10585055 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) 8301337 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 0.17719359941253549 19040 loss "deviance" 19040 max_depth 3 19040 max_features null 19040 max_leaf_nodes 394 19040 min_impurity_decrease 0.0 19040 min_samples_leaf 106 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 47671 19040 subsample 1.0 19040 tol 0.0001 19040 validation_fraction 0.23472203496375077 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 22096378 description https://api.openml.org/data/download/22096378/description.xml -1 22096379 predictions https://api.openml.org/data/download/22096379/predictions.arff area_under_roc_curve 0.9948369042987516 [0.994837,0.994837] average_cost 0 f_measure 0.9773546930566982 [0.982609,0.967456] kappa 0.9500648425011314 kb_relative_information_score 0.8963475227910433 mean_absolute_error 0.05272068248456631 mean_prior_absolute_error 0.45306405137877787 weighted_recall 0.9773312725399279 [0.980284,0.971768] number_of_instances 1941 [1268,673] precision 0.9773985472964656 [0.984945,0.963181] predictive_accuracy 0.9773312725399279 prior_entropy 0.9311124141243181 relative_absolute_error 0.11636474428753546 root_mean_prior_squared_error 0.47592842871248736 root_mean_squared_error 0.1397412305217406 root_relative_squared_error 0.29361816208327307 total_cost 0 unweighted_recall 0.976026056876081 [0.980284,0.971768] area_under_roc_curve 0.9916628068550255 [0.991663,0.991663] area_under_roc_curve 0.980138676695264 [0.980139,0.980139] area_under_roc_curve 0.9994123868844753 [0.999412,0.999412] area_under_roc_curve 0.9849571042425667 [0.984957,0.984957] area_under_roc_curve 0.9997649547537901 [0.999765,0.999765] area_under_roc_curve 0.9996474321306853 [0.999647,0.999647] area_under_roc_curve 0.9997649547537901 [0.999765,0.999765] area_under_roc_curve 0.9967093665530614 [0.996709,0.996709] area_under_roc_curve 0.9920634920634921 [0.992063,0.992063] area_under_roc_curve 0.9978991596638654 [0.997899,0.997899] 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 0.9693316345490257 [0.97619,0.956522] f_measure 0.9381443298969072 [0.952756,0.910448] f_measure 0.9845627951410111 [0.988142,0.977778] f_measure 0.9638526273233115 [0.972549,0.947368] f_measure 0.9896907216494846 [0.992126,0.985075] f_measure 0.9948542650470037 [0.996047,0.992593] f_measure 0.9896907216494846 [0.992126,0.985075] f_measure 0.9795153145076946 [0.984,0.971014] f_measure 0.9896907216494846 [0.992063,0.985294] f_measure 0.9741822830124042 [0.980237,0.962963] kappa 0.9327199539965497 kappa 0.8632036667058409 kappa 0.9659210680407543 kappa 0.9199198018634274 kappa 0.9772006111176402 kappa 0.9886403560135848 kappa 0.9772006111176402 kappa 0.9550353459265267 kappa 0.977357609710551 kappa 0.9432017800679237 kb_relative_information_score 0.8209480702677903 kb_relative_information_score 0.7677771505311164 kb_relative_information_score 0.9183341743972382 kb_relative_information_score 0.8935521938460298 kb_relative_information_score 0.9396066047159145 kb_relative_information_score 0.9345973811700297 kb_relative_information_score 0.9248614593695281 kb_relative_information_score 0.909273970357009 kb_relative_information_score 0.9399225819306426 kb_relative_information_score 0.9149255567184177 mean_absolute_error 0.09069512333678062 mean_absolute_error 0.11212159031652917 mean_absolute_error 0.04219121968394319 mean_absolute_error 0.05181035839074702 mean_absolute_error 0.0328035945881147 mean_absolute_error 0.036118287921208136 mean_absolute_error 0.04050671356034224 mean_absolute_error 0.04513215436759571 mean_absolute_error 0.03289958722463416 mean_absolute_error 0.042732450915294574 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 0.9696527472527473 [0.984,0.942857] precision 0.9381443298969072 [0.952756,0.910448] precision 0.984646779674069 [0.992063,0.970588] precision 0.9638443064667293 [0.96875,0.954545] precision 0.9896907216494846 [0.992126,0.985075] precision 0.9949211643420254 [1,0.985294] precision 0.9896907216494846 [0.992126,0.985075] precision 0.9805430521271962 [1,0.943662] precision 0.9896907216494846 [0.992063,0.985294] precision 0.9741946974277085 [0.976378,0.970149] predictive_accuracy 0.9692307692307692 predictive_accuracy 0.9381443298969071 predictive_accuracy 0.9845360824742267 predictive_accuracy 0.9639175257731959 predictive_accuracy 0.9896907216494846 predictive_accuracy 0.9948453608247422 predictive_accuracy 0.9896907216494846 predictive_accuracy 0.979381443298969 predictive_accuracy 0.9896907216494846 predictive_accuracy 0.9742268041237113 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 0.19991286174562883 relative_absolute_error 0.24770301719655347 relative_absolute_error 0.09321034767176911 relative_absolute_error 0.1144612920597404 relative_absolute_error 0.07247087141227125 relative_absolute_error 0.0797938101734021 relative_absolute_error 0.08948887664978242 relative_absolute_error 0.09970756549094348 relative_absolute_error 0.07243035818865091 relative_absolute_error 0.09407798052117192 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 0.18307412155018904 root_mean_squared_error 0.2249348536547893 root_mean_squared_error 0.11048654928232363 root_mean_squared_error 0.16605700633976034 root_mean_squared_error 0.08862116141794597 root_mean_squared_error 0.08897642629651203 root_mean_squared_error 0.09833132280002459 root_mean_squared_error 0.1396658086862436 root_mean_squared_error 0.09999317743769628 root_mean_squared_error 0.1279267079745525 root_relative_squared_error 0.3841510686119718 root_relative_squared_error 0.47306082816400874 root_relative_squared_error 0.23236442754529396 root_relative_squared_error 0.349234739148441 root_relative_squared_error 0.18637929752571808 root_relative_squared_error 0.18712645562479138 root_relative_squared_error 0.20680075249535115 root_relative_squared_error 0.29373137177180025 root_relative_squared_error 0.2095655092829368 root_relative_squared_error 0.26810854894855984 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 0.9695460861509958 [0.968504,0.970588] unweighted_recall 0.9316018333529203 [0.952756,0.910448] unweighted_recall 0.9846632976848043 [0.984252,0.985075] unweighted_recall 0.9583382301092961 [0.976378,0.940299] unweighted_recall 0.9886003055588201 [0.992126,0.985075] unweighted_recall 0.9960629921259843 [0.992126,1] unweighted_recall 0.9886003055588201 [0.992126,0.985075] unweighted_recall 0.984251968503937 [0.968504,1] unweighted_recall 0.9886788048552755 [0.992063,0.985294] unweighted_recall 0.9700046685340803 [0.984127,0.955882] usercpu_time_millis 1027.5802500000282 usercpu_time_millis 909.1407209998579 usercpu_time_millis 1047.3135249994812 usercpu_time_millis 1044.2522179982916 usercpu_time_millis 1047.490448001554 usercpu_time_millis 1047.3920790009288 usercpu_time_millis 1045.2665150005487 usercpu_time_millis 1048.3242999980575 usercpu_time_millis 1033.4259909996035 usercpu_time_millis 1007.7588489984919 usercpu_time_millis_testing 6.897041999764042 usercpu_time_millis_testing 6.893611000123201 usercpu_time_millis_testing 7.14695199894777 usercpu_time_millis_testing 6.676844999674358 usercpu_time_millis_testing 6.787460000850842 usercpu_time_millis_testing 6.979367000894854 usercpu_time_millis_testing 6.616716000280576 usercpu_time_millis_testing 6.919040999491699 usercpu_time_millis_testing 6.5720019993023016 usercpu_time_millis_testing 7.126119999156799 usercpu_time_millis_training 1020.6832080002641 usercpu_time_millis_training 902.2471099997347 usercpu_time_millis_training 1040.1665730005334 usercpu_time_millis_training 1037.5753729986172 usercpu_time_millis_training 1040.702988000703 usercpu_time_millis_training 1040.412712000034 usercpu_time_millis_training 1038.649799000268 usercpu_time_millis_training 1041.4052589985658 usercpu_time_millis_training 1026.8539890003012 usercpu_time_millis_training 1000.6327289993351 wall_clock_time_millis 1050.4629611968994 wall_clock_time_millis 929.6219348907471 wall_clock_time_millis 1072.1654891967773 wall_clock_time_millis 1057.9416751861572 wall_clock_time_millis 1073.761224746704 wall_clock_time_millis 1077.219009399414 wall_clock_time_millis 1058.5048198699951 wall_clock_time_millis 1072.3330974578857 wall_clock_time_millis 1070.4569816589355 wall_clock_time_millis 1041.8097972869873 wall_clock_time_millis_testing 6.9026947021484375 wall_clock_time_millis_testing 6.916046142578125 wall_clock_time_millis_testing 7.227659225463867 wall_clock_time_millis_testing 6.682872772216797 wall_clock_time_millis_testing 6.793498992919922 wall_clock_time_millis_testing 6.985187530517578 wall_clock_time_millis_testing 6.901979446411133 wall_clock_time_millis_testing 6.92439079284668 wall_clock_time_millis_testing 6.583213806152344 wall_clock_time_millis_testing 7.697105407714844 wall_clock_time_millis_training 1043.560266494751 wall_clock_time_millis_training 922.705888748169 wall_clock_time_millis_training 1064.9378299713135 wall_clock_time_millis_training 1051.2588024139404 wall_clock_time_millis_training 1066.9677257537842 wall_clock_time_millis_training 1070.2338218688965 wall_clock_time_millis_training 1051.602840423584 wall_clock_time_millis_training 1065.408706665039 wall_clock_time_millis_training 1063.8737678527832 wall_clock_time_millis_training 1034.1126918792725 weighted_recall 0.9692307692307692 [0.968504,0.970588] weighted_recall 0.9381443298969072 [0.952756,0.910448] weighted_recall 0.9845360824742269 [0.984252,0.985075] weighted_recall 0.9639175257731959 [0.976378,0.940299] weighted_recall 0.9896907216494846 [0.992126,0.985075] weighted_recall 0.9948453608247423 [0.992126,1] weighted_recall 0.9896907216494846 [0.992126,0.985075] weighted_recall 0.979381443298969 [0.968504,1] weighted_recall 0.9896907216494846 [0.992063,0.985294] weighted_recall 0.9742268041237113 [0.984127,0.955882]