10559338 8323 Heinrich Peters 219 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) 8276070 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 9947.045017657287 17495 cache_size 200 17495 class_weight null 17495 coef0 0.13893166748012198 17495 decision_function_shape "ovr" 17495 degree 2 17495 gamma 9.972833450436674e-05 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": [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 openml-python Sklearn_0.21.2. 151 electricity https://www.openml.org/data/download/2419/electricity-normalized.arff -1 22043641 description https://api.openml.org/data/download/22043641/description.xml -1 22043642 predictions https://api.openml.org/data/download/22043642/predictions.arff area_under_roc_curve 0.8440703400401243 [0.84407,0.84407] average_cost 0 f_measure 0.7698984189719343 [0.708971,0.814848] kappa 0.526361810744603 kb_relative_information_score 0.3839784550064567 mean_absolute_error 0.31466328705540586 mean_prior_absolute_error 0.4886137014923867 weighted_recall 0.773680261299435 [0.649322,0.865427] number_of_instances 45312 [19237,26075] precision 0.774454088799221 [0.780687,0.769855] predictive_accuracy 0.773680261299435 prior_entropy 0.9835093906388539 relative_absolute_error 0.6439919431123623 root_mean_prior_squared_error 0.4942738102212943 root_mean_squared_error 0.39593885786259236 root_relative_squared_error 0.8010516634197635 total_cost 0 unweighted_recall 0.757374136839108 [0.649322,0.865427] area_under_roc_curve 0.8427565351453388 [0.842757,0.842757] area_under_roc_curve 0.8409473728683851 [0.840947,0.840947] area_under_roc_curve 0.830526042551359 [0.830526,0.830526] area_under_roc_curve 0.8430481025417734 [0.843048,0.843048] area_under_roc_curve 0.8463249032869286 [0.846325,0.846325] area_under_roc_curve 0.8410787524711575 [0.841079,0.841079] area_under_roc_curve 0.856964736711572 [0.856965,0.856965] area_under_roc_curve 0.8513043589228231 [0.851304,0.851304] area_under_roc_curve 0.8381045441204151 [0.838105,0.838105] area_under_roc_curve 0.8498001269744041 [0.8498,0.8498] 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 0.7697711032674771 [0.709477,0.814252] f_measure 0.7683725454577106 [0.708404,0.812613] f_measure 0.7544459346248178 [0.687464,0.803879] f_measure 0.7714314525184117 [0.713122,0.814465] f_measure 0.7701200382362562 [0.707163,0.816583] f_measure 0.7702721698687929 [0.708796,0.815642] f_measure 0.7796427679615706 [0.723129,0.821351] f_measure 0.7762798299864228 [0.716078,0.82067] f_measure 0.7642280083351985 [0.699369,0.812052] f_measure 0.7742608651050636 [0.716216,0.81706] kappa 0.5261041805053652 kappa 0.5232393558012317 kappa 0.4945990553173182 kappa 0.5295925536098016 kappa 0.526864517837646 kappa 0.5271604992425225 kappa 0.5464821552051922 kappa 0.5394478406521263 kappa 0.5146565208823431 kappa 0.5353282915070113 kb_relative_information_score 0.38244442692958186 kb_relative_information_score 0.38284111615845184 kb_relative_information_score 0.36360395936294304 kb_relative_information_score 0.3842624204963922 kb_relative_information_score 0.3857667362160916 kb_relative_information_score 0.38129486200779583 kb_relative_information_score 0.39910827179688757 kb_relative_information_score 0.3930848610777935 kb_relative_information_score 0.37540617380888364 kb_relative_information_score 0.39197303980554293 mean_absolute_error 0.31564902347522905 mean_absolute_error 0.31522201918322507 mean_absolute_error 0.3236242592157924 mean_absolute_error 0.3144359066444775 mean_absolute_error 0.3135216037000577 mean_absolute_error 0.3160787656674303 mean_absolute_error 0.3079240045827006 mean_absolute_error 0.3107793711426219 mean_absolute_error 0.318472414951033 mean_absolute_error 0.3109251611244483 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 0.773926001743663 [0.778399,0.770626] precision 0.7721049396573645 [0.774353,0.770447] precision 0.7597078826052206 [0.764968,0.755826] precision 0.7748114583090839 [0.776147,0.773826] precision 0.776079043071111 [0.787995,0.767285] precision 0.7752798171806092 [0.783512,0.769205] precision 0.7833882266031559 [0.788344,0.779731] precision 0.7815862164199561 [0.792429,0.773591] precision 0.7700636923191642 [0.77991,0.762803] precision 0.777868352982132 [0.780847,0.775672] predictive_accuracy 0.7733892321270962 predictive_accuracy 0.7718446601941747 predictive_accuracy 0.7589935996468771 predictive_accuracy 0.7746634297064665 predictive_accuracy 0.7744427278746413 predictive_accuracy 0.7742220260428162 predictive_accuracy 0.7828293974839992 predictive_accuracy 0.7801809755020966 predictive_accuracy 0.768704480247186 predictive_accuracy 0.7775325535201942 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 0.6460111026369174 relative_absolute_error 0.6451371904971895 relative_absolute_error 0.6623141510207143 relative_absolute_error 0.6435097018508776 relative_absolute_error 0.6416385325514052 relative_absolute_error 0.6468718996714934 relative_absolute_error 0.6301827501074364 relative_absolute_error 0.6360697628046414 relative_absolute_error 0.6518150567489301 relative_absolute_error 0.6363681500457852 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 0.39587172965688333 root_mean_squared_error 0.3973504419939695 root_mean_squared_error 0.4056877920779746 root_mean_squared_error 0.39664178286338647 root_mean_squared_error 0.3949241943956994 root_mean_squared_error 0.3977080035279433 root_mean_squared_error 0.386556957609727 root_mean_squared_error 0.3917976829387528 root_mean_squared_error 0.3996503828462748 root_mean_squared_error 0.3929090961863371 root_relative_squared_error 0.8009180149732166 root_relative_squared_error 0.8039097096586693 root_relative_squared_error 0.8207538828328955 root_relative_squared_error 0.8024527474968134 root_relative_squared_error 0.798977865009612 root_relative_squared_error 0.8046098366857912 root_relative_squared_error 0.7820499657363967 root_relative_squared_error 0.7927065972882166 root_relative_squared_error 0.8085946111644763 root_relative_squared_error 0.794955269631211 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 0.7574403243498335 [0.651767,0.863113] unweighted_recall 0.7562346147468847 [0.652807,0.859663] unweighted_recall 0.7413391859594392 [0.62422,0.858458] unweighted_recall 0.7595860776240523 [0.659563,0.859609] unweighted_recall 0.7570113487835006 [0.641372,0.872651] unweighted_recall 0.7575684806697465 [0.647089,0.868048] unweighted_recall 0.767771699733725 [0.667879,0.867664] unweighted_recall 0.7634979095482838 [0.653146,0.87385] unweighted_recall 0.7510017578617255 [0.633905,0.868098] unweighted_recall 0.7622899777954308 [0.661466,0.863113] usercpu_time_millis 333769.2399999996 usercpu_time_millis 333296.0300000009 usercpu_time_millis 332572.81800000055 usercpu_time_millis 335872.00200000004 usercpu_time_millis 332726.138 usercpu_time_millis 332519.24600000074 usercpu_time_millis 338403.2559999996 usercpu_time_millis 335152.84000000067 usercpu_time_millis 336100.79399999906 usercpu_time_millis 331537.3359999994 usercpu_time_millis_testing 2450.811999999587 usercpu_time_millis_testing 2413.610000000517 usercpu_time_millis_testing 2391.42400000037 usercpu_time_millis_testing 2490.523999999823 usercpu_time_millis_testing 2446.0280000002967 usercpu_time_millis_testing 2374.886000000515 usercpu_time_millis_testing 2408.7799999997515 usercpu_time_millis_testing 2458.5360000000946 usercpu_time_millis_testing 2414.46999999971 usercpu_time_millis_testing 2470.143999999891 usercpu_time_millis_training 331318.428 usercpu_time_millis_training 330882.4200000004 usercpu_time_millis_training 330181.3940000002 usercpu_time_millis_training 333381.47800000024 usercpu_time_millis_training 330280.1099999997 usercpu_time_millis_training 330144.3600000002 usercpu_time_millis_training 335994.47599999985 usercpu_time_millis_training 332694.3040000006 usercpu_time_millis_training 333686.3239999993 usercpu_time_millis_training 329067.1919999995 wall_clock_time_millis 169444.28896903992 wall_clock_time_millis 168976.63617134094 wall_clock_time_millis 168861.73558235168 wall_clock_time_millis 170412.67371177673 wall_clock_time_millis 168716.5608406067 wall_clock_time_millis 168727.96893119812 wall_clock_time_millis 171742.64311790466 wall_clock_time_millis 170207.30757713318 wall_clock_time_millis 170710.96420288086 wall_clock_time_millis 168154.8671722412 wall_clock_time_millis_testing 1239.5799160003662 wall_clock_time_millis_testing 1214.1690254211426 wall_clock_time_millis_testing 1209.5067501068115 wall_clock_time_millis_testing 1257.8117847442627 wall_clock_time_millis_testing 1240.0870323181152 wall_clock_time_millis_testing 1197.1099376678467 wall_clock_time_millis_testing 1222.1341133117676 wall_clock_time_millis_testing 1239.8338317871094 wall_clock_time_millis_testing 1213.456153869629 wall_clock_time_millis_testing 1243.3710098266602 wall_clock_time_millis_training 168204.70905303955 wall_clock_time_millis_training 167762.4671459198 wall_clock_time_millis_training 167652.22883224487 wall_clock_time_millis_training 169154.86192703247 wall_clock_time_millis_training 167476.47380828857 wall_clock_time_millis_training 167530.85899353027 wall_clock_time_millis_training 170520.5090045929 wall_clock_time_millis_training 168967.47374534607 wall_clock_time_millis_training 169497.50804901123 wall_clock_time_millis_training 166911.49616241455 weighted_recall 0.7733892321270962 [0.651767,0.863113] weighted_recall 0.7718446601941747 [0.652807,0.859663] weighted_recall 0.7589935996468771 [0.62422,0.858458] weighted_recall 0.7746634297064665 [0.659563,0.859609] weighted_recall 0.7744427278746414 [0.641372,0.872651] weighted_recall 0.7742220260428162 [0.647089,0.868048] weighted_recall 0.7828293974839992 [0.667879,0.867664] weighted_recall 0.7801809755020966 [0.653146,0.87385] weighted_recall 0.7687044802471861 [0.633905,0.868098] weighted_recall 0.7775325535201942 [0.661466,0.863113]