10553058 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) 8275722 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 0.1 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 22031071 description https://api.openml.org/data/download/22031071/description.xml -1 22031072 predictions https://api.openml.org/data/download/22031072/predictions.arff area_under_roc_curve 0.8273375069047139 [0.827338,0.827338] average_cost 0 f_measure 0.7562001779591021 [0.688684,0.806011] kappa 0.49819874374688405 kb_relative_information_score 0.352371252816738 mean_absolute_error 0.3299581735395798 mean_prior_absolute_error 0.4886137014923867 weighted_recall 0.7609683968926554 [0.622758,0.862934] number_of_instances 45312 [19237,26075] precision 0.7621134069431621 [0.77022,0.756133] predictive_accuracy 0.7609683968926554 prior_entropy 0.9835093906388539 relative_absolute_error 0.67529455791309 root_mean_prior_squared_error 0.4942738102212943 root_mean_squared_error 0.4055142090925782 root_relative_squared_error 0.8204242278404819 total_cost 0 unweighted_recall 0.7428460355067393 [0.622758,0.862934] area_under_roc_curve 0.828338241202505 [0.828338,0.828338] area_under_roc_curve 0.8235110183921533 [0.823511,0.823511] area_under_roc_curve 0.8142710294609029 [0.814271,0.814271] area_under_roc_curve 0.8284825278496165 [0.828483,0.828483] area_under_roc_curve 0.8284924962140152 [0.828492,0.828492] area_under_roc_curve 0.8218858630251036 [0.821886,0.821886] area_under_roc_curve 0.8414429965062876 [0.841443,0.841443] area_under_roc_curve 0.8349159273119392 [0.834916,0.834916] area_under_roc_curve 0.8206646057253334 [0.820665,0.820665] area_under_roc_curve 0.831995994563709 [0.831996,0.831996] 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 0.7574963238358042 [0.689893,0.807369] f_measure 0.7584741748007288 [0.692264,0.80732] f_measure 0.7465215890156224 [0.675512,0.798928] f_measure 0.7553795249752234 [0.690517,0.803249] f_measure 0.7512276121758086 [0.679837,0.803915] f_measure 0.75596925581901 [0.68674,0.807061] f_measure 0.7699000978750672 [0.709513,0.814467] f_measure 0.7623547693009874 [0.695878,0.811371] f_measure 0.7500403335882532 [0.679572,0.802] f_measure 0.7544642665174539 [0.686584,0.804515] kappa 0.5008771782715027 kappa 0.5028586276462835 kappa 0.47834332308619976 kappa 0.4965082345150075 kappa 0.48811382060145325 kappa 0.497825894118329 kappa 0.5264008179375765 kappa 0.510832497708021 kappa 0.4855060228985538 kappa 0.49456568138765683 kb_relative_information_score 0.35130017505904554 kb_relative_information_score 0.34884917632379725 kb_relative_information_score 0.33453125974166165 kb_relative_information_score 0.355109175819366 kb_relative_information_score 0.35426273343009707 kb_relative_information_score 0.34845387106700715 kb_relative_information_score 0.36751387861210993 kb_relative_information_score 0.361948322255476 kb_relative_information_score 0.34365968630171245 kb_relative_information_score 0.3580857190849379 mean_absolute_error 0.33077681602446174 mean_absolute_error 0.3317338824430449 mean_absolute_error 0.33774593280149184 mean_absolute_error 0.3285363078997185 mean_absolute_error 0.3287226964932137 mean_absolute_error 0.331918079837509 mean_absolute_error 0.32367319595330585 mean_absolute_error 0.32578709161066927 mean_absolute_error 0.3336577941914727 mean_absolute_error 0.3270293655627833 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 0.7637451464700497 [0.773402,0.756621] precision 0.76402923269893 [0.771392,0.758597] precision 0.7526286100164028 [0.758911,0.747992] precision 0.7596035258234084 [0.760951,0.758609] precision 0.7586682770360094 [0.770751,0.749751] precision 0.7630337854448713 [0.775163,0.754082] precision 0.7741727784039948 [0.779229,0.770441] precision 0.7688727871242936 [0.780724,0.760134] precision 0.7564492436210029 [0.764629,0.750418] precision 0.7601712674411072 [0.767009,0.755129] predictive_accuracy 0.7623565754633715 predictive_accuracy 0.763018534863195 predictive_accuracy 0.7517104391966453 predictive_accuracy 0.7594350033105275 predictive_accuracy 0.7567865813286251 predictive_accuracy 0.7612006179651292 predictive_accuracy 0.7735599205473406 predictive_accuracy 0.7671595674244096 predictive_accuracy 0.7552416685058486 predictive_accuracy 0.7592143014787023 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 0.6769718255233586 relative_absolute_error 0.6789305692113909 relative_absolute_error 0.6912149023876495 relative_absolute_error 0.6723669182692217 relative_absolute_error 0.6727483723770189 relative_absolute_error 0.6792878932769385 relative_absolute_error 0.6624143026404924 relative_absolute_error 0.6667859495426873 relative_absolute_error 0.6828948563381131 relative_absolute_error 0.6693285021424767 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 0.4045654485930237 root_mean_squared_error 0.4075605310887938 root_mean_squared_error 0.4138391883443124 root_mean_squared_error 0.4050560941366504 root_mean_squared_error 0.40519774732650427 root_mean_squared_error 0.4078489541545165 root_mean_squared_error 0.39624156976142333 root_mean_squared_error 0.40142523693541476 root_mean_squared_error 0.4096131902084745 root_mean_squared_error 0.4035429176472004 root_relative_squared_error 0.8185069347960683 root_relative_squared_error 0.8245665125519044 root_relative_squared_error 0.8372451114741074 root_relative_squared_error 0.8194758839671575 root_relative_squared_error 0.8197624649485391 root_relative_squared_error 0.8251261666442162 root_relative_squared_error 0.8016430695528104 root_relative_squared_error 0.8121855934672102 root_relative_squared_error 0.828751910371276 root_relative_squared_error 0.8164702014276021 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 0.7440376165452852 [0.622661,0.865414] unweighted_recall 0.7452943446041606 [0.627859,0.86273] unweighted_recall 0.7329675541700857 [0.608628,0.857307] unweighted_recall 0.7427440275541541 [0.632017,0.853471] unweighted_recall 0.7373106708549746 [0.608108,0.866513] unweighted_recall 0.7422358403371061 [0.616424,0.868048] unweighted_recall 0.7575377781073984 [0.651247,0.863828] unweighted_recall 0.7488402220137885 [0.627665,0.870015] unweighted_recall 0.736370390398438 [0.611544,0.861196] unweighted_recall 0.7411188702149313 [0.621425,0.860813] usercpu_time_millis 344.2080000004353 usercpu_time_millis 376.8239999999423 usercpu_time_millis 395.66000000013446 usercpu_time_millis 366.3619999997536 usercpu_time_millis 360.71199999969394 usercpu_time_millis 389.4339999988006 usercpu_time_millis 371.4379999992161 usercpu_time_millis 384.3719999995301 usercpu_time_millis 367.05199999960314 usercpu_time_millis 366.69999999958236 usercpu_time_millis_testing 10.720000000219443 usercpu_time_millis_testing 8.227999999689928 usercpu_time_millis_testing 9.61600000027829 usercpu_time_millis_testing 7.085999999617343 usercpu_time_millis_testing 7.026000000223576 usercpu_time_millis_testing 7.391999999526888 usercpu_time_millis_testing 6.9759999996676925 usercpu_time_millis_testing 7.201999999779218 usercpu_time_millis_testing 7.045999999718333 usercpu_time_millis_testing 7.004000000051747 usercpu_time_millis_training 333.48800000021583 usercpu_time_millis_training 368.5960000002524 usercpu_time_millis_training 386.04399999985617 usercpu_time_millis_training 359.27600000013626 usercpu_time_millis_training 353.68599999947037 usercpu_time_millis_training 382.0419999992737 usercpu_time_millis_training 364.4619999995484 usercpu_time_millis_training 377.16999999975087 usercpu_time_millis_training 360.0059999998848 usercpu_time_millis_training 359.6959999995306 wall_clock_time_millis 109.86685752868652 wall_clock_time_millis 96.90713882446289 wall_clock_time_millis 101.32169723510742 wall_clock_time_millis 98.1137752532959 wall_clock_time_millis 91.64309501647949 wall_clock_time_millis 99.78604316711426 wall_clock_time_millis 94.47073936462402 wall_clock_time_millis 99.76387023925781 wall_clock_time_millis 98.30403327941895 wall_clock_time_millis 92.95368194580078 wall_clock_time_millis_testing 2.8028488159179688 wall_clock_time_millis_testing 2.2192001342773438 wall_clock_time_millis_testing 2.9489994049072266 wall_clock_time_millis_testing 1.7888545989990234 wall_clock_time_millis_testing 1.79290771484375 wall_clock_time_millis_testing 1.9190311431884766 wall_clock_time_millis_testing 1.7619132995605469 wall_clock_time_millis_testing 1.8279552459716797 wall_clock_time_millis_testing 1.7840862274169922 wall_clock_time_millis_testing 1.809835433959961 wall_clock_time_millis_training 107.06400871276855 wall_clock_time_millis_training 94.68793869018555 wall_clock_time_millis_training 98.3726978302002 wall_clock_time_millis_training 96.32492065429688 wall_clock_time_millis_training 89.85018730163574 wall_clock_time_millis_training 97.86701202392578 wall_clock_time_millis_training 92.70882606506348 wall_clock_time_millis_training 97.93591499328613 wall_clock_time_millis_training 96.51994705200195 wall_clock_time_millis_training 91.14384651184082 weighted_recall 0.7623565754633715 [0.622661,0.865414] weighted_recall 0.763018534863195 [0.627859,0.86273] weighted_recall 0.7517104391966454 [0.608628,0.857307] weighted_recall 0.7594350033105275 [0.632017,0.853471] weighted_recall 0.756786581328625 [0.608108,0.866513] weighted_recall 0.7612006179651291 [0.616424,0.868048] weighted_recall 0.7735599205473406 [0.651247,0.863828] weighted_recall 0.7671595674244096 [0.627665,0.870015] weighted_recall 0.7552416685058486 [0.611544,0.861196] weighted_recall 0.7592143014787023 [0.621425,0.860813]