10559556 8323 Heinrich Peters 14954 Supervised Classification 18298 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4) 8276168 copy true 17405 with_mean true 17405 with_std true 17405 add_indicator false 17407 copy true 17407 fill_value null 17407 missing_values NaN 17407 strategy "most_frequent" 17407 verbose 0 17407 categorical_features null 17408 categories null 17408 drop null 17408 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 17408 handle_unknown "ignore" 17408 n_values null 17408 sparse true 17408 C 13917.287565392886 17495 cache_size 200 17495 class_weight null 17495 coef0 0.030380904322180546 17495 decision_function_shape "ovr" 17495 degree 5 17495 gamma 0.0011255179130262153 17495 kernel "poly" 17495 max_iter -1 17495 probability true 17495 random_state 1 17495 shrinking true 17495 tol 0.001 17495 verbose false 17495 memory null 18298 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] 18298 verbose false 18298 n_jobs null 18299 remainder "drop" 18299 sparse_threshold 0.3 18299 transformer_weights null 18299 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, true]}}] 18299 verbose false 18299 memory null 18300 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18300 verbose false 18300 memory null 18301 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18301 verbose false 18301 openml-python Sklearn_0.21.2. 6332 cylinder-bands https://www.openml.org/data/download/1854224/phpAz9Len -1 22044099 description https://api.openml.org/data/download/22044099/description.xml -1 22044100 predictions https://api.openml.org/data/download/22044100/predictions.arff area_under_roc_curve 0.813034188034188 [0.813034,0.813034] average_cost 0 f_measure 0.740604489724695 [0.665037,0.795827] kappa 0.46516873427604766 kb_relative_information_score 0.22502140282805697 mean_absolute_error 0.39370275038771246 mean_prior_absolute_error 0.48794587945879536 weighted_recall 0.7462962962962963 [0.596491,0.855769] number_of_instances 540 [228,312] precision 0.7469620099485133 [0.751381,0.743733] predictive_accuracy 0.7462962962962963 prior_entropy 0.9824743303740947 relative_absolute_error 0.806857413827098 root_mean_prior_squared_error 0.49391365607219145 root_mean_squared_error 0.42907272031234606 root_relative_squared_error 0.8687200992264767 total_cost 0 unweighted_recall 0.7261302294197031 [0.596491,0.855769] area_under_roc_curve 0.8653576437587658 [0.865358,0.865358] area_under_roc_curve 0.8345021037868162 [0.834502,0.834502] area_under_roc_curve 0.8520336605890604 [0.852034,0.852034] area_under_roc_curve 0.6858345021037868 [0.685835,0.685835] area_under_roc_curve 0.8106591865357644 [0.810659,0.810659] area_under_roc_curve 0.7405329593267882 [0.740533,0.740533] area_under_roc_curve 0.9172510518934082 [0.917251,0.917251] area_under_roc_curve 0.7503506311360448 [0.750351,0.750351] area_under_roc_curve 0.9019886363636362 [0.901989,0.901989] area_under_roc_curve 0.7883522727272727 [0.788352,0.788352] 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 0.7452381959424211 [0.648649,0.816901] f_measure 0.7761994949494949 [0.727273,0.8125] f_measure 0.741820987654321 [0.708333,0.766667] f_measure 0.5074735449735448 [0.214286,0.725] f_measure 0.7227366255144033 [0.611111,0.805556] f_measure 0.6608946608946609 [0.571429,0.727273] f_measure 0.8880997474747474 [0.863636,0.90625] f_measure 0.6985730319063653 [0.619048,0.757576] f_measure 0.8110021786492374 [0.75,0.852941] f_measure 0.7796296296296297 [0.75,0.8] kappa 0.481536189069424 kappa 0.5404255319148936 kappa 0.47572815533980567 kappa 0.07332293291731665 kappa 0.43833580980683495 kappa 0.3027259684361549 kappa 0.7702127659574467 kappa 0.3802008608321378 kappa 0.6052631578947367 kappa 0.5524861878453039 kb_relative_information_score 0.1683543581408022 kb_relative_information_score 0.3362740521172612 kb_relative_information_score 0.2819411625511203 kb_relative_information_score 0.037751737994585234 kb_relative_information_score 0.21263000445703586 kb_relative_information_score 0.1635017975501772 kb_relative_information_score 0.3261336616342583 kb_relative_information_score 0.17539386075097643 kb_relative_information_score 0.2914232741905657 kb_relative_information_score 0.2576501892550309 mean_absolute_error 0.4241604198914865 mean_absolute_error 0.34116610450824253 mean_absolute_error 0.368007959407857 mean_absolute_error 0.47391685783496235 mean_absolute_error 0.4005521925245664 mean_absolute_error 0.41918172007950777 mean_absolute_error 0.3531335241753524 mean_absolute_error 0.41569110996395625 mean_absolute_error 0.36416375339907064 mean_absolute_error 0.3770538620921215 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.4856498564985656 mean_prior_absolute_error 0.4856498564985656 number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [22,32] number_of_instances 54 [22,32] precision 0.7812830687830687 [0.857143,0.725] precision 0.7768157768157766 [0.761905,0.787879] precision 0.7449297573435506 [0.68,0.793103] precision 0.5953136810279667 [0.6,0.591837] precision 0.7664512542561324 [0.846154,0.707317] precision 0.6626566416040099 [0.631579,0.685714] precision 0.8898508898508899 [0.904762,0.878788] precision 0.7014759120022278 [0.684211,0.714286] precision 0.8168724279835392 [0.833333,0.805556] precision 0.78998778998779 [0.692308,0.857143] predictive_accuracy 0.7592592592592592 predictive_accuracy 0.7777777777777777 predictive_accuracy 0.7407407407407408 predictive_accuracy 0.5925925925925926 predictive_accuracy 0.7407407407407408 predictive_accuracy 0.6666666666666667 predictive_accuracy 0.8888888888888888 predictive_accuracy 0.7037037037037037 predictive_accuracy 0.8148148148148148 predictive_accuracy 0.7777777777777777 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9757955887617137 prior_entropy 0.9757955887617137 relative_absolute_error 0.8682562015235704 relative_absolute_error 0.6983668727617309 relative_absolute_error 0.7533121384773497 relative_absolute_error 0.9701076091141181 relative_absolute_error 0.8199301700104208 relative_absolute_error 0.8580648050977072 relative_absolute_error 0.7228641757983074 relative_absolute_error 0.8509195276559697 relative_absolute_error 0.7498483702324458 relative_absolute_error 0.7763903500571406 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.4915838450298872 root_mean_prior_squared_error 0.4915838450298872 root_mean_squared_error 0.44671768257190236 root_mean_squared_error 0.41204595950092093 root_mean_squared_error 0.4061000478825692 root_mean_squared_error 0.48237760411888303 root_mean_squared_error 0.4264888184437953 root_mean_squared_error 0.45147299156028786 root_mean_squared_error 0.3820900629147461 root_mean_squared_error 0.44928261324327107 root_mean_squared_error 0.3913978290074824 root_mean_squared_error 0.4328157956851525 root_relative_squared_error 0.903382704169679 root_relative_squared_error 0.8332672013184034 root_relative_squared_error 0.8212429767889078 root_relative_squared_error 0.9754966087998249 root_relative_squared_error 0.8624745272801533 root_relative_squared_error 0.9129992115538447 root_relative_squared_error 0.7726883616628002 root_relative_squared_error 0.9085696804106204 root_relative_squared_error 0.7961975011275771 root_relative_squared_error 0.8804516260269664 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 0.7286115007012622 [0.521739,0.935484] unweighted_recall 0.7671809256661992 [0.695652,0.83871] unweighted_recall 0.7405329593267882 [0.73913,0.741935] unweighted_recall 0.5329593267882188 [0.130435,0.935484] unweighted_recall 0.7068723702664796 [0.478261,0.935484] unweighted_recall 0.6479663394109396 [0.521739,0.774194] unweighted_recall 0.8807854137447405 [0.826087,0.935484] unweighted_recall 0.6858345021037868 [0.565217,0.806452] unweighted_recall 0.7940340909090908 [0.681818,0.90625] unweighted_recall 0.7840909090909092 [0.818182,0.75] usercpu_time_millis 220.7419999999729 usercpu_time_millis 217.99200000003793 usercpu_time_millis 218.35199999998167 usercpu_time_millis 219.28800000000592 usercpu_time_millis 217.9540000000202 usercpu_time_millis 225.06400000003168 usercpu_time_millis 221.8880000000354 usercpu_time_millis 231.22399999999743 usercpu_time_millis 230.69400000002815 usercpu_time_millis 217.736000000059 usercpu_time_millis_testing 10.503999999968983 usercpu_time_millis_testing 9.382000000016433 usercpu_time_millis_testing 10.14199999997345 usercpu_time_millis_testing 9.569999999996526 usercpu_time_millis_testing 9.47800000000143 usercpu_time_millis_testing 9.988000000021202 usercpu_time_millis_testing 9.948000000008506 usercpu_time_millis_testing 9.838000000002012 usercpu_time_millis_testing 9.410000000002583 usercpu_time_millis_testing 9.78000000003476 usercpu_time_millis_training 210.23800000000392 usercpu_time_millis_training 208.6100000000215 usercpu_time_millis_training 208.21000000000822 usercpu_time_millis_training 209.7180000000094 usercpu_time_millis_training 208.47600000001876 usercpu_time_millis_training 215.07600000001048 usercpu_time_millis_training 211.94000000002688 usercpu_time_millis_training 221.38599999999542 usercpu_time_millis_training 221.28400000002557 usercpu_time_millis_training 207.95600000002423 wall_clock_time_millis 110.43500900268555 wall_clock_time_millis 109.2989444732666 wall_clock_time_millis 109.5728874206543 wall_clock_time_millis 109.86900329589844 wall_clock_time_millis 109.26389694213867 wall_clock_time_millis 114.5172119140625 wall_clock_time_millis 111.21320724487305 wall_clock_time_millis 116.00589752197266 wall_clock_time_millis 115.52023887634277 wall_clock_time_millis 109.08222198486328 wall_clock_time_millis_testing 5.314111709594727 wall_clock_time_millis_testing 4.696846008300781 wall_clock_time_millis_testing 5.094766616821289 wall_clock_time_millis_testing 4.802942276000977 wall_clock_time_millis_testing 4.775047302246094 wall_clock_time_millis_testing 5.013942718505859 wall_clock_time_millis_testing 4.991054534912109 wall_clock_time_millis_testing 4.960060119628906 wall_clock_time_millis_testing 4.7130584716796875 wall_clock_time_millis_testing 4.91023063659668 wall_clock_time_millis_training 105.12089729309082 wall_clock_time_millis_training 104.60209846496582 wall_clock_time_millis_training 104.47812080383301 wall_clock_time_millis_training 105.06606101989746 wall_clock_time_millis_training 104.48884963989258 wall_clock_time_millis_training 109.50326919555664 wall_clock_time_millis_training 106.22215270996094 wall_clock_time_millis_training 111.04583740234375 wall_clock_time_millis_training 110.80718040466309 wall_clock_time_millis_training 104.1719913482666 weighted_recall 0.7592592592592593 [0.521739,0.935484] weighted_recall 0.7777777777777778 [0.695652,0.83871] weighted_recall 0.7407407407407407 [0.73913,0.741935] weighted_recall 0.5925925925925926 [0.130435,0.935484] weighted_recall 0.7407407407407407 [0.478261,0.935484] weighted_recall 0.6666666666666666 [0.521739,0.774194] weighted_recall 0.8888888888888888 [0.826087,0.935484] weighted_recall 0.7037037037037037 [0.565217,0.806452] weighted_recall 0.8148148148148148 [0.681818,0.90625] weighted_recall 0.7777777777777778 [0.818182,0.75]