10553056 8323 Heinrich Peters 219 Supervised Classification 18607 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)),logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2) 8275727 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 0.01 17462 class_weight null 17462 dual false 17462 fit_intercept true 17462 intercept_scaling 1 17462 l1_ratio null 17462 max_iter 10000 17462 multi_class "warn" 17462 n_jobs null 17462 penalty "l2" 17462 random_state 1 17462 solver "lbfgs" 17462 tol 0.0001 17462 verbose 0 17462 warm_start false 17462 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": [true, false, true, true, true, true, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, true, false, false, false, false, false, false]}}] 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 memory null 18607 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": "logisticregression", "step_name": "logisticregression"}}] 18607 verbose false 18607 openml-python Sklearn_0.21.2. 151 electricity https://www.openml.org/data/download/2419/electricity-normalized.arff -1 22031067 description https://api.openml.org/data/download/22031067/description.xml -1 22031068 predictions https://api.openml.org/data/download/22031068/predictions.arff area_under_roc_curve 0.827138065023404 [0.827138,0.827138] average_cost 0 f_measure 0.7545609755249156 [0.68505,0.805843] kappa 0.49488465416896854 kb_relative_information_score 0.3430868167991273 mean_absolute_error 0.3350687016352604 mean_prior_absolute_error 0.4886137014923867 weighted_recall 0.7597766596045198 [0.615377,0.866309] number_of_instances 45312 [19237,26075] precision 0.7614386595610024 [0.772514,0.753268] predictive_accuracy 0.7597766596045197 prior_entropy 0.9835093906388539 relative_absolute_error 0.6857537981678585 root_mean_prior_squared_error 0.4942738102212943 root_mean_squared_error 0.40579655796656755 root_relative_squared_error 0.820995467643503 total_cost 0 unweighted_recall 0.7408426714039953 [0.615377,0.866309] area_under_roc_curve 0.8280787645243167 [0.828079,0.828079] area_under_roc_curve 0.8236389631136564 [0.823639,0.823639] area_under_roc_curve 0.8134891109574653 [0.813489,0.813489] area_under_roc_curve 0.828239698492863 [0.82824,0.82824] area_under_roc_curve 0.828185271223246 [0.828185,0.828185] area_under_roc_curve 0.8220329960836289 [0.822033,0.822033] area_under_roc_curve 0.8414154838205471 [0.841415,0.841415] area_under_roc_curve 0.8343520397257608 [0.834352,0.834352] area_under_roc_curve 0.8205322077913791 [0.820532,0.820532] area_under_roc_curve 0.8320657826313053 [0.832066,0.832066] 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 0.7552871974795298 [0.685598,0.806699] f_measure 0.7567298100502943 [0.688581,0.807005] f_measure 0.7430202693435545 [0.668994,0.797653] f_measure 0.7559351655405061 [0.689891,0.804676] f_measure 0.7493144193580151 [0.675454,0.803824] f_measure 0.7545946331331403 [0.684103,0.806618] f_measure 0.769243883619886 [0.70699,0.815188] f_measure 0.7607132262224116 [0.692731,0.81084] f_measure 0.746169882792694 [0.672875,0.800213] f_measure 0.754398400901231 [0.684622,0.805848] kappa 0.49639472857330713 kappa 0.49931176030600083 kappa 0.47124349318980696 kappa 0.49765635320514146 kappa 0.4843157601285383 kappa 0.4950460617475015 kappa 0.5250469330491239 kappa 0.5074981331630257 kappa 0.4776312018706977 kappa 0.494500911418035 kb_relative_information_score 0.34190198152774715 kb_relative_information_score 0.33983018473966425 kb_relative_information_score 0.32528548000281726 kb_relative_information_score 0.34567194398022677 kb_relative_information_score 0.3449437465323923 kb_relative_information_score 0.3393152334114331 kb_relative_information_score 0.3579621861848189 kb_relative_information_score 0.35209033979684146 kb_relative_information_score 0.334908523573287 kb_relative_information_score 0.34896000229563434 mean_absolute_error 0.33591961766014306 mean_absolute_error 0.33670535623611747 mean_absolute_error 0.34279653313348013 mean_absolute_error 0.3337405667452999 mean_absolute_error 0.33385117921098717 mean_absolute_error 0.3368977742718766 mean_absolute_error 0.3289761775924046 mean_absolute_error 0.3311830370107735 mean_absolute_error 0.3384796509121684 mean_absolute_error 0.33213657456796447 mean_prior_absolute_error 0.48861238171727794 mean_prior_absolute_error 0.48861238171727794 mean_prior_absolute_error 0.48862652068817236 mean_prior_absolute_error 0.48862652068817236 mean_prior_absolute_error 0.48862652068817236 mean_prior_absolute_error 0.48862652068817236 mean_prior_absolute_error 0.48862652068817236 mean_prior_absolute_error 0.4885932162099533 mean_prior_absolute_error 0.4885932162099533 mean_prior_absolute_error 0.4885932162099533 number_of_instances 4532 [1924,2608] number_of_instances 4532 [1924,2608] number_of_instances 4531 [1924,2607] number_of_instances 4531 [1924,2607] number_of_instances 4531 [1924,2607] number_of_instances 4531 [1924,2607] number_of_instances 4531 [1924,2607] number_of_instances 4531 [1923,2608] number_of_instances 4531 [1923,2608] number_of_instances 4531 [1923,2608] precision 0.7624581522137451 [0.774722,0.753411] precision 0.7631725777512304 [0.773316,0.755689] precision 0.7503002961495921 [0.759577,0.743454] precision 0.7609280467976299 [0.765526,0.757535] precision 0.7580830871182807 [0.773826,0.746465] precision 0.7622274885408521 [0.775873,0.752157] precision 0.7745416948263858 [0.783681,0.767797] precision 0.7679128466230305 [0.781699,0.757747] precision 0.7535768200028308 [0.764045,0.745858] precision 0.7613441665168738 [0.772549,0.753082] predictive_accuracy 0.7605913503971756 predictive_accuracy 0.7616946160635482 predictive_accuracy 0.7488413153829176 predictive_accuracy 0.7603178106378283 predictive_accuracy 0.7554623703376738 predictive_accuracy 0.7600971088060031 predictive_accuracy 0.7733392187155154 predictive_accuracy 0.7658353564334583 predictive_accuracy 0.7519311410284705 predictive_accuracy 0.7596557051423527 prior_entropy 0.9835055532661361 prior_entropy 0.9835055532661361 prior_entropy 0.98354666368022 prior_entropy 0.98354666368022 prior_entropy 0.98354666368022 prior_entropy 0.98354666368022 prior_entropy 0.98354666368022 prior_entropy 0.9834498277152368 prior_entropy 0.9834498277152368 prior_entropy 0.9834498277152368 relative_absolute_error 0.6874971454458837 relative_absolute_error 0.6891052475025955 relative_absolute_error 0.7015512229067958 relative_absolute_error 0.6830177090577605 relative_absolute_error 0.683244083314998 relative_absolute_error 0.6894791011290099 relative_absolute_error 0.6732671348437674 relative_absolute_error 0.6778297897375246 relative_absolute_error 0.6927637136220909 relative_absolute_error 0.6797813877654048 root_mean_prior_squared_error 0.49427247515480305 root_mean_prior_squared_error 0.49427247515480305 root_mean_prior_squared_error 0.4942867777581652 root_mean_prior_squared_error 0.4942867777581652 root_mean_prior_squared_error 0.4942867777581652 root_mean_prior_squared_error 0.4942867777581652 root_mean_prior_squared_error 0.4942867777581652 root_mean_prior_squared_error 0.494253087181386 root_mean_prior_squared_error 0.494253087181386 root_mean_prior_squared_error 0.494253087181386 root_mean_squared_error 0.4050011562536198 root_mean_squared_error 0.40768363474271235 root_mean_squared_error 0.4141177473334124 root_mean_squared_error 0.405264531764673 root_mean_squared_error 0.4055008052351971 root_mean_squared_error 0.408022999659291 root_mean_squared_error 0.3968559872508592 root_mean_squared_error 0.4019627312579396 root_mean_squared_error 0.409717014752973 root_mean_squared_error 0.40360019911943856 root_relative_squared_error 0.8193884478935957 root_relative_squared_error 0.824815572857923 root_relative_squared_error 0.8378086689100627 root_relative_squared_error 0.8198975776830363 root_relative_squared_error 0.820375586566049 root_relative_squared_error 0.8254782810697 root_relative_squared_error 0.8028861080419695 root_relative_squared_error 0.8132730815102086 root_relative_squared_error 0.8289619738937734 root_relative_squared_error 0.8165860964492495 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 0.7414815121870337 [0.614865,0.868098] unweighted_recall 0.7431898332971953 [0.620582,0.865798] unweighted_recall 0.72904450436096 [0.597713,0.860376] unweighted_recall 0.7429665214475341 [0.627859,0.858074] unweighted_recall 0.7350024960784455 [0.599272,0.870733] unweighted_recall 0.7406641283223562 [0.611746,0.869582] unweighted_recall 0.7563928117725587 [0.643971,0.868815] unweighted_recall 0.7469386965662675 [0.621945,0.871933] unweighted_recall 0.7321287713471729 [0.601144,0.863113] unweighted_recall 0.7406145018806887 [0.614665,0.866564] usercpu_time_millis 314.66999999975087 usercpu_time_millis 364.57399999926565 usercpu_time_millis 357.63999999926455 usercpu_time_millis 381.6820000001826 usercpu_time_millis 402.4760000002061 usercpu_time_millis 355.4839999997057 usercpu_time_millis 347.4800000003597 usercpu_time_millis 351.7860000001747 usercpu_time_millis 355.46400000021094 usercpu_time_millis 325.71400000051653 usercpu_time_millis_testing 7.945999999719788 usercpu_time_millis_testing 8.441999999377003 usercpu_time_millis_testing 8.313999999700172 usercpu_time_millis_testing 7.278000000042084 usercpu_time_millis_testing 9.595999999874039 usercpu_time_millis_testing 7.206000000223867 usercpu_time_millis_testing 6.959999999708089 usercpu_time_millis_testing 7.324000000153319 usercpu_time_millis_testing 7.657999999537424 usercpu_time_millis_testing 7.006000000728818 usercpu_time_millis_training 306.7240000000311 usercpu_time_millis_training 356.13199999988865 usercpu_time_millis_training 349.3259999995644 usercpu_time_millis_training 374.4040000001405 usercpu_time_millis_training 392.8800000003321 usercpu_time_millis_training 348.27799999948184 usercpu_time_millis_training 340.52000000065163 usercpu_time_millis_training 344.46200000002136 usercpu_time_millis_training 347.8060000006735 usercpu_time_millis_training 318.7079999997877 wall_clock_time_millis 100.93092918395996 wall_clock_time_millis 93.12152862548828 wall_clock_time_millis 91.91393852233887 wall_clock_time_millis 97.29123115539551 wall_clock_time_millis 103.68728637695312 wall_clock_time_millis 93.22595596313477 wall_clock_time_millis 89.09201622009277 wall_clock_time_millis 90.58785438537598 wall_clock_time_millis 90.55376052856445 wall_clock_time_millis 85.09588241577148 wall_clock_time_millis_testing 2.0868778228759766 wall_clock_time_millis_testing 2.286672592163086 wall_clock_time_millis_testing 2.2449493408203125 wall_clock_time_millis_testing 1.8532276153564453 wall_clock_time_millis_testing 2.5610923767089844 wall_clock_time_millis_testing 1.8320083618164062 wall_clock_time_millis_testing 1.7490386962890625 wall_clock_time_millis_testing 1.8520355224609375 wall_clock_time_millis_testing 1.9848346710205078 wall_clock_time_millis_testing 1.7600059509277344 wall_clock_time_millis_training 98.84405136108398 wall_clock_time_millis_training 90.8348560333252 wall_clock_time_millis_training 89.66898918151855 wall_clock_time_millis_training 95.43800354003906 wall_clock_time_millis_training 101.12619400024414 wall_clock_time_millis_training 91.39394760131836 wall_clock_time_millis_training 87.34297752380371 wall_clock_time_millis_training 88.73581886291504 wall_clock_time_millis_training 88.56892585754395 wall_clock_time_millis_training 83.33587646484375 weighted_recall 0.7605913503971756 [0.614865,0.868098] weighted_recall 0.7616946160635482 [0.620582,0.865798] weighted_recall 0.7488413153829176 [0.597713,0.860376] weighted_recall 0.7603178106378283 [0.627859,0.858074] weighted_recall 0.7554623703376738 [0.599272,0.870733] weighted_recall 0.7600971088060031 [0.611746,0.869582] weighted_recall 0.7733392187155154 [0.643971,0.868815] weighted_recall 0.7658353564334583 [0.621945,0.871933] weighted_recall 0.7519311410284706 [0.601144,0.863113] weighted_recall 0.7596557051423527 [0.614665,0.866564]