10554540 8323 Heinrich Peters 9977 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) 8275807 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 224.662208931 17462 class_weight null 17462 dual true 17462 fit_intercept true 17462 intercept_scaling 1 17462 l1_ratio null 17462 max_iter 785 17462 multi_class "warn" 17462 n_jobs null 17462 penalty "l2" 17462 random_state 1 17462 solver "liblinear" 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, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, true, true, true, false, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true, true, false, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, false, false, false, true, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, false, false, false, true, 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. 1486 nomao https://www.openml.org/data/download/1592278/phpDYCOet -1 22034035 description https://api.openml.org/data/download/22034035/description.xml -1 22034036 predictions https://api.openml.org/data/download/22034036/predictions.arff area_under_roc_curve 0.9846519806706071 [0.984652,0.984652] average_cost 0 f_measure 0.9455905450798463 [0.904142,0.962163] kappa 0.8663089829283117 kb_relative_information_score 0.8317743882486203 mean_absolute_error 0.06697353657282946 mean_prior_absolute_error 0.4080904194746198 weighted_recall 0.9457420571594372 [0.895876,0.96568] number_of_instances 34465 [9844,24621] precision 0.9455012444989794 [0.912562,0.958671] predictive_accuracy 0.945742057159437 prior_entropy 0.8629999933345911 relative_absolute_error 0.16411445448548373 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.20472028571264167 root_relative_squared_error 0.4532110760529872 total_cost 0 unweighted_recall 0.9307776823090717 [0.895876,0.96568] area_under_roc_curve 0.977674872668337 [0.977675,0.977675] area_under_roc_curve 0.9865525531221779 [0.986553,0.986553] area_under_roc_curve 0.9848899207033198 [0.98489,0.98489] area_under_roc_curve 0.9875826264808852 [0.987583,0.987583] area_under_roc_curve 0.9876630365309041 [0.987663,0.987663] area_under_roc_curve 0.9860910225674151 [0.986091,0.986091] area_under_roc_curve 0.9831615350069016 [0.983162,0.983162] area_under_roc_curve 0.987001198708169 [0.987001,0.987001] area_under_roc_curve 0.986120329826369 [0.98612,0.98612] area_under_roc_curve 0.9844081254581839 [0.984408,0.984408] 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 0.9339762700406984 [0.882536,0.954527] f_measure 0.9484694680512835 [0.910282,0.963747] f_measure 0.94241496596923 [0.901088,0.958949] f_measure 0.9486921758800931 [0.911619,0.963525] f_measure 0.9481413222182465 [0.90955,0.963581] f_measure 0.9478798922380098 [0.906904,0.964257] f_measure 0.9440026343186436 [0.900826,0.961259] f_measure 0.9532900541652184 [0.917098,0.967755] f_measure 0.949420051607356 [0.909943,0.965198] f_measure 0.9394105962042852 [0.890774,0.958849] kappa 0.8370965273055314 kappa 0.8740322467396648 kappa 0.8600755356667337 kappa 0.8751678491384153 kappa 0.8731322092850872 kappa 0.8712032131374452 kappa 0.8621002434388234 kappa 0.8848707426856088 kappa 0.8751697639114275 kappa 0.8497305261197031 kb_relative_information_score 0.8017202850469094 kb_relative_information_score 0.8419253784359304 kb_relative_information_score 0.8266879649103152 kb_relative_information_score 0.8365257829043138 kb_relative_information_score 0.8388683548246714 kb_relative_information_score 0.8344787311794403 kb_relative_information_score 0.8303355562148116 kb_relative_information_score 0.8446525251725024 kb_relative_information_score 0.8420942764705291 kb_relative_information_score 0.8204496517189185 mean_absolute_error 0.07902992657391159 mean_absolute_error 0.06253362186775846 mean_absolute_error 0.06812808570625578 mean_absolute_error 0.06457718537147492 mean_absolute_error 0.06391522053081755 mean_absolute_error 0.06638029997598999 mean_absolute_error 0.06763589466211449 mean_absolute_error 0.06275626197529016 mean_absolute_error 0.06303079146675834 mean_absolute_error 0.07174711521916782 mean_prior_absolute_error 0.4080229059806574 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.4081472833897437 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 mean_prior_absolute_error 0.40805842175852763 number_of_instances 3447 [984,2463] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3447 [985,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] number_of_instances 3446 [984,2462] precision 0.9338873778090346 [0.903191,0.946151] precision 0.9486151410203015 [0.903904,0.966503] precision 0.9433482869605427 [0.878496,0.969295] precision 0.9493841503546253 [0.892128,0.972291] precision 0.9482272247214888 [0.905433,0.965349] precision 0.9480328005363604 [0.934267,0.953535] precision 0.9439198993868687 [0.915966,0.955092] precision 0.95329497471714 [0.935518,0.9604] precision 0.9494777993401837 [0.932764,0.956158] precision 0.9399318473005219 [0.931264,0.943396] predictive_accuracy 0.934435741224253 predictive_accuracy 0.9483608935306063 predictive_accuracy 0.941978532056861 predictive_accuracy 0.9483608935306063 predictive_accuracy 0.9480707861908907 predictive_accuracy 0.9483459082994777 predictive_accuracy 0.9442832269297736 predictive_accuracy 0.9535693557748114 predictive_accuracy 0.9497968659315148 predictive_accuracy 0.9402205455600696 prior_entropy 0.862791736866817 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.863175399426382 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 prior_entropy 0.862901291120622 relative_absolute_error 0.1936899262652133 relative_absolute_error 0.1532133727521212 relative_absolute_error 0.16692034586249993 relative_absolute_error 0.15822029938591936 relative_absolute_error 0.15659842202057314 relative_absolute_error 0.16267352035015992 relative_absolute_error 0.1657505177092967 relative_absolute_error 0.15379234597056488 relative_absolute_error 0.15446511603688307 relative_absolute_error 0.17582559602611225 root_mean_prior_squared_error 0.4516359481339797 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.45177362368332785 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_prior_squared_error 0.4516752654560011 root_mean_squared_error 0.22293462156536523 root_mean_squared_error 0.1984996521933232 root_mean_squared_error 0.21078307698294815 root_mean_squared_error 0.1999334383471057 root_mean_squared_error 0.2012274590363336 root_mean_squared_error 0.20012123730633272 root_mean_squared_error 0.20775694288474392 root_mean_squared_error 0.1956887574539583 root_mean_squared_error 0.1960756828946925 root_mean_squared_error 0.2124949662189487 root_relative_squared_error 0.4936157595214957 root_relative_squared_error 0.4393785776490177 root_relative_squared_error 0.4665679135147943 root_relative_squared_error 0.44255226039324874 root_relative_squared_error 0.44541657256507877 root_relative_squared_error 0.4430644151042782 root_relative_squared_error 0.45996971446952534 root_relative_squared_error 0.43325099340207474 root_relative_squared_error 0.4341076385857413 root_relative_squared_error 0.4704596033267808 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 0.9129290326094491 [0.862805,0.963053] unweighted_recall 0.9388792900823482 [0.916751,0.961007] unweighted_recall 0.9368475961518636 [0.924873,0.948822] unweighted_recall 0.9434471994622835 [0.93198,0.954915] unweighted_recall 0.9377626212851587 [0.913706,0.96182] unweighted_recall 0.9281604782944661 [0.881098,0.975223] unweighted_recall 0.926842477198127 [0.886179,0.967506] unweighted_recall 0.9373068197578808 [0.89939,0.975223] unweighted_recall 0.9313112150211673 [0.888211,0.974411] unweighted_recall 0.9142378791781419 [0.853659,0.974817] usercpu_time_millis 40964.613999989524 usercpu_time_millis 41967.64599999733 usercpu_time_millis 40398.68600000045 usercpu_time_millis 40828.04600000236 usercpu_time_millis 40946.63600000058 usercpu_time_millis 40441.92199999816 usercpu_time_millis 34797.30800000107 usercpu_time_millis 27076.735999995435 usercpu_time_millis 26707.127999994555 usercpu_time_millis 27684.636000005412 usercpu_time_millis_testing 58.68199999531498 usercpu_time_millis_testing 53.31399999704445 usercpu_time_millis_testing 48.14800000167452 usercpu_time_millis_testing 55.43800000305055 usercpu_time_millis_testing 52.617999994254205 usercpu_time_millis_testing 53.6839999986114 usercpu_time_millis_testing 33.781999998609535 usercpu_time_millis_testing 36.71799999574432 usercpu_time_millis_testing 33.61399999994319 usercpu_time_millis_testing 47.61000000144122 usercpu_time_millis_training 40905.93199999421 usercpu_time_millis_training 41914.332000000286 usercpu_time_millis_training 40350.53799999878 usercpu_time_millis_training 40772.60799999931 usercpu_time_millis_training 40894.01800000633 usercpu_time_millis_training 40388.23799999955 usercpu_time_millis_training 34763.52600000246 usercpu_time_millis_training 27040.01799999969 usercpu_time_millis_training 26673.51399999461 usercpu_time_millis_training 27637.02600000397 wall_clock_time_millis 25814.157962799072 wall_clock_time_millis 25966.240167617798 wall_clock_time_millis 24724.536657333374 wall_clock_time_millis 25221.699953079224 wall_clock_time_millis 25074.28002357483 wall_clock_time_millis 24602.133750915527 wall_clock_time_millis 19838.215112686157 wall_clock_time_millis 13739.82310295105 wall_clock_time_millis 13518.385887145996 wall_clock_time_millis 14067.024230957031 wall_clock_time_millis_testing 55.52101135253906 wall_clock_time_millis_testing 43.157100677490234 wall_clock_time_millis_testing 48.41494560241699 wall_clock_time_millis_testing 46.76008224487305 wall_clock_time_millis_testing 41.27383232116699 wall_clock_time_millis_testing 40.71688652038574 wall_clock_time_millis_testing 23.57316017150879 wall_clock_time_millis_testing 24.85489845275879 wall_clock_time_millis_testing 23.099899291992188 wall_clock_time_millis_testing 32.31692314147949 wall_clock_time_millis_training 25758.636951446533 wall_clock_time_millis_training 25923.083066940308 wall_clock_time_millis_training 24676.121711730957 wall_clock_time_millis_training 25174.93987083435 wall_clock_time_millis_training 25033.006191253662 wall_clock_time_millis_training 24561.41686439514 wall_clock_time_millis_training 19814.64195251465 wall_clock_time_millis_training 13714.968204498291 wall_clock_time_millis_training 13495.285987854004 wall_clock_time_millis_training 14034.707307815552 weighted_recall 0.934435741224253 [0.862805,0.963053] weighted_recall 0.9483608935306064 [0.916751,0.961007] weighted_recall 0.941978532056861 [0.924873,0.948822] weighted_recall 0.9483608935306064 [0.93198,0.954915] weighted_recall 0.9480707861908906 [0.913706,0.96182] weighted_recall 0.9483459082994776 [0.881098,0.975223] weighted_recall 0.9442832269297736 [0.886179,0.967506] weighted_recall 0.9535693557748114 [0.89939,0.975223] weighted_recall 0.9497968659315148 [0.888211,0.974411] weighted_recall 0.9402205455600696 [0.853659,0.974817]