10576160 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) 8292442 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 0.689627483734651 19038 loss "deviance" 19038 max_depth 3 19038 max_features null 19038 max_leaf_nodes 67 19038 min_impurity_decrease 0.0 19038 min_impurity_split null 19038 min_samples_leaf 167 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 16 19038 random_state 23456 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.3012135283152982 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 22078587 description https://api.openml.org/data/download/22078587/description.xml -1 22078588 predictions https://api.openml.org/data/download/22078588/predictions.arff area_under_roc_curve 0.99762 [0.999156,0.998247,0.999478,0.995608,0.998692,0.995319,0.998044,0.9992,0.997239,0.995217] average_cost 0 f_measure 0.9484470367219074 [0.977667,0.944039,0.9801,0.927318,0.952618,0.917293,0.956298,0.962779,0.929648,0.936709] kappa 0.9427777777777778 kb_relative_information_score 0.9483394051806523 mean_absolute_error 0.01165706097036198 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.9485 [0.985,0.97,0.985,0.925,0.955,0.915,0.93,0.97,0.925,0.925] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9487470533320616 [0.970443,0.919431,0.975248,0.929648,0.950249,0.919598,0.984127,0.955665,0.934343,0.948718] predictive_accuracy 0.9484999999999999 prior_entropy 3.3219280948872383 relative_absolute_error 0.06476144983534234 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.0897439014094729 root_relative_squared_error 0.29914633803157176 total_cost 0 unweighted_recall 0.9485000000000001 [0.985,0.97,0.985,0.925,0.955,0.915,0.93,0.97,0.925,0.925] area_under_roc_curve 0.9969166666666667 [0.997778,0.995556,1,1,1,0.988333,0.998611,1,0.989722,0.999167] area_under_roc_curve 0.9971944444444446 [1,0.998056,1,0.984167,0.998333,0.995556,0.998333,0.999167,0.999167,0.999167] area_under_roc_curve 0.9978888888888888 [1,0.996389,1,0.999722,1,0.988333,1,0.997778,1,0.996667] area_under_roc_curve 0.9980833333333333 [1,1,1,0.990556,0.998056,0.996944,1,0.998889,1,0.996389] area_under_roc_curve 0.9972500000000001 [0.999167,0.999444,0.994167,0.993056,0.9975,0.997222,1,0.998889,0.998056,0.995] area_under_roc_curve 0.9978888888888889 [1,0.998889,1,1,0.996667,0.995556,0.996111,1,0.9975,0.994167] area_under_roc_curve 0.9958333333333332 [0.996389,0.998889,0.999722,0.999722,0.999722,0.998333,1,1,0.996389,0.969167] area_under_roc_curve 0.9989444444444444 [1,0.999444,1,0.999722,0.999167,0.998333,0.997222,1,0.995556,1] area_under_roc_curve 0.9991111111111111 [1,1,1,0.993889,1,0.997778,1,1,1,0.999444] area_under_roc_curve 0.9979444444444445 [1,0.999722,1,0.998056,1,0.996944,0.992222,0.998611,0.996667,0.997222] 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 0.9452036517184141 [0.95,0.926829,1,0.947368,1,0.95,0.923077,1,0.85,0.904762] f_measure 0.9404457009312667 [1,0.883721,0.97561,0.894737,0.918919,0.857143,0.974359,0.97561,0.95,0.974359] f_measure 0.9600478822430043 [1,0.974359,1,0.918919,0.97561,0.9,1,0.926829,1,0.904762] f_measure 0.9650942553381577 [1,0.97561,0.952381,0.923077,0.974359,0.974359,0.97561,0.926829,0.974359,0.974359] f_measure 0.9159258014797316 [0.930233,0.909091,0.947368,0.837209,0.918919,0.871795,0.947368,0.947368,0.926829,0.923077] f_measure 0.9392146153121763 [1,0.952381,0.97561,1,0.9,0.9,0.864865,0.97561,0.904762,0.918919] f_measure 0.9494549224844475 [0.974359,0.95,0.97561,0.95,0.97561,0.926829,1,0.97561,0.871795,0.894737] f_measure 0.9498293887125722 [0.97561,0.95,0.974359,0.95,0.909091,0.894737,0.974359,0.97561,0.918919,0.97561] f_measure 0.9652094589193433 [0.974359,0.974359,1,0.926829,0.952381,0.926829,0.974359,0.97561,1,0.947368] f_measure 0.9548869580948574 [0.97561,0.952381,1,0.930233,1,0.974359,0.918919,0.947368,0.9,0.95] kappa 0.9388888888888889 kappa 0.9333333333333332 kappa 0.9555555555555555 kappa 0.961111111111111 kappa 0.9055555555555556 kappa 0.9333333333333332 kappa 0.9444444444444444 kappa 0.9444444444444444 kappa 0.961111111111111 kappa 0.95 kb_relative_information_score 0.9499206876775537 kb_relative_information_score 0.9361682841136263 kb_relative_information_score 0.9570194982792934 kb_relative_information_score 0.9636390816248553 kb_relative_information_score 0.9197022723292136 kb_relative_information_score 0.9422096407465763 kb_relative_information_score 0.9471846967578043 kb_relative_information_score 0.9546426094822802 kb_relative_information_score 0.9649696434964179 kb_relative_information_score 0.9479376372985739 mean_absolute_error 0.011107059997218283 mean_absolute_error 0.013373029364674716 mean_absolute_error 0.010291491877343097 mean_absolute_error 0.008958607004099782 mean_absolute_error 0.017701193830327006 mean_absolute_error 0.012814439001804229 mean_absolute_error 0.012681486102168033 mean_absolute_error 0.011259392272025581 mean_absolute_error 0.007290412199382241 mean_absolute_error 0.011093498054576854 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 0.9465766689450901 [0.95,0.904762,1,1,1,0.95,0.947368,1,0.85,0.863636] precision 0.9443475123909906 [1,0.826087,0.952381,0.944444,1,0.818182,1,0.952381,0.95,1] precision 0.9620779220779221 [1,1,1,1,0.952381,0.9,1,0.904762,1,0.863636] precision 0.966598313966735 [1,0.952381,0.909091,0.947368,1,1,0.952381,0.904762,1,1] precision 0.9232374414296612 [0.869565,0.833333,1,0.782609,1,0.894737,1,1,0.904762,0.947368] precision 0.9418665648077412 [1,0.909091,0.952381,1,0.9,0.9,0.941176,0.952381,0.863636,1] precision 0.9501086048454469 [1,0.95,0.952381,0.95,0.952381,0.904762,1,0.952381,0.894737,0.944444] precision 0.9534920634920634 [0.952381,0.95,1,0.95,0.833333,0.944444,1,0.952381,1,0.952381] precision 0.9670995670995671 [1,1,1,0.904762,0.909091,0.904762,1,0.952381,1,1] precision 0.9581037078863166 [0.952381,0.909091,1,0.869565,1,1,1,1,0.9,0.95] predictive_accuracy 0.945 predictive_accuracy 0.94 predictive_accuracy 0.96 predictive_accuracy 0.965 predictive_accuracy 0.915 predictive_accuracy 0.94 predictive_accuracy 0.95 predictive_accuracy 0.95 predictive_accuracy 0.965 predictive_accuracy 0.955 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 0.06170588887343497 relative_absolute_error 0.07429460758152628 relative_absolute_error 0.05717495487412839 relative_absolute_error 0.04977003891166551 relative_absolute_error 0.09833996572403902 relative_absolute_error 0.07119132778780136 relative_absolute_error 0.07045270056760027 relative_absolute_error 0.06255217928903108 relative_absolute_error 0.04050228999656805 relative_absolute_error 0.06163054474764926 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 0.08953284334753919 root_mean_squared_error 0.10069755084068524 root_mean_squared_error 0.0847541347953808 root_mean_squared_error 0.07311856396331666 root_mean_squared_error 0.10872213924869555 root_mean_squared_error 0.09543571901587003 root_mean_squared_error 0.08938737305407624 root_mean_squared_error 0.0812504476502695 root_mean_squared_error 0.07463385977015895 root_mean_squared_error 0.09361374419280073 root_relative_squared_error 0.29844281115846416 root_relative_squared_error 0.3356585028022843 root_relative_squared_error 0.2825137826512695 root_relative_squared_error 0.243728546544389 root_relative_squared_error 0.36240713082898535 root_relative_squared_error 0.3181190633862336 root_relative_squared_error 0.2979579101802543 root_relative_squared_error 0.2708348255008985 root_relative_squared_error 0.24877953256719665 root_relative_squared_error 0.3120458139760027 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 0.945 [0.95,0.95,1,0.9,1,0.95,0.9,1,0.85,0.95] unweighted_recall 0.9400000000000001 [1,0.95,1,0.85,0.85,0.9,0.95,1,0.95,0.95] unweighted_recall 0.9600000000000002 [1,0.95,1,0.85,1,0.9,1,0.95,1,0.95] unweighted_recall 0.9649999999999999 [1,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95] unweighted_recall 0.915 [1,1,0.9,0.9,0.85,0.85,0.9,0.9,0.95,0.9] unweighted_recall 0.9400000000000001 [1,1,1,1,0.9,0.9,0.8,1,0.95,0.85] unweighted_recall 0.95 [0.95,0.95,1,0.95,1,0.95,1,1,0.85,0.85] unweighted_recall 0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1] unweighted_recall 0.9650000000000001 [0.95,0.95,1,0.95,1,0.95,0.95,1,1,0.9] unweighted_recall 0.9549999999999998 [1,1,1,1,1,0.95,0.85,0.9,0.9,0.95] usercpu_time_millis 5991.898573000071 usercpu_time_millis 5103.287863999867 usercpu_time_millis 5824.503370999992 usercpu_time_millis 4821.086359998844 usercpu_time_millis 4599.723454999548 usercpu_time_millis 5873.630370000683 usercpu_time_millis 4462.809357999504 usercpu_time_millis 5271.3460639988625 usercpu_time_millis 6709.08728500126 usercpu_time_millis 5700.307869000426 usercpu_time_millis_testing 3.109700000095472 usercpu_time_millis_testing 2.901199000007182 usercpu_time_millis_testing 2.986800000144285 usercpu_time_millis_testing 3.463999999439693 usercpu_time_millis_testing 3.4623999999894295 usercpu_time_millis_testing 2.954900000077032 usercpu_time_millis_testing 3.551099999640428 usercpu_time_millis_testing 2.8347999996185536 usercpu_time_millis_testing 3.2204000008277944 usercpu_time_millis_testing 3.034299999853829 usercpu_time_millis_training 5988.788872999976 usercpu_time_millis_training 5100.38666499986 usercpu_time_millis_training 5821.516570999847 usercpu_time_millis_training 4817.622359999405 usercpu_time_millis_training 4596.261054999559 usercpu_time_millis_training 5870.675470000606 usercpu_time_millis_training 4459.258257999863 usercpu_time_millis_training 5268.511263999244 usercpu_time_millis_training 6705.866885000432 usercpu_time_millis_training 5697.273569000572 wall_clock_time_millis 5996.711254119873 wall_clock_time_millis 5123.383045196533 wall_clock_time_millis 5829.820394515991 wall_clock_time_millis 4822.9053020477295 wall_clock_time_millis 4602.319240570068 wall_clock_time_millis 5885.390996932983 wall_clock_time_millis 4471.618413925171 wall_clock_time_millis 5290.244102478027 wall_clock_time_millis 6723.923921585083 wall_clock_time_millis 5705.971479415894 wall_clock_time_millis_testing 3.1137466430664062 wall_clock_time_millis_testing 2.904176712036133 wall_clock_time_millis_testing 2.9904842376708984 wall_clock_time_millis_testing 3.467559814453125 wall_clock_time_millis_testing 3.4673213958740234 wall_clock_time_millis_testing 2.9582977294921875 wall_clock_time_millis_testing 3.5560131072998047 wall_clock_time_millis_testing 2.838611602783203 wall_clock_time_millis_testing 3.223896026611328 wall_clock_time_millis_testing 3.0379295349121094 wall_clock_time_millis_training 5993.597507476807 wall_clock_time_millis_training 5120.478868484497 wall_clock_time_millis_training 5826.82991027832 wall_clock_time_millis_training 4819.437742233276 wall_clock_time_millis_training 4598.851919174194 wall_clock_time_millis_training 5882.432699203491 wall_clock_time_millis_training 4468.062400817871 wall_clock_time_millis_training 5287.405490875244 wall_clock_time_millis_training 6720.700025558472 wall_clock_time_millis_training 5702.933549880981 weighted_recall 0.945 [0.95,0.95,1,0.9,1,0.95,0.9,1,0.85,0.95] weighted_recall 0.94 [1,0.95,1,0.85,0.85,0.9,0.95,1,0.95,0.95] weighted_recall 0.96 [1,0.95,1,0.85,1,0.9,1,0.95,1,0.95] weighted_recall 0.965 [1,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95] weighted_recall 0.915 [1,1,0.9,0.9,0.85,0.85,0.9,0.9,0.95,0.9] weighted_recall 0.94 [1,1,1,1,0.9,0.9,0.8,1,0.95,0.85] weighted_recall 0.95 [0.95,0.95,1,0.95,1,0.95,1,1,0.85,0.85] weighted_recall 0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1] weighted_recall 0.965 [0.95,0.95,1,0.95,1,0.95,0.95,1,1,0.9] weighted_recall 0.955 [1,1,1,1,1,0.95,0.85,0.9,0.9,0.95]