124221802 wall_clock_time_millis_training 6111.841678619385 wall_clock_time_millis_training 7634.567022323608 wall_clock_time_millis_training 7634.7644329071045 wall_clock_time_millis_training 8034.381866455078 wall_clock_time_millis_training 7004.5764446258545 wall_clock_time_millis_training 6840.284585952759 weighted_recall 0.955 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1] weighted_recall 0.955 [1,0.9,1,0.9,1,0.9,0.95,0.95,1,0.95] weighted_recall 0.96 [1,0.85,1,0.9,1,0.9,1,0.95,1,1] weighted_recall 0.96 [0.95,0.95,1,0.9,0.95,0.95,1,1,1,0.9] weighted_recall 0.92 [1,0.9,0.9,0.85,0.9,0.85,0.95,1,0.95,0.9] weighted_recall 0.95 [1,0.95,0.95,1,0.95,0.95,0.85,1,0.95,0.9] weighted_recall 0.955 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85] weighted_recall 0.955 [1,0.95,0.9,1,1,0.9,0.95,1,0.85,1] weighted_recall 0.97 [1,1,1,0.95,1,0.9,0.9,1,0.95,1] weighted_recall 0.94 [1,1,1,1,0.9,0.85,0.85,0.9,0.95,0.95]