10585116 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) 8301398 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 "median" 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 0.042869239518196114 19040 loss "deviance" 19040 max_depth 3 19040 max_features null 19040 max_leaf_nodes 780 19040 min_impurity_decrease 0.0 19040 min_samples_leaf 116 19040 min_samples_split 2 19040 min_weight_fraction_leaf 0.0 19040 n_estimators 100 19040 n_iter_no_change 14 19040 random_state 59548 19040 subsample 1.0 19040 tol 0.0001 19040 validation_fraction 0.2497271074646948 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 22096500 description https://api.openml.org/data/download/22096500/description.xml -1 22096501 predictions https://api.openml.org/data/download/22096501/predictions.arff area_under_roc_curve 0.9717717175788995 [0.971772,0.971772] average_cost 0 f_measure 0.913553400039378 [0.932156,0.878505] kappa 0.8107710226056718 kb_relative_information_score 0.6228437930972021 mean_absolute_error 0.18617652799454798 mean_prior_absolute_error 0.45306405137877787 weighted_recall 0.9129314786192684 [0.915615,0.907875] number_of_instances 1941 [1268,673] precision 0.9152111553744376 [0.949305,0.850975] predictive_accuracy 0.9129314786192684 prior_entropy 0.9311124141243181 relative_absolute_error 0.4109276104073366 root_mean_prior_squared_error 0.47592842871248736 root_mean_squared_error 0.2639791037117185 root_relative_squared_error 0.554661347769983 total_cost 0 unweighted_recall 0.9117451638456743 [0.915615,0.907875] area_under_roc_curve 0.977999073645206 [0.977999,0.977999] area_under_roc_curve 0.9696204019273709 [0.96962,0.96962] area_under_roc_curve 0.9724997061934423 [0.9725,0.9725] area_under_roc_curve 0.9737924550475967 [0.973792,0.973792] area_under_roc_curve 0.9722646609472322 [0.972265,0.972265] area_under_roc_curve 0.9582794687977436 [0.958279,0.958279] area_under_roc_curve 0.9737336937360442 [0.973734,0.973734] area_under_roc_curve 0.9593371724056879 [0.959337,0.959337] area_under_roc_curve 0.978874883286648 [0.978875,0.978875] area_under_roc_curve 0.9842436974789917 [0.984244,0.984244] 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 0.9388483516483517 [0.952,0.914286] f_measure 0.918507946514052 [0.934959,0.887324] f_measure 0.9335221178416848 [0.947791,0.906475] f_measure 0.9011091785006914 [0.926641,0.852713] f_measure 0.9025488834038516 [0.924303,0.861314] f_measure 0.8728223175940406 [0.897959,0.825175] f_measure 0.9083214398283086 [0.926829,0.873239] f_measure 0.8929056997192899 [0.91498,0.851064] f_measure 0.9286566015060184 [0.942623,0.902778] f_measure 0.9379262466787743 [0.952756,0.910448] kappa 0.866346812885538 kappa 0.8226082980912103 kappa 0.8543711745005197 kappa 0.7795190812298122 kappa 0.7856727526456565 kappa 0.7237726392527623 kappa 0.8004343353526117 kappa 0.7663722904002753 kappa 0.8456818181818182 kappa 0.863219741480611 kb_relative_information_score 0.6451379111872526 kb_relative_information_score 0.6276372527356255 kb_relative_information_score 0.6291680886910269 kb_relative_information_score 0.623530861270286 kb_relative_information_score 0.6260401058211444 kb_relative_information_score 0.5654376315298093 kb_relative_information_score 0.6285849536397544 kb_relative_information_score 0.5679890678804224 kb_relative_information_score 0.6448692921112614 kb_relative_information_score 0.6695064005441206 mean_absolute_error 0.17834876814847472 mean_absolute_error 0.18345731638134208 mean_absolute_error 0.18444273760245075 mean_absolute_error 0.18519917190942095 mean_absolute_error 0.18424692604975915 mean_absolute_error 0.20944468361065263 mean_absolute_error 0.18134346527210518 mean_absolute_error 0.20885073432006465 mean_absolute_error 0.178239220598872 mean_absolute_error 0.1682326053298937 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 0.940073657146828 [0.96748,0.888889] precision 0.9227375898813134 [0.966387,0.84] precision 0.9353663173905695 [0.967213,0.875] precision 0.9014949965232638 [0.909091,0.887097] precision 0.9034942277542876 [0.935484,0.842857] precision 0.8783659196041826 [0.932203,0.776316] precision 0.9126316093447688 [0.957983,0.826667] precision 0.896474180365933 [0.941667,0.810811] precision 0.9327551799295548 [0.974576,0.855263] precision 0.9379271126210559 [0.945312,0.924242] predictive_accuracy 0.9384615384615383 predictive_accuracy 0.9175257731958762 predictive_accuracy 0.9329896907216495 predictive_accuracy 0.9020618556701031 predictive_accuracy 0.9020618556701031 predictive_accuracy 0.8711340206185567 predictive_accuracy 0.9072164948453608 predictive_accuracy 0.8917525773195877 predictive_accuracy 0.9278350515463917 predictive_accuracy 0.9381443298969071 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 0.39312160695755927 relative_absolute_error 0.40530044807741056 relative_absolute_error 0.4074774757933842 relative_absolute_error 0.4091486174496749 relative_absolute_error 0.4070448819257203 relative_absolute_error 0.46271266684386236 relative_absolute_error 0.4006304527965367 relative_absolute_error 0.46140049288231716 relative_absolute_error 0.3924040293604572 relative_absolute_error 0.3703738828045324 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 0.25117384886584265 root_mean_squared_error 0.26333351749514644 root_mean_squared_error 0.2604051300751748 root_mean_squared_error 0.26474880671858847 root_mean_squared_error 0.2640693252243658 root_mean_squared_error 0.28933749568996536 root_mean_squared_error 0.26289939246376703 root_mean_squared_error 0.28676977514917823 root_mean_squared_error 0.2538474813525015 root_mean_squared_error 0.23939034222391434 root_relative_squared_error 0.5270471961420465 root_relative_squared_error 0.5538171156915462 root_relative_squared_error 0.5476584197154976 root_relative_squared_error 0.5567936125805548 root_relative_squared_error 0.5553645940307111 root_relative_squared_error 0.6085061212437008 root_relative_squared_error 0.5529041066867868 root_relative_squared_error 0.6031059443223302 root_relative_squared_error 0.5320130640210347 root_relative_squared_error 0.5017138195936396 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 0.9390921723019916 [0.937008,0.941176] unweighted_recall 0.9229051592431543 [0.905512,0.940299] unweighted_recall 0.9347161828652015 [0.929134,0.940299] unweighted_recall 0.8828887060759196 [0.944882,0.820896] unweighted_recall 0.8969914208485134 [0.913386,0.880597] unweighted_recall 0.8733693736044188 [0.866142,0.880597] unweighted_recall 0.9115054648019744 [0.897638,0.925373] unweighted_recall 0.8926430837936303 [0.889764,0.895522] unweighted_recall 0.9342903828197946 [0.912698,0.955882] unweighted_recall 0.9286881419234361 [0.960317,0.897059] usercpu_time_millis 1005.0306210014242 usercpu_time_millis 1005.6357260000368 usercpu_time_millis 1002.0778060006705 usercpu_time_millis 999.4904449995374 usercpu_time_millis 1007.0080530003906 usercpu_time_millis 1005.2992090004409 usercpu_time_millis 1017.2423280000658 usercpu_time_millis 1014.2504620016553 usercpu_time_millis 1003.9179889972729 usercpu_time_millis 989.5324629997049 usercpu_time_millis_testing 6.736262001140858 usercpu_time_millis_testing 7.141505999243236 usercpu_time_millis_testing 6.887916000778205 usercpu_time_millis_testing 7.251807999637094 usercpu_time_millis_testing 7.4511020011414075 usercpu_time_millis_testing 7.562857999801054 usercpu_time_millis_testing 6.576812000275822 usercpu_time_millis_testing 7.2323630010942 usercpu_time_millis_testing 7.18758399852959 usercpu_time_millis_testing 4.552933998638764 usercpu_time_millis_training 998.2943590002833 usercpu_time_millis_training 998.4942200007936 usercpu_time_millis_training 995.1898899998923 usercpu_time_millis_training 992.2386369999003 usercpu_time_millis_training 999.5569509992492 usercpu_time_millis_training 997.7363510006398 usercpu_time_millis_training 1010.6655159997899 usercpu_time_millis_training 1007.018099000561 usercpu_time_millis_training 996.7304049987433 usercpu_time_millis_training 984.9795290010661 wall_clock_time_millis 1027.5375843048096 wall_clock_time_millis 1033.212661743164 wall_clock_time_millis 1008.9213848114014 wall_clock_time_millis 1023.6086845397949 wall_clock_time_millis 1011.458158493042 wall_clock_time_millis 1031.6689014434814 wall_clock_time_millis 1037.5034809112549 wall_clock_time_millis 1037.8758907318115 wall_clock_time_millis 1008.4662437438965 wall_clock_time_millis 1014.533281326294 wall_clock_time_millis_testing 6.742238998413086 wall_clock_time_millis_testing 9.047746658325195 wall_clock_time_millis_testing 6.893634796142578 wall_clock_time_millis_testing 7.323741912841797 wall_clock_time_millis_testing 7.459163665771484 wall_clock_time_millis_testing 7.568120956420898 wall_clock_time_millis_testing 6.582736968994141 wall_clock_time_millis_testing 7.251262664794922 wall_clock_time_millis_testing 7.308721542358398 wall_clock_time_millis_testing 4.557371139526367 wall_clock_time_millis_training 1020.7953453063965 wall_clock_time_millis_training 1024.1649150848389 wall_clock_time_millis_training 1002.0277500152588 wall_clock_time_millis_training 1016.2849426269531 wall_clock_time_millis_training 1003.9989948272705 wall_clock_time_millis_training 1024.1007804870605 wall_clock_time_millis_training 1030.9207439422607 wall_clock_time_millis_training 1030.6246280670166 wall_clock_time_millis_training 1001.1575222015381 wall_clock_time_millis_training 1009.9759101867676 weighted_recall 0.9384615384615385 [0.937008,0.941176] weighted_recall 0.9175257731958762 [0.905512,0.940299] weighted_recall 0.9329896907216495 [0.929134,0.940299] weighted_recall 0.9020618556701031 [0.944882,0.820896] weighted_recall 0.9020618556701031 [0.913386,0.880597] weighted_recall 0.8711340206185567 [0.866142,0.880597] weighted_recall 0.9072164948453608 [0.897638,0.925373] weighted_recall 0.8917525773195877 [0.889764,0.895522] weighted_recall 0.9278350515463918 [0.912698,0.955882] weighted_recall 0.9381443298969072 [0.960317,0.897059]