10576217 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) 8292499 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 0.848392724911614 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 190 19038 min_samples_split 2 19038 min_weight_fraction_leaf 0.0 19038 n_estimators 100 19038 n_iter_no_change 7 19038 random_state 52664 19038 subsample 1.0 19038 tol 0.0001 19038 validation_fraction 0.2611548407814239 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 22078701 description https://api.openml.org/data/download/22078701/description.xml -1 22078702 predictions https://api.openml.org/data/download/22078702/predictions.arff area_under_roc_curve 0.9966533333333334 [0.999125,0.997689,0.999739,0.99465,0.998514,0.991653,0.996956,0.998231,0.995494,0.994483] average_cost 0 f_measure 0.9435779275441752 [0.964646,0.933985,0.97,0.931034,0.940299,0.916877,0.937824,0.965,0.921569,0.954545] kappa 0.9372222222222222 kb_relative_information_score 0.9399017343306889 mean_absolute_error 0.014258711199811383 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.9435 [0.955,0.955,0.97,0.945,0.945,0.91,0.905,0.965,0.94,0.945] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9441592702238332 [0.97449,0.913876,0.97,0.917476,0.935644,0.923858,0.973118,0.965,0.903846,0.964286] predictive_accuracy 0.9434999999999999 prior_entropy 3.3219280948872383 relative_absolute_error 0.0792150622211719 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.09468556110724487 root_relative_squared_error 0.3156185370241447 total_cost 0 unweighted_recall 0.9435 [0.955,0.955,0.97,0.945,0.945,0.91,0.905,0.965,0.94,0.945] area_under_roc_curve 0.9958611111111111 [0.995833,0.993889,1,0.998889,1,0.981667,0.998611,1,0.990556,0.999167] area_under_roc_curve 0.9964444444444445 [0.999722,0.995,0.999444,0.991389,0.996667,0.99,0.999444,0.995556,0.998889,0.998333] area_under_roc_curve 0.997777777777778 [0.998611,0.999167,1,0.996111,0.998611,0.993333,0.998889,0.997222,0.996944,0.998889] area_under_roc_curve 0.9972222222222222 [0.999722,1,0.999444,0.984167,0.9975,0.997222,1,1,0.998333,0.995833] area_under_roc_curve 0.9949166666666669 [0.999722,0.998889,0.997778,0.989444,0.999444,0.970833,1,0.996667,0.9975,0.998889] area_under_roc_curve 0.997138888888889 [1,0.998889,1,1,0.998333,0.992222,0.997222,1,0.998611,0.986111] area_under_roc_curve 0.998 [1,0.996389,1,1,0.998889,0.9975,1,0.999444,0.995,0.992778] area_under_roc_curve 0.9979444444444445 [1,0.997778,1,0.9975,0.999444,0.995833,0.997222,0.999722,0.991944,1] area_under_roc_curve 0.9985277777777776 [1,0.999722,1,0.990833,1,0.997222,1,1,0.997778,0.999722] area_under_roc_curve 0.9942222222222223 [1,0.998611,1,0.9975,0.998611,0.996944,0.983056,0.989722,0.992222,0.985556] 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 0.9354490544831471 [0.923077,0.894737,1,0.904762,0.97561,0.974359,0.894737,1,0.837209,0.95] f_measure 0.9297689110205155 [0.952381,0.926829,0.923077,0.923077,0.894737,0.904762,0.947368,0.923077,0.952381,0.95] f_measure 0.9452125858736897 [0.947368,0.95,0.974359,0.974359,0.926829,0.9,0.926829,0.95,0.95,0.952381] f_measure 0.9651094434021261 [0.95,0.97561,0.97561,0.926829,0.974359,0.974359,0.974359,0.97561,0.95,0.974359] f_measure 0.9352036517184142 [0.95,0.926829,0.9,0.923077,0.947368,0.9,1,0.95,0.904762,0.95] f_measure 0.9337456250765431 [1,0.952381,0.97561,0.974359,0.926829,0.878049,0.823529,0.97561,0.883721,0.947368] f_measure 0.9549472414620038 [0.947368,0.952381,1,0.952381,0.95,0.923077,1,0.974359,0.926829,0.923077] f_measure 0.9499711330199134 [1,0.904762,0.974359,0.904762,0.952381,0.918919,0.95,0.97561,0.918919,1] f_measure 0.9501396161331378 [0.974359,0.95,0.97561,0.904762,0.930233,0.894737,0.947368,0.97561,0.974359,0.974359] f_measure 0.9351441455420916 [1,0.904762,1,0.926829,0.923077,0.904762,0.894737,0.947368,0.926829,0.923077] kappa 0.9277777777777778 kappa 0.9222222222222223 kappa 0.9388888888888889 kappa 0.961111111111111 kappa 0.9277777777777778 kappa 0.9277777777777778 kappa 0.95 kappa 0.9444444444444444 kappa 0.9444444444444444 kappa 0.9277777777777778 kb_relative_information_score 0.9396454996185208 kb_relative_information_score 0.9253186201243541 kb_relative_information_score 0.9325891350342437 kb_relative_information_score 0.9584987523908082 kb_relative_information_score 0.9290070261235389 kb_relative_information_score 0.935805276306595 kb_relative_information_score 0.9469441749833801 kb_relative_information_score 0.9442716613401785 kb_relative_information_score 0.9547929129686505 kb_relative_information_score 0.9321442844162892 mean_absolute_error 0.013807684703759437 mean_absolute_error 0.017100307240936037 mean_absolute_error 0.016445408429730003 mean_absolute_error 0.01069126129917437 mean_absolute_error 0.017972168339407003 mean_absolute_error 0.013080417171405692 mean_absolute_error 0.013345037672135978 mean_absolute_error 0.01350364731838427 mean_absolute_error 0.01044434178408007 mean_absolute_error 0.016196838039100672 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 0.9384883321611011 [0.947368,0.944444,1,0.863636,0.952381,1,0.944444,1,0.782609,0.95] precision 0.9323129794182425 [0.909091,0.904762,0.947368,0.947368,0.944444,0.863636,1,0.947368,0.909091,0.95] precision 0.946861471861472 [1,0.95,1,1,0.904762,0.9,0.904762,0.95,0.95,0.909091] precision 0.9661904761904762 [0.95,0.952381,0.952381,0.904762,1,1,1,0.952381,0.95,1] precision 0.9365766689450901 [0.95,0.904762,0.9,0.947368,1,0.9,1,0.95,0.863636,0.95] precision 0.9401844532279314 [1,0.909091,0.952381,1,0.904762,0.857143,1,0.952381,0.826087,1] precision 0.9567680565048985 [1,0.909091,1,0.909091,0.95,0.947368,1,1,0.904762,0.947368] precision 0.9538744588744588 [1,0.863636,1,0.863636,0.909091,1,0.95,0.952381,1,1] precision 0.9532407930234017 [1,0.95,0.952381,0.863636,0.869565,0.944444,1,0.952381,1,1] precision 0.9375977823346244 [1,0.863636,1,0.904762,0.947368,0.863636,0.944444,1,0.904762,0.947368] predictive_accuracy 0.935 predictive_accuracy 0.93 predictive_accuracy 0.945 predictive_accuracy 0.965 predictive_accuracy 0.935 predictive_accuracy 0.935 predictive_accuracy 0.955 predictive_accuracy 0.95 predictive_accuracy 0.95 predictive_accuracy 0.935 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 0.07670935946533029 relative_absolute_error 0.0950017068940892 relative_absolute_error 0.0913633801651668 relative_absolute_error 0.05939589610652435 relative_absolute_error 0.09984537966337234 relative_absolute_error 0.07266898428558725 relative_absolute_error 0.0741390981785333 relative_absolute_error 0.07502026287991269 relative_absolute_error 0.058024121022667116 relative_absolute_error 0.08998243355055939 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 0.09633051947983408 root_mean_squared_error 0.10520244992906232 root_mean_squared_error 0.09895602256016853 root_mean_squared_error 0.07520100711747815 root_mean_squared_error 0.09882022473445842 root_mean_squared_error 0.10170171797174117 root_mean_squared_error 0.08788485946998709 root_mean_squared_error 0.0912180328931801 root_mean_squared_error 0.08369522335975578 root_mean_squared_error 0.10344515347768822 root_relative_squared_error 0.3211017315994471 root_relative_squared_error 0.3506748330968746 root_relative_squared_error 0.32985340853389533 root_relative_squared_error 0.25067002372492736 root_relative_squared_error 0.32940074911486156 root_relative_squared_error 0.33900572657247074 root_relative_squared_error 0.2929495315666238 root_relative_squared_error 0.3040601096439339 root_relative_squared_error 0.2789840778658528 root_relative_squared_error 0.3448171782589609 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 0.9349999999999999 [0.9,0.85,1,0.95,1,0.95,0.85,1,0.9,0.95] unweighted_recall 0.93 [1,0.95,0.9,0.9,0.85,0.95,0.9,0.9,1,0.95] unweighted_recall 0.9450000000000001 [0.9,0.95,0.95,0.95,0.95,0.9,0.95,0.95,0.95,1] unweighted_recall 0.9650000000000001 [0.95,1,1,0.95,0.95,0.95,0.95,1,0.95,0.95] unweighted_recall 0.9349999999999999 [0.95,0.95,0.9,0.9,0.9,0.9,1,0.95,0.95,0.95] unweighted_recall 0.9350000000000002 [1,1,1,0.95,0.95,0.9,0.7,1,0.95,0.9] unweighted_recall 0.9550000000000001 [0.9,1,1,1,0.95,0.9,1,0.95,0.95,0.9] unweighted_recall 0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1] unweighted_recall 0.9499999999999998 [0.95,0.95,1,0.95,1,0.85,0.9,1,0.95,0.95] unweighted_recall 0.9350000000000002 [1,0.95,1,0.95,0.9,0.95,0.85,0.9,0.95,0.9] usercpu_time_millis 3923.059149000437 usercpu_time_millis 2971.0428359994694 usercpu_time_millis 3657.2285479996935 usercpu_time_millis 3502.716042999964 usercpu_time_millis 2986.3245370006553 usercpu_time_millis 5075.0812599999335 usercpu_time_millis 3522.3215409996556 usercpu_time_millis 3806.5721459997803 usercpu_time_millis 4152.544149999812 usercpu_time_millis 3295.081941000717 usercpu_time_millis_testing 2.6119989997823723 usercpu_time_millis_testing 2.6170000001002336 usercpu_time_millis_testing 3.2712999991417746 usercpu_time_millis_testing 2.690999999686028 usercpu_time_millis_testing 3.344200000356068 usercpu_time_millis_testing 2.864899999622139 usercpu_time_millis_testing 3.6145999993095757 usercpu_time_millis_testing 2.5848999994195765 usercpu_time_millis_testing 2.7046000004702364 usercpu_time_millis_testing 3.3196000003954396 usercpu_time_millis_training 3920.447150000655 usercpu_time_millis_training 2968.425835999369 usercpu_time_millis_training 3653.9572480005518 usercpu_time_millis_training 3500.025043000278 usercpu_time_millis_training 2982.980337000299 usercpu_time_millis_training 5072.216360000311 usercpu_time_millis_training 3518.706941000346 usercpu_time_millis_training 3803.9872460003608 usercpu_time_millis_training 4149.839549999342 usercpu_time_millis_training 3291.7623410003216 wall_clock_time_millis 3925.997734069824 wall_clock_time_millis 2972.522258758545 wall_clock_time_millis 3659.5664024353027 wall_clock_time_millis 3502.781391143799 wall_clock_time_millis 2989.5639419555664 wall_clock_time_millis 5093.977928161621 wall_clock_time_millis 3525.908946990967 wall_clock_time_millis 3811.248540878296 wall_clock_time_millis 4157.371759414673 wall_clock_time_millis 3300.093412399292 wall_clock_time_millis_testing 2.6094913482666016 wall_clock_time_millis_testing 2.6204586029052734 wall_clock_time_millis_testing 3.273487091064453 wall_clock_time_millis_testing 2.694368362426758 wall_clock_time_millis_testing 3.3490657806396484 wall_clock_time_millis_testing 2.867460250854492 wall_clock_time_millis_testing 3.618001937866211 wall_clock_time_millis_testing 2.588987350463867 wall_clock_time_millis_testing 2.707242965698242 wall_clock_time_millis_testing 3.3228397369384766 wall_clock_time_millis_training 3923.3882427215576 wall_clock_time_millis_training 2969.9018001556396 wall_clock_time_millis_training 3656.2929153442383 wall_clock_time_millis_training 3500.087022781372 wall_clock_time_millis_training 2986.2148761749268 wall_clock_time_millis_training 5091.110467910767 wall_clock_time_millis_training 3522.2909450531006 wall_clock_time_millis_training 3808.659553527832 wall_clock_time_millis_training 4154.664516448975 wall_clock_time_millis_training 3296.7705726623535 weighted_recall 0.935 [0.9,0.85,1,0.95,1,0.95,0.85,1,0.9,0.95] weighted_recall 0.93 [1,0.95,0.9,0.9,0.85,0.95,0.9,0.9,1,0.95] weighted_recall 0.945 [0.9,0.95,0.95,0.95,0.95,0.9,0.95,0.95,0.95,1] weighted_recall 0.965 [0.95,1,1,0.95,0.95,0.95,0.95,1,0.95,0.95] weighted_recall 0.935 [0.95,0.95,0.9,0.9,0.9,0.9,1,0.95,0.95,0.95] weighted_recall 0.935 [1,1,1,0.95,0.95,0.9,0.7,1,0.95,0.9] weighted_recall 0.955 [0.9,1,1,1,0.95,0.9,1,0.95,0.95,0.9] weighted_recall 0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1] weighted_recall 0.95 [0.95,0.95,1,0.95,1,0.85,0.9,1,0.95,0.95] weighted_recall 0.935 [1,0.95,1,0.95,0.9,0.95,0.85,0.9,0.95,0.9]