10554553 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) 8275821 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 1000 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, 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 22034061 description https://api.openml.org/data/download/22034061/description.xml -1 22034062 predictions https://api.openml.org/data/download/22034062/predictions.arff area_under_roc_curve 0.988111241430241 [0.988111,0.988111] average_cost 0 f_measure 0.9494016698945315 [0.911204,0.964674] kappa 0.8758785380620222 kb_relative_information_score 0.8252009566725866 mean_absolute_error 0.07220138453988474 mean_prior_absolute_error 0.4080904194746198 weighted_recall 0.9494559698244596 [0.907964,0.966045] number_of_instances 34465 [9844,24621] precision 0.9493567745238299 [0.914467,0.963306] predictive_accuracy 0.9494559698244597 prior_entropy 0.8629999933345911 relative_absolute_error 0.1769249683264743 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.1915722589128278 root_relative_squared_error 0.4241038903475054 total_cost 0 unweighted_recall 0.9370047440531245 [0.907964,0.966045] area_under_roc_curve 0.9877566025964767 [0.987757,0.987757] area_under_roc_curve 0.987558297286264 [0.987558,0.987558] area_under_roc_curve 0.986580181190646 [0.98658,0.98658] area_under_roc_curve 0.9885834223342006 [0.988583,0.988583] area_under_roc_curve 0.9885075482357211 [0.988508,0.988508] area_under_roc_curve 0.988924745563459 [0.988925,0.988925] area_under_roc_curve 0.9875014860018625 [0.987501,0.987501] area_under_roc_curve 0.9909345630824302 [0.990935,0.990935] area_under_roc_curve 0.9881871107500677 [0.988187,0.988187] area_under_roc_curve 0.9868856207855335 [0.986886,0.986886] 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 0.9485798703753839 [0.909648,0.964134] f_measure 0.9509793174668029 [0.914257,0.965671] f_measure 0.944648152512199 [0.903389,0.961155] f_measure 0.9510090027877235 [0.91443,0.965643] f_measure 0.9478123585984802 [0.908815,0.963415] f_measure 0.9487511799658269 [0.909558,0.964416] f_measure 0.9484699951788093 [0.910282,0.963733] f_measure 0.9534978409946188 [0.918284,0.967572] f_measure 0.9537379007384786 [0.918503,0.96782] f_measure 0.9465140603323858 [0.904836,0.963172] kappa 0.8737825755869052 kappa 0.879928073464991 kappa 0.8645448318982553 kappa 0.8800741118162025 kappa 0.8722294343054269 kappa 0.8739800943337421 kappa 0.8740182514853567 kappa 0.8858570944734596 kappa 0.8863270187901056 kappa 0.8680358239238825 kb_relative_information_score 0.822290388843172 kb_relative_information_score 0.8260776010714977 kb_relative_information_score 0.8145475621164688 kb_relative_information_score 0.8245417575830962 kb_relative_information_score 0.8231515938685409 kb_relative_information_score 0.8245829816708407 kb_relative_information_score 0.8235675119495106 kb_relative_information_score 0.8383958430210336 kb_relative_information_score 0.833406907968393 kb_relative_information_score 0.8214554839743555 mean_absolute_error 0.0731655864139377 mean_absolute_error 0.0723773690521552 mean_absolute_error 0.0762902845813679 mean_absolute_error 0.07267012902895524 mean_absolute_error 0.07269502083601219 mean_absolute_error 0.07230000168243689 mean_absolute_error 0.07252484134838155 mean_absolute_error 0.06712769753972847 mean_absolute_error 0.06899453946038078 mean_absolute_error 0.07386657874416751 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 0.948524284194263 [0.913846,0.962379] precision 0.9509869667624238 [0.913793,0.965868] precision 0.9447160623491199 [0.900202,0.962525] precision 0.9510509207347038 [0.912121,0.966626] precision 0.9478470806976601 [0.906977,0.964199] precision 0.9486697321048428 [0.919958,0.960145] precision 0.9486425291223688 [0.903,0.966885] precision 0.9534456850257705 [0.922998,0.965615] precision 0.9536724546899502 [0.926577,0.964502] precision 0.9465291820016206 [0.926518,0.954527] predictive_accuracy 0.9486510008703221 predictive_accuracy 0.9509718595880475 predictive_accuracy 0.9445894981143023 predictive_accuracy 0.9509718595880475 predictive_accuracy 0.9477806788511749 predictive_accuracy 0.9489262913522926 predictive_accuracy 0.9483459082994777 predictive_accuracy 0.9535693557748114 predictive_accuracy 0.9538595473012188 predictive_accuracy 0.9468949506674404 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 0.1793173504269051 relative_absolute_error 0.1773314977158414 relative_absolute_error 0.1869185161487834 relative_absolute_error 0.17804878774499117 relative_absolute_error 0.17810977506028142 relative_absolute_error 0.17718051589490558 relative_absolute_error 0.17773151460968695 relative_absolute_error 0.1645051148569405 relative_absolute_error 0.16908005271168974 relative_absolute_error 0.18101961583304546 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 0.1929516295889737 root_mean_squared_error 0.1919365054494693 root_mean_squared_error 0.19995498979480358 root_mean_squared_error 0.1901609084063108 root_mean_squared_error 0.19513112800716584 root_mean_squared_error 0.18899607847802435 root_mean_squared_error 0.19264895491864678 root_mean_squared_error 0.18176784638730373 root_mean_squared_error 0.18482735731477037 root_mean_squared_error 0.19665908268982843 root_relative_squared_error 0.4272282363398889 root_relative_squared_error 0.42485106563903297 root_relative_squared_error 0.44259996447903005 root_relative_squared_error 0.4209207851842291 root_relative_squared_error 0.43192235619302916 root_relative_squared_error 0.41843353606538136 root_relative_squared_error 0.4265209314133081 root_relative_squared_error 0.4024303748486095 root_relative_squared_error 0.4092040708232559 root_relative_squared_error 0.4353992740587331 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 0.9356915272867711 [0.905488,0.965895] unweighted_recall 0.9400980177891772 [0.914721,0.965475] unweighted_recall 0.9331938871867617 [0.906599,0.959789] unweighted_recall 0.9407070723731685 [0.916751,0.964663] unweighted_recall 0.9366459524879693 [0.91066,0.962632] unweighted_recall 0.9340574290186443 [0.89939,0.968725] unweighted_recall 0.9391420320580135 [0.917683,0.960601] unweighted_recall 0.9415774239992603 [0.913618,0.969537] unweighted_recall 0.940865381440167 [0.910569,0.971162] unweighted_recall 0.9280601731687503 [0.884146,0.971974] usercpu_time_millis 42291.0120000015 usercpu_time_millis 36778.142000002845 usercpu_time_millis 63720.00400000252 usercpu_time_millis 48147.18200000061 usercpu_time_millis 40464.553999998316 usercpu_time_millis 45036.64800000843 usercpu_time_millis 40523.49400000094 usercpu_time_millis 50199.541999994835 usercpu_time_millis 47408.417999999074 usercpu_time_millis 48090.85399999458 usercpu_time_millis_testing 85.86800000193762 usercpu_time_millis_testing 82.45599999645492 usercpu_time_millis_testing 83.0980000027921 usercpu_time_millis_testing 81.89800000400282 usercpu_time_millis_testing 83.87999999831663 usercpu_time_millis_testing 95.17800000321586 usercpu_time_millis_testing 86.08600000297884 usercpu_time_millis_testing 83.08599999872968 usercpu_time_millis_testing 88.184000000183 usercpu_time_millis_testing 70.43599999451544 usercpu_time_millis_training 42205.143999999564 usercpu_time_millis_training 36695.68600000639 usercpu_time_millis_training 63636.905999999726 usercpu_time_millis_training 48065.28399999661 usercpu_time_millis_training 40380.674 usercpu_time_millis_training 44941.47000000521 usercpu_time_millis_training 40437.40799999796 usercpu_time_millis_training 50116.455999996106 usercpu_time_millis_training 47320.23399999889 usercpu_time_millis_training 48020.41800000006 wall_clock_time_millis 11593.750953674316 wall_clock_time_millis 9658.515214920044 wall_clock_time_millis 17943.6252117157 wall_clock_time_millis 12954.248905181885 wall_clock_time_millis 10859.762191772461 wall_clock_time_millis 13375.094890594482 wall_clock_time_millis 11527.416229248047 wall_clock_time_millis 13217.242956161499 wall_clock_time_millis 12818.233966827393 wall_clock_time_millis 13118.56198310852 wall_clock_time_millis_testing 26.339054107666016 wall_clock_time_millis_testing 25.736093521118164 wall_clock_time_millis_testing 26.420116424560547 wall_clock_time_millis_testing 25.265932083129883 wall_clock_time_millis_testing 27.233123779296875 wall_clock_time_millis_testing 28.486013412475586 wall_clock_time_millis_testing 27.942180633544922 wall_clock_time_millis_testing 25.322914123535156 wall_clock_time_millis_testing 36.20004653930664 wall_clock_time_millis_testing 24.476051330566406 wall_clock_time_millis_training 11567.41189956665 wall_clock_time_millis_training 9632.779121398926 wall_clock_time_millis_training 17917.205095291138 wall_clock_time_millis_training 12928.982973098755 wall_clock_time_millis_training 10832.529067993164 wall_clock_time_millis_training 13346.608877182007 wall_clock_time_millis_training 11499.474048614502 wall_clock_time_millis_training 13191.920042037964 wall_clock_time_millis_training 12782.033920288086 wall_clock_time_millis_training 13094.085931777954 weighted_recall 0.9486510008703221 [0.905488,0.965895] weighted_recall 0.9509718595880475 [0.914721,0.965475] weighted_recall 0.9445894981143023 [0.906599,0.959789] weighted_recall 0.9509718595880475 [0.916751,0.964663] weighted_recall 0.9477806788511749 [0.91066,0.962632] weighted_recall 0.9489262913522926 [0.89939,0.968725] weighted_recall 0.9483459082994776 [0.917683,0.960601] weighted_recall 0.9535693557748114 [0.913618,0.969537] weighted_recall 0.9538595473012188 [0.910569,0.971162] weighted_recall 0.9468949506674406 [0.884146,0.971974]