10437824 11497 Fares Gaaloul 35 Supervised Classification predictive_accuracy 17593 sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier)(2) 8260898 copy true 17467 fill_value null 17467 missing_values NaN 17467 strategy "constant" 17467 verbose 0 17467 bootstrap true 17478 class_weight null 17478 criterion "gini" 17478 max_depth null 17478 max_features "auto" 17478 max_leaf_nodes null 17478 min_impurity_decrease 0.0 17478 min_impurity_split null 17478 min_samples_leaf 1 17478 min_samples_split 2 17478 min_weight_fraction_leaf 0.0 17478 n_estimators 100 17478 n_jobs null 17478 oob_score false 17478 random_state 31461 17478 verbose 0 17478 warm_start false 17478 memory null 17593 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "Imputer", "step_name": "Imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "fs", "step_name": "fs"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "rf", "step_name": "rf"}}] 17593 percentile 80 17594 score_func {"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_classif"} 17594 openml-python Sklearn_0.20.3. 35 dermatology https://www.openml.org/data/download/35/dataset_35_dermatology.arff -1 21800001 description https://api.openml.org/data/download/21800001/description.xml -1 21800002 predictions https://api.openml.org/data/download/21800002/predictions.arff area_under_roc_curve 0.9991492710116312 [1,0.99699,1,0.997393,1,1] average_cost 0 f_measure 0.9753004004657782 [0.99115,0.934426,1,0.927835,1,0.974359] kappa 0.9691708704970657 kb_relative_information_score 0.9355860032823 mean_absolute_error 0.02822404371584699 mean_prior_absolute_error 0.2664473039935758 weighted_recall 0.9754098360655737 [1,0.934426,1,0.918367,1,0.95] number_of_instances 366 [112,61,72,49,52,20] precision 0.9753349391237657 [0.982456,0.934426,1,0.9375,1,1] predictive_accuracy 0.9754098360655737 prior_entropy 2.432654569700141 relative_absolute_error 0.10592730079388414 root_mean_prior_squared_error 0.3648729603686826 root_mean_squared_error 0.0893117786572504 root_relative_squared_error 0.2447749994052892 total_cost 0 unweighted_recall 0.967132262741162 [1,0.934426,1,0.918367,1,0.95] area_under_roc_curve 1 [1,1,1,1,1,1] area_under_roc_curve 0.9973844812554491 [1,0.983871,1,1,1,1] area_under_roc_curve 1 [1,1,1,1,1,1] area_under_roc_curve 0.9982835658238884 [1,0.994624,1,0.99375,1,1] area_under_roc_curve 1 [1,1,1,1,1,1] area_under_roc_curve 1 [1,1,1,1,1,1] area_under_roc_curve 1 [1,1,1,1,1,1] area_under_roc_curve 1 [1,1,1,1,1,1] area_under_roc_curve 0.9954301075268818 [1,0.983333,1,0.987097,1,1] area_under_roc_curve 1 [1,1,1,1,1,1] 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 0.9725109725109725 [1,0.923077,1,0.888889,1,1] f_measure 0.9725109725109725 [1,0.923077,1,0.888889,1,1] f_measure 0.9690560125342734 [0.956522,1,1,1,1,0.666667] f_measure 0.9725109725109725 [1,0.923077,1,0.888889,1,1] f_measure 0.972972972972973 [1,0.909091,1,0.909091,1,1] f_measure 0.9731619731619732 [1,0.923077,1,0.909091,1,1] f_measure 0.9715634606938954 [0.956522,0.909091,1,1,1,1] f_measure 1 [1,1,1,1,1,1] f_measure 0.9444444444444444 [1,0.833333,1,0.8,1,1] f_measure 1 [1,1,1,1,1,1] kappa 0.9662716499544212 kappa 0.9661482159194877 kappa 0.9658986175115208 kappa 0.9658986175115208 kappa 0.9659613615455382 kappa 0.9663023679417123 kappa 0.965082444228904 kappa 1 kappa 0.9305019305019304 kappa 1 kb_relative_information_score 0.9358356478023357 kb_relative_information_score 0.9335759217774374 kb_relative_information_score 0.9181815076630646 kb_relative_information_score 0.9365674005328526 kb_relative_information_score 0.9380759707333162 kb_relative_information_score 0.9515931792975197 kb_relative_information_score 0.9430012127805351 kb_relative_information_score 0.9404229983937604 kb_relative_information_score 0.8910146156982663 kb_relative_information_score 0.9675944876427722 mean_absolute_error 0.029549549549549546 mean_absolute_error 0.026306306306306315 mean_absolute_error 0.03468468468468469 mean_absolute_error 0.02783783783783783 mean_absolute_error 0.027387387387387385 mean_absolute_error 0.02288288288288288 mean_absolute_error 0.02546296296296297 mean_absolute_error 0.028888888888888895 mean_absolute_error 0.04314814814814816 mean_absolute_error 0.01611111111111111 mean_prior_absolute_error 0.26707352513804133 mean_prior_absolute_error 0.2665891698149763 mean_prior_absolute_error 0.2665891698149763 mean_prior_absolute_error 0.2656204591688463 mean_prior_absolute_error 0.2656204591688463 mean_prior_absolute_error 0.2668555652426621 mean_prior_absolute_error 0.26655217045002 mean_prior_absolute_error 0.26655217045002 mean_prior_absolute_error 0.26655217045002 mean_prior_absolute_error 0.2664774990043808 number_of_instances 37 [11,6,7,5,6,2] number_of_instances 37 [11,6,8,5,5,2] number_of_instances 37 [11,6,8,5,5,2] number_of_instances 37 [12,6,7,5,5,2] number_of_instances 37 [12,6,7,5,5,2] number_of_instances 37 [11,7,7,5,5,2] number_of_instances 36 [11,6,7,5,5,2] number_of_instances 36 [11,6,7,5,5,2] number_of_instances 36 [11,6,7,5,5,2] number_of_instances 36 [11,6,7,4,6,2] precision 0.9768339768339768 [1,0.857143,1,1,1,1] precision 0.9768339768339768 [1,0.857143,1,1,1,1] precision 0.9752252252252251 [0.916667,1,1,1,1,1] precision 0.9768339768339768 [1,0.857143,1,1,1,1] precision 0.9774774774774776 [1,1,1,0.833333,1,1] precision 0.9774774774774776 [1,1,1,0.833333,1,1] precision 0.9745370370370369 [0.916667,1,1,1,1,1] precision 1 [1,1,1,1,1,1] precision 0.9444444444444444 [1,0.833333,1,0.8,1,1] precision 1 [1,1,1,1,1,1] predictive_accuracy 0.9729729729729729 predictive_accuracy 0.9729729729729729 predictive_accuracy 0.9729729729729729 predictive_accuracy 0.9729729729729729 predictive_accuracy 0.9729729729729729 predictive_accuracy 0.9729729729729729 predictive_accuracy 0.9722222222222223 predictive_accuracy 1 predictive_accuracy 0.9444444444444444 predictive_accuracy 1 prior_entropy 2.4459870034632 prior_entropy 2.4335031087519345 prior_entropy 2.4335031087519345 prior_entropy 2.416466503250984 prior_entropy 2.416466503250984 prior_entropy 2.4398714397922903 prior_entropy 2.435841132544266 prior_entropy 2.435841132544266 prior_entropy 2.435841132544266 prior_entropy 2.4335060140779197 relative_absolute_error 0.11064200217627851 relative_absolute_error 0.09867732558139534 relative_absolute_error 0.13010537790697674 relative_absolute_error 0.1048030634573304 relative_absolute_error 0.10310722100656453 relative_absolute_error 0.08575006806425263 relative_absolute_error 0.09552712671584647 relative_absolute_error 0.10837986740125126 relative_absolute_error 0.1618750583621253 relative_absolute_error 0.0604595553895012 root_mean_prior_squared_error 0.36573008948221786 root_mean_prior_squared_error 0.3650673130117323 root_mean_prior_squared_error 0.3650673130117323 root_mean_prior_squared_error 0.36373813710343333 root_mean_prior_squared_error 0.36373813710343333 root_mean_prior_squared_error 0.3654319888259535 root_mean_prior_squared_error 0.3650166347779916 root_mean_prior_squared_error 0.3650166347779916 root_mean_prior_squared_error 0.3650166347779916 root_mean_prior_squared_error 0.3649143354528711 root_mean_squared_error 0.09071785783256639 root_mean_squared_error 0.0956344391207788 root_mean_squared_error 0.09835585327713788 root_mean_squared_error 0.08963891529428017 root_mean_squared_error 0.08334234185542153 root_mean_squared_error 0.07495944849662996 root_mean_squared_error 0.08129165598838133 root_mean_squared_error 0.07409328454600198 root_mean_squared_error 0.1308129849710534 root_mean_squared_error 0.05396329342281694 root_relative_squared_error 0.24804592359627872 root_relative_squared_error 0.2619638508082628 root_relative_squared_error 0.269418405240726 root_relative_squared_error 0.24643804471014338 root_relative_squared_error 0.22912731262964084 root_relative_squared_error 0.20512557955710697 root_relative_squared_error 0.22270671592220473 root_relative_squared_error 0.2029860490907944 root_relative_squared_error 0.3583754067828053 root_relative_squared_error 0.14787934641111497 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 0.9666666666666667 [1,1,1,0.8,1,1] unweighted_recall 0.9666666666666667 [1,1,1,0.8,1,1] unweighted_recall 0.9166666666666666 [1,1,1,1,1,0.5] unweighted_recall 0.9666666666666667 [1,1,1,0.8,1,1] unweighted_recall 0.9722222222222223 [1,0.833333,1,1,1,1] unweighted_recall 0.9761904761904763 [1,0.857143,1,1,1,1] unweighted_recall 0.9722222222222223 [1,0.833333,1,1,1,1] unweighted_recall 1 [1,1,1,1,1,1] unweighted_recall 0.938888888888889 [1,0.833333,1,0.8,1,1] unweighted_recall 1 [1,1,1,1,1,1] usercpu_time_millis 112.24447699999995 usercpu_time_millis 109.20125000000081 usercpu_time_millis 108.32854900000032 usercpu_time_millis 110.26640600000005 usercpu_time_millis 111.8374830000004 usercpu_time_millis 108.51104199999995 usercpu_time_millis 112.17435799999987 usercpu_time_millis 119.8005550000003 usercpu_time_millis 113.36998100000083 usercpu_time_millis 108.5822900000002 usercpu_time_millis_testing 5.559814999999801 usercpu_time_millis_testing 5.265407000000444 usercpu_time_millis_testing 5.112720000000515 usercpu_time_millis_testing 5.0301070000005055 usercpu_time_millis_testing 5.158050000000358 usercpu_time_millis_testing 5.430389999999896 usercpu_time_millis_testing 5.04270600000023 usercpu_time_millis_testing 5.086979999999741 usercpu_time_millis_testing 5.128936000000195 usercpu_time_millis_testing 4.988379999999459 usercpu_time_millis_training 106.68466200000015 usercpu_time_millis_training 103.93584300000036 usercpu_time_millis_training 103.21582899999981 usercpu_time_millis_training 105.23629899999953 usercpu_time_millis_training 106.67943300000005 usercpu_time_millis_training 103.08065200000004 usercpu_time_millis_training 107.13165199999963 usercpu_time_millis_training 114.71357500000056 usercpu_time_millis_training 108.24104500000064 usercpu_time_millis_training 103.59391000000073 wall_clock_time_millis 112.55288124084473 wall_clock_time_millis 110.0614070892334 wall_clock_time_millis 108.56342315673828 wall_clock_time_millis 110.9015941619873 wall_clock_time_millis 111.95778846740723 wall_clock_time_millis 108.59274864196777 wall_clock_time_millis 112.28132247924805 wall_clock_time_millis 119.81391906738281 wall_clock_time_millis 113.53421211242676 wall_clock_time_millis 108.7028980255127 wall_clock_time_millis_testing 5.562543869018555 wall_clock_time_millis_testing 5.269050598144531 wall_clock_time_millis_testing 5.115985870361328 wall_clock_time_millis_testing 5.0334930419921875 wall_clock_time_millis_testing 5.161523818969727 wall_clock_time_millis_testing 5.433797836303711 wall_clock_time_millis_testing 5.045175552368164 wall_clock_time_millis_testing 5.0907135009765625 wall_clock_time_millis_testing 5.13148307800293 wall_clock_time_millis_testing 4.990816116333008 wall_clock_time_millis_training 106.99033737182617 wall_clock_time_millis_training 104.79235649108887 wall_clock_time_millis_training 103.44743728637695 wall_clock_time_millis_training 105.86810111999512 wall_clock_time_millis_training 106.7962646484375 wall_clock_time_millis_training 103.15895080566406 wall_clock_time_millis_training 107.23614692687988 wall_clock_time_millis_training 114.72320556640625 wall_clock_time_millis_training 108.40272903442383 wall_clock_time_millis_training 103.71208190917969 weighted_recall 0.972972972972973 [1,1,1,0.8,1,1] weighted_recall 0.972972972972973 [1,1,1,0.8,1,1] weighted_recall 0.972972972972973 [1,1,1,1,1,0.5] weighted_recall 0.972972972972973 [1,1,1,0.8,1,1] weighted_recall 0.972972972972973 [1,0.833333,1,1,1,1] weighted_recall 0.972972972972973 [1,0.857143,1,1,1,1] weighted_recall 0.9722222222222222 [1,0.833333,1,1,1,1] weighted_recall 1 [1,1,1,1,1,1] weighted_recall 0.9444444444444444 [1,0.833333,1,0.8,1,1] weighted_recall 1 [1,1,1,1,1,1]