10448797 8323 Heinrich Peters 9977 Supervised Classification 17651 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)),randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1) 8264351 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 copy true 13294 with_mean true 13294 with_std true 13294 categorical_features null 16348 categories null 16348 drop null 16348 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 16348 handle_unknown "ignore" 16348 n_values null 16348 sparse true 16348 n_jobs null 16375 remainder "drop" 16375 sparse_threshold 0.3 16375 transformer_weights null 16375 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]}}] 16375 verbose false 16375 memory null 16376 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 16376 verbose false 16376 memory null 16377 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 16377 verbose false 16377 bootstrap false 17650 class_weight null 17650 criterion "gini" 17650 max_depth null 17650 max_features 0.21975649694764154 17650 max_leaf_nodes null 17650 min_impurity_decrease 0 17650 min_impurity_split null 17650 min_samples_leaf 2 17650 min_samples_split 4 17650 min_weight_fraction_leaf 0.0 17650 n_estimators 300 17650 n_jobs 1 17650 oob_score false 17650 random_state 1 17650 verbose 0 17650 warm_start false 17650 memory null 17651 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": "randomforestclassifier", "step_name": "randomforestclassifier"}}] 17651 verbose false 17651 openml-python Sklearn_0.21.2. 1486 nomao https://www.openml.org/data/download/1592278/phpDYCOet -1 21822025 description https://api.openml.org/data/download/21822025/description.xml -1 21822026 predictions https://api.openml.org/data/download/21822026/predictions.arff area_under_roc_curve 0.9947393301740396 [0.99474,0.994739] average_cost 0 f_measure 0.9700327246810391 [0.947443,0.979064] kappa 0.9265080656554294 kb_relative_information_score 0.8771788893091934 mean_absolute_error 0.052884544514336614 mean_prior_absolute_error 0.4080904194746198 weighted_recall 0.9700565791382562 [0.944941,0.980098] number_of_instances 34465 [9844,24621] precision 0.9700142224609898 [0.949959,0.978033] predictive_accuracy 0.9700565791382562 prior_entropy 0.8629999933345911 relative_absolute_error 0.1295902623306393 root_mean_prior_squared_error 0.4517106852187937 root_mean_squared_error 0.15203617828258295 root_relative_squared_error 0.33657866253250496 total_cost 0 unweighted_recall 0.9625196854695073 [0.944941,0.980098] area_under_roc_curve 0.9940970142380585 [0.994098,0.994097] area_under_roc_curve 0.9948585284781521 [0.99486,0.994858] area_under_roc_curve 0.993829102967259 [0.993828,0.993829] area_under_roc_curve 0.9952971902943786 [0.995298,0.995297] area_under_roc_curve 0.995286910742203 [0.995287,0.995287] area_under_roc_curve 0.9952690887858812 [0.99527,0.995269] area_under_roc_curve 0.9943029816652765 [0.994302,0.994303] area_under_roc_curve 0.9960589405327448 [0.996058,0.996059] area_under_roc_curve 0.9944877285809041 [0.99449,0.994487] area_under_roc_curve 0.9941633736014444 [0.994165,0.994163] 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 0.9712749873673682 [0.94967,0.979907] f_measure 0.9698288366695678 [0.947208,0.978879] f_measure 0.9667127389376313 [0.942065,0.976574] f_measure 0.9727299100667247 [0.952284,0.98091] f_measure 0.9712485506773203 [0.949567,0.979923] f_measure 0.966856900897385 [0.941718,0.976904] f_measure 0.9666431994123715 [0.941654,0.976631] f_measure 0.9744078630567096 [0.954964,0.982179] f_measure 0.9701057094746782 [0.947636,0.979086] f_measure 0.970528740822953 [0.94775,0.979633] kappa 0.9295761916996598 kappa 0.9260870820223747 kappa 0.9186410100373644 kappa 0.9331940933663772 kappa 0.9294902827616258 kappa 0.9186233811429567 kappa 0.9182848246780695 kappa 0.9371444726982392 kappa 0.9267222958797523 kappa 0.9273918813990485 kb_relative_information_score 0.8749297160045572 kb_relative_information_score 0.8746897335744984 kb_relative_information_score 0.8685190040736963 kb_relative_information_score 0.8824291458785699 kb_relative_information_score 0.8801761657155699 kb_relative_information_score 0.8729853808568627 kb_relative_information_score 0.87610607929041 kb_relative_information_score 0.8892716680166692 kb_relative_information_score 0.8758436179721824 kb_relative_information_score 0.876840512711829 mean_absolute_error 0.0540603513923075 mean_absolute_error 0.05357281974074657 mean_absolute_error 0.05622701151280524 mean_absolute_error 0.05104774528270844 mean_absolute_error 0.05183832594275527 mean_absolute_error 0.05430501621223342 mean_absolute_error 0.052649915989984156 mean_absolute_error 0.04833095876632323 mean_absolute_error 0.053368877717855236 mean_absolute_error 0.053443748316525604 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 0.9712707991882483 [0.950153,0.979708] precision 0.9698288366695678 [0.947208,0.978879] precision 0.9668315933413548 [0.935,0.979567] precision 0.9727299100667247 [0.952284,0.98091] precision 0.9712274499305763 [0.952965,0.978534] precision 0.9668241289558004 [0.947531,0.974535] precision 0.9666601888715963 [0.940223,0.977227] precision 0.974391859465313 [0.961856,0.979402] precision 0.970101343723325 [0.948118,0.978888] precision 0.9706140665037419 [0.965227,0.972767] predictive_accuracy 0.9712793733681463 predictive_accuracy 0.9698288366695678 predictive_accuracy 0.9666376559326951 predictive_accuracy 0.9727299100667247 predictive_accuracy 0.9712793733681463 predictive_accuracy 0.9669181659895532 predictive_accuracy 0.9666279744631457 predictive_accuracy 0.9744631456761462 predictive_accuracy 0.9701102727800348 predictive_accuracy 0.9706906558328496 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 0.13249342279541107 relative_absolute_error 0.131258547884513 relative_absolute_error 0.13776157235650038 relative_absolute_error 0.1250718732187725 relative_absolute_error 0.12700887168040845 relative_absolute_error 0.1330814739178914 relative_absolute_error 0.12902543651247134 relative_absolute_error 0.11844127259533321 relative_absolute_error 0.13078734532144215 relative_absolute_error 0.13097082541810995 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 0.15386162943660722 root_mean_squared_error 0.1526597841358949 root_mean_squared_error 0.16012442316680073 root_mean_squared_error 0.14566533822071087 root_mean_squared_error 0.14951390539611714 root_mean_squared_error 0.15554768223291685 root_mean_squared_error 0.15466019577586854 root_mean_squared_error 0.14162382138454693 root_mean_squared_error 0.15331360638821243 root_mean_squared_error 0.1525829274165509 root_relative_squared_error 0.3406762240081109 root_relative_squared_error 0.3379121226495114 root_relative_squared_error 0.3544350860090062 root_relative_squared_error 0.32242993079829607 root_relative_squared_error 0.3309487264376447 root_relative_squared_error 0.3443794560587227 root_relative_squared_error 0.34241457880082743 root_relative_squared_error 0.31355230674756285 root_relative_squared_error 0.33943325684090864 root_relative_squared_error 0.337815548218047 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 0.9646462770961449 [0.949187,0.980106] unweighted_recall 0.9630435410111873 [0.947208,0.978879] unweighted_recall 0.9614186394619537 [0.949239,0.973599] unweighted_recall 0.9665970466831886 [0.952284,0.98091] unweighted_recall 0.963754448325203 [0.946193,0.981316] unweighted_recall 0.9576303718967327 [0.935976,0.979285] unweighted_recall 0.9595625870962203 [0.943089,0.976036] unweighted_recall 0.9665711497691744 [0.948171,0.984972] unweighted_recall 0.9632198027910417 [0.947154,0.979285] unweighted_recall 0.9587452860718697 [0.930894,0.986596] usercpu_time_millis 73193.73969301523 usercpu_time_millis 72685.73625000136 usercpu_time_millis 74121.33928399999 usercpu_time_millis 74125.30033600342 usercpu_time_millis 72413.28774997965 usercpu_time_millis 74316.28260899743 usercpu_time_millis 70821.18129100127 usercpu_time_millis 69396.51941298507 usercpu_time_millis 70254.21883701347 usercpu_time_millis 70025.4311789904 usercpu_time_millis_testing 191.45752300391905 usercpu_time_millis_testing 192.55018499097787 usercpu_time_millis_testing 204.76165099535137 usercpu_time_millis_testing 205.99332700658124 usercpu_time_millis_testing 190.30647099134512 usercpu_time_millis_testing 188.74968100863043 usercpu_time_millis_testing 197.3076770082116 usercpu_time_millis_testing 185.7125419919612 usercpu_time_millis_testing 187.40296400210354 usercpu_time_millis_testing 186.7345469945576 usercpu_time_millis_training 73002.28217001131 usercpu_time_millis_training 72493.18606501038 usercpu_time_millis_training 73916.57763300464 usercpu_time_millis_training 73919.30700899684 usercpu_time_millis_training 72222.9812789883 usercpu_time_millis_training 74127.5329279888 usercpu_time_millis_training 70623.87361399306 usercpu_time_millis_training 69210.80687099311 usercpu_time_millis_training 70066.81587301136 usercpu_time_millis_training 69838.69663199584 wall_clock_time_millis 73207.115650177 wall_clock_time_millis 72685.99915504456 wall_clock_time_millis 74122.28965759277 wall_clock_time_millis 74129.26077842712 wall_clock_time_millis 72415.85946083069 wall_clock_time_millis 74316.67494773865 wall_clock_time_millis 70822.14617729187 wall_clock_time_millis 69396.86441421509 wall_clock_time_millis 70254.55951690674 wall_clock_time_millis 70031.27694129944 wall_clock_time_millis_testing 191.46132469177246 wall_clock_time_millis_testing 192.55423545837402 wall_clock_time_millis_testing 204.76484298706055 wall_clock_time_millis_testing 205.99651336669922 wall_clock_time_millis_testing 190.31023979187012 wall_clock_time_millis_testing 188.7524127960205 wall_clock_time_millis_testing 197.3111629486084 wall_clock_time_millis_testing 185.7161521911621 wall_clock_time_millis_testing 187.40582466125488 wall_clock_time_millis_testing 186.7375373840332 wall_clock_time_millis_training 73015.65432548523 wall_clock_time_millis_training 72493.44491958618 wall_clock_time_millis_training 73917.52481460571 wall_clock_time_millis_training 73923.26426506042 wall_clock_time_millis_training 72225.54922103882 wall_clock_time_millis_training 74127.92253494263 wall_clock_time_millis_training 70624.83501434326 wall_clock_time_millis_training 69211.14826202393 wall_clock_time_millis_training 70067.15369224548 wall_clock_time_millis_training 69844.5394039154 weighted_recall 0.9712793733681462 [0.949187,0.980106] weighted_recall 0.9698288366695678 [0.947208,0.978879] weighted_recall 0.9666376559326951 [0.949239,0.973599] weighted_recall 0.9727299100667247 [0.952284,0.98091] weighted_recall 0.9712793733681462 [0.946193,0.981316] weighted_recall 0.9669181659895532 [0.935976,0.979285] weighted_recall 0.9666279744631456 [0.943089,0.976036] weighted_recall 0.9744631456761462 [0.948171,0.984972] weighted_recall 0.9701102727800348 [0.947154,0.979285] weighted_recall 0.9706906558328496 [0.930894,0.986596]