10585067 28997 Marc Boel 9967 Supervised Classification 19039 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(2) 8301349 Python_3.7.12. Sklearn_1.0.1. NumPy_1.19.5. SciPy_1.4.1. n_jobs null 19031 remainder "drop" 19031 sparse_threshold 0.3 19031 transformer_weights null 19031 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"}}}] 19031 verbose false 19031 verbose_feature_names_out true 19031 add_indicator false 19032 copy true 19032 fill_value null 19032 missing_values NaN 19032 strategy "most_frequent" 19032 verbose 0 19032 categories "auto" 19033 drop null 19033 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 19033 handle_unknown "ignore" 19033 sparse true 19033 memory null 19039 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"}}] 19039 verbose false 19039 ccp_alpha 0.0 19040 criterion "friedman_mse" 19040 init null 19040 learning_rate 0.46750728605561914 19040 loss "deviance" 19040 max_depth 3 19040 max_features null 19040 max_leaf_nodes 227 19040 min_impurity_decrease 0.0 19040 min_samples_leaf 42 19040 min_samples_split 2 19040 min_weight_fraction_leaf 0.0 19040 n_estimators 100 19040 n_iter_no_change 6 19040 random_state 30652 19040 subsample 1.0 19040 tol 0.0001 19040 validation_fraction 0.17139112918014396 19040 verbose 0 19040 warm_start false 19040 openml-python Sklearn_1.0.1. 1504 steel-plates-fault https://www.openml.org/data/download/1592296/php9xWOpn -1 22096402 description https://api.openml.org/data/download/22096402/description.xml -1 22096403 predictions https://api.openml.org/data/download/22096403/predictions.arff area_under_roc_curve 0.9997773517514214 [0.999777,0.999777] average_cost 0 f_measure 0.9943377073785328 [0.995654,0.991858] kappa 0.9875118660960412 kb_relative_information_score 0.9855647583984017 mean_absolute_error 0.0067282804552854705 mean_prior_absolute_error 0.45306405137877787 weighted_recall 0.994332818134982 [0.993691,0.995542] number_of_instances 1941 [1268,673] precision 0.9943570945726876 [0.997625,0.988201] predictive_accuracy 0.994332818134982 prior_entropy 0.9311124141243181 relative_absolute_error 0.014850616452154543 root_mean_prior_squared_error 0.47592842871248736 root_mean_squared_error 0.06088655348151957 root_relative_squared_error 0.12793216334278212 total_cost 0 unweighted_recall 0.9946165997159477 [0.993691,0.995542] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.9996474321306853 [0.999647,0.999647] area_under_roc_curve 0.9985897285227406 [0.99859,0.99859] area_under_roc_curve 1 [1,1] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.998249299719888 [0.998249,0.998249] 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 1 [1,1] f_measure 1 [1,1] f_measure 1 [1,1] f_measure 1 [1,1] f_measure 1 [1,1] f_measure 0.9845627951410111 [0.988142,0.977778] f_measure 0.979451230664087 [0.984127,0.970588] f_measure 0.9897256153320434 [0.992063,0.985294] f_measure 1 [1,1] f_measure 0.9896907216494846 [0.992063,0.985294] kappa 1 kappa 1 kappa 1 kappa 1 kappa 1 kappa 0.9659210680407543 kappa 0.9547205041428404 kappa 0.9773602520714203 kappa 1 kappa 0.977357609710551 kb_relative_information_score 0.9999526329909323 kb_relative_information_score 0.9999524170932077 kb_relative_information_score 0.9999532589731901 kb_relative_information_score 0.9999547741669036 kb_relative_information_score 0.9999561465699713 kb_relative_information_score 0.9678324928659758 kb_relative_information_score 0.9542438284771364 kb_relative_information_score 0.9624622419168261 kb_relative_information_score 0.9999533487857949 kb_relative_information_score 0.9712641688800397 mean_absolute_error 0.0000306296585411977 mean_absolute_error 0.0000306681765691529 mean_absolute_error 0.00003012555894549952 mean_absolute_error 0.000029148999628375846 mean_absolute_error 0.000028264484662257792 mean_absolute_error 0.014102473704484543 mean_absolute_error 0.01989846198739258 mean_absolute_error 0.01899424146433562 mean_absolute_error 0.00003021982592366667 mean_absolute_error 0.014143094665550936 mean_prior_absolute_error 0.4536732781714767 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.45422372672718864 mean_prior_absolute_error 0.45422372672718864 number_of_instances 195 [127,68] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [126,68] number_of_instances 194 [126,68] precision 1 [1,1] precision 1 [1,1] precision 1 [1,1] precision 1 [1,1] precision 1 [1,1] precision 0.984646779674069 [0.992063,0.970588] precision 0.9797471985656655 [0.992,0.956522] precision 0.9899895413118183 [1,0.971014] precision 1 [1,1] precision 0.9896907216494846 [0.992063,0.985294] predictive_accuracy 1 predictive_accuracy 1 predictive_accuracy 1 predictive_accuracy 1 predictive_accuracy 1 predictive_accuracy 0.9845360824742267 predictive_accuracy 0.979381443298969 predictive_accuracy 0.9896907216494846 predictive_accuracy 1 predictive_accuracy 0.9896907216494846 prior_entropy 0.932928534004902 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9345694345320188 prior_entropy 0.9345694345320188 relative_absolute_error 0.000067514795371352 relative_absolute_error 0.00006775322974504683 relative_absolute_error 0.00006655445953331936 relative_absolute_error 0.00006439700985177237 relative_absolute_error 0.00006244290783409298 relative_absolute_error 0.03115568800508621 relative_absolute_error 0.04396039208802982 relative_absolute_error 0.041962755850977314 relative_absolute_error 0.0000665307075467174 relative_absolute_error 0.031136846961861638 root_mean_prior_squared_error 0.4765680392655914 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.4771452028525092 root_mean_prior_squared_error 0.4771452028525092 root_mean_squared_error 0.00003283741549338191 root_mean_squared_error 0.000033334045521366966 root_mean_squared_error 0.00003329114557311315 root_mean_squared_error 0.000032304981630317445 root_mean_squared_error 0.00003092984008026352 root_mean_squared_error 0.08181894741435736 root_mean_squared_error 0.12308371528124185 root_mean_squared_error 0.08690576165832226 root_mean_squared_error 0.00003342381958595163 root_mean_squared_error 0.08771701164006811 root_relative_squared_error 0.0000689039398109566 root_relative_squared_error 0.00007010488114303345 root_relative_squared_error 0.00007001465819750324 root_relative_squared_error 0.0000679406553299868 root_relative_squared_error 0.00006504859307310944 root_relative_squared_error 0.17207355105022992 root_relative_squared_error 0.25885754625562707 root_relative_squared_error 0.18277163771784616 root_relative_squared_error 0.0000700495769131379 root_relative_squared_error 0.18383714457500766 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 1 [1,1] unweighted_recall 1 [1,1] unweighted_recall 1 [1,1] unweighted_recall 1 [1,1] unweighted_recall 1 [1,1] unweighted_recall 0.9846632976848043 [0.984252,0.985075] unweighted_recall 0.9807262898107886 [0.976378,0.985075] unweighted_recall 0.9921259842519685 [0.984252,1] unweighted_recall 1 [1,1] unweighted_recall 0.9886788048552755 [0.992063,0.985294] usercpu_time_millis 689.4269419990451 usercpu_time_millis 717.5239380012499 usercpu_time_millis 691.3230009995459 usercpu_time_millis 690.7924589995673 usercpu_time_millis 689.2701120013953 usercpu_time_millis 1029.3482489978487 usercpu_time_millis 1045.5373210006655 usercpu_time_millis 548.1575969988626 usercpu_time_millis 689.9761370004853 usercpu_time_millis 809.9323860005825 usercpu_time_millis_testing 6.941263000044273 usercpu_time_millis_testing 7.313135000003967 usercpu_time_millis_testing 6.472265000411426 usercpu_time_millis_testing 7.252506000440917 usercpu_time_millis_testing 7.085577000907506 usercpu_time_millis_testing 6.964885998968384 usercpu_time_millis_testing 6.698491999486578 usercpu_time_millis_testing 6.1376089997793315 usercpu_time_millis_testing 6.222419000550872 usercpu_time_millis_testing 4.505816999881063 usercpu_time_millis_training 682.4856789990008 usercpu_time_millis_training 710.210803001246 usercpu_time_millis_training 684.8507359991345 usercpu_time_millis_training 683.5399529991264 usercpu_time_millis_training 682.1845350004878 usercpu_time_millis_training 1022.3833629988803 usercpu_time_millis_training 1038.838829001179 usercpu_time_millis_training 542.0199879990832 usercpu_time_millis_training 683.7537179999345 usercpu_time_millis_training 805.4265690007014 wall_clock_time_millis 706.2399387359619 wall_clock_time_millis 742.9001331329346 wall_clock_time_millis 725.9185314178467 wall_clock_time_millis 724.8067855834961 wall_clock_time_millis 693.2566165924072 wall_clock_time_millis 1049.6978759765625 wall_clock_time_millis 1077.0528316497803 wall_clock_time_millis 552.6080131530762 wall_clock_time_millis 698.2741355895996 wall_clock_time_millis 815.1707649230957 wall_clock_time_millis_testing 6.947517395019531 wall_clock_time_millis_testing 7.323741912841797 wall_clock_time_millis_testing 6.479024887084961 wall_clock_time_millis_testing 7.25865364074707 wall_clock_time_millis_testing 7.093191146850586 wall_clock_time_millis_testing 6.970882415771484 wall_clock_time_millis_testing 6.704092025756836 wall_clock_time_millis_testing 6.1492919921875 wall_clock_time_millis_testing 6.22868537902832 wall_clock_time_millis_testing 4.511117935180664 wall_clock_time_millis_training 699.2924213409424 wall_clock_time_millis_training 735.5763912200928 wall_clock_time_millis_training 719.4395065307617 wall_clock_time_millis_training 717.548131942749 wall_clock_time_millis_training 686.1634254455566 wall_clock_time_millis_training 1042.726993560791 wall_clock_time_millis_training 1070.3487396240234 wall_clock_time_millis_training 546.4587211608887 wall_clock_time_millis_training 692.0454502105713 wall_clock_time_millis_training 810.659646987915 weighted_recall 1 [1,1] weighted_recall 1 [1,1] weighted_recall 1 [1,1] weighted_recall 1 [1,1] weighted_recall 1 [1,1] weighted_recall 0.9845360824742269 [0.984252,0.985075] weighted_recall 0.979381443298969 [0.976378,0.985075] weighted_recall 0.9896907216494846 [0.984252,1] weighted_recall 1 [1,1] weighted_recall 0.9896907216494846 [0.992063,0.985294]