10435705 10963 Nelly Palacios 16 Supervised Classification 17488 sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=xgboost.sklearn.XGBClassifier)(1) 8259290 add_indicator false 17407 copy true 17407 fill_value -1 17407 missing_values NaN 17407 strategy "constant" 17407 verbose 0 17407 memory null 17488 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}] 17488 verbose false 17488 base_score 0.5 17489 booster "gbtree" 17489 colsample_bylevel 1 17489 colsample_bynode 1 17489 colsample_bytree 1 17489 gamma 0 17489 learning_rate 0.1 17489 max_delta_step 0 17489 max_depth 3 17489 min_child_weight 1 17489 missing null 17489 n_estimators 100 17489 n_jobs 1 17489 nthread null 17489 objective "multi:softprob" 17489 random_state 42 17489 reg_alpha 0 17489 reg_lambda 1 17489 scale_pos_weight 1 17489 seed null 17489 silent null 17489 subsample 1 17489 verbosity 1 17489 openml-python Sklearn_0.21.2. 16 mfeat-karhunen https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff -1 21794314 description https://api.openml.org/data/download/21794314/description.xml -1 21794315 predictions https://api.openml.org/data/download/21794315/predictions.arff area_under_roc_curve 0.9974958333333332 [0.999494,0.998078,0.999647,0.996469,0.997481,0.996428,0.993322,0.999469,0.99705,0.997519] average_cost 0 f_measure 0.9515387322368043 [0.98,0.948403,0.974874,0.935,0.947891,0.915423,0.959391,0.972431,0.934343,0.947631] kappa 0.9461111111111111 kb_relative_information_score 0.9302320753898171 mean_absolute_error 0.019742439177182547 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.9515 [0.98,0.965,0.97,0.935,0.955,0.92,0.945,0.97,0.925,0.95] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9517195277016945 [0.98,0.932367,0.979798,0.935,0.940887,0.910891,0.974227,0.974874,0.943878,0.945274] predictive_accuracy 0.9515 prior_entropy 3.3219280948872383 relative_absolute_error 0.10968021765101078 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.08764316158154047 root_relative_squared_error 0.29214387193846375 total_cost 0 unweighted_recall 0.9514999999999999 [0.98,0.965,0.97,0.935,0.955,0.92,0.945,0.97,0.925,0.95] area_under_roc_curve 0.9984722222222221 [0.998333,0.997778,1,0.999722,1,0.998333,0.998056,1,0.993056,0.999444] area_under_roc_curve 0.9979722222222221 [1,0.995278,1,0.994444,1,0.996111,0.9975,0.997778,0.999722,0.998889] area_under_roc_curve 0.9989444444444446 [1,0.999167,0.999722,0.9975,0.999444,0.996944,1,0.998889,0.998889,0.998889] area_under_roc_curve 0.9972777777777779 [1,0.999444,1,0.995278,0.988056,0.996667,1,1,0.999444,0.993889] area_under_roc_curve 0.9971388888888888 [1,0.996944,0.997778,0.9925,0.996389,0.991111,0.999444,1,0.997222,1] area_under_roc_curve 0.9982222222222221 [1,0.998889,1,1,0.998333,0.993611,0.998056,0.999444,0.9975,0.996389] area_under_roc_curve 0.9978888888888889 [0.998889,0.998611,1,0.998333,1,0.996667,0.999722,0.999722,0.9975,0.989444] area_under_roc_curve 0.9991111111111111 [1,1,1,0.999444,0.999444,0.999167,0.996944,1,0.996111,1] area_under_roc_curve 0.9986388888888889 [0.999722,1,0.999722,0.99,1,0.9975,1,1,0.999444,1] area_under_roc_curve 0.9941388888888889 [1,0.999722,1,0.9975,1,0.999167,0.9525,0.999167,0.995833,0.9975] 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 0.955126364863207 [0.974359,0.923077,1,0.95,1,0.95,0.95,1,0.894737,0.909091] f_measure 0.9501005092468506 [1,0.926829,1,0.9,0.974359,0.9,0.974359,0.923077,0.952381,0.95] f_measure 0.9548404783064602 [0.97561,0.974359,0.95,0.923077,0.95,0.9,1,0.947368,0.97561,0.952381] f_measure 0.9699906191369605 [0.974359,0.97561,0.97561,0.95,0.95,0.974359,0.97561,1,0.95,0.974359] f_measure 0.9201579172458654 [0.97561,0.930233,0.918919,0.871795,0.9,0.837209,0.923077,1,0.894737,0.95] f_measure 0.9548404783064603 [1,0.952381,0.97561,0.974359,0.95,0.9,0.923077,0.97561,0.95,0.947368] f_measure 0.9549286112700746 [0.974359,0.95,0.974359,0.95,0.97561,0.926829,1,0.952381,0.926829,0.918919] f_measure 0.9646596461744086 [0.97561,0.97561,0.974359,0.952381,0.952381,0.918919,0.974359,0.97561,0.947368,1] f_measure 0.9550956735616555 [0.95,0.947368,0.97561,0.95,0.909091,0.95,0.974359,1,0.918919,0.97561] f_measure 0.9349677181563619 [1,0.930233,1,0.926829,0.918919,0.904762,0.894737,0.947368,0.926829,0.9] kappa 0.95 kappa 0.9444444444444444 kappa 0.95 kappa 0.9666666666666667 kappa 0.9111111111111112 kappa 0.95 kappa 0.95 kappa 0.961111111111111 kappa 0.95 kappa 0.9277777777777778 kb_relative_information_score 0.9314789040735486 kb_relative_information_score 0.9250234062637255 kb_relative_information_score 0.92812864745158 kb_relative_information_score 0.945953948865096 kb_relative_information_score 0.9068030808897636 kb_relative_information_score 0.9313525643213602 kb_relative_information_score 0.922302160553672 kb_relative_information_score 0.9430024207083341 kb_relative_information_score 0.9421665192741608 kb_relative_information_score 0.9261091014965847 mean_absolute_error 0.019436394519753496 mean_absolute_error 0.020180409469559492 mean_absolute_error 0.02072453524592801 mean_absolute_error 0.015848657460538006 mean_absolute_error 0.025319200219875503 mean_absolute_error 0.0190454915214675 mean_absolute_error 0.022063239714688983 mean_absolute_error 0.017334693002621488 mean_absolute_error 0.017260048147578505 mean_absolute_error 0.020211722469814498 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 mean_prior_absolute_error 0.1799999999999998 number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] number_of_instances 200 [20,20,20,20,20,20,20,20,20,20] precision 0.9575146198830409 [1,0.947368,1,0.95,1,0.95,0.95,1,0.944444,0.833333] precision 0.9511221234905446 [1,0.904762,1,0.9,1,0.9,1,0.947368,0.909091,0.95] precision 0.9561221234905446 [0.952381,1,0.95,0.947368,0.95,0.9,1,1,0.952381,0.909091] precision 0.9707142857142856 [1,0.952381,0.952381,0.95,0.95,1,0.952381,1,0.95,1] precision 0.924110457302677 [0.952381,0.869565,1,0.894737,0.9,0.782609,0.947368,1,0.944444,0.95] precision 0.9561221234905445 [1,0.909091,0.952381,1,0.95,0.9,0.947368,0.952381,0.95,1] precision 0.9570995670995671 [1,0.95,1,0.95,0.952381,0.904762,1,0.909091,0.904762,1] precision 0.9675324675324675 [0.952381,0.952381,1,0.909091,0.909091,1,1,0.952381,1,1] precision 0.9588095238095238 [0.95,1,0.952381,0.95,0.833333,0.95,1,1,1,0.952381] precision 0.9387169834995922 [1,0.869565,1,0.904762,1,0.863636,0.944444,1,0.904762,0.9] predictive_accuracy 0.955 predictive_accuracy 0.95 predictive_accuracy 0.955 predictive_accuracy 0.97 predictive_accuracy 0.92 predictive_accuracy 0.955 predictive_accuracy 0.955 predictive_accuracy 0.965 predictive_accuracy 0.955 predictive_accuracy 0.935 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 prior_entropy 3.321928094887355 relative_absolute_error 0.10797996955418622 relative_absolute_error 0.11211338594199731 relative_absolute_error 0.11513630692182242 relative_absolute_error 0.08804809700298902 relative_absolute_error 0.14066222344375295 relative_absolute_error 0.10580828623037512 relative_absolute_error 0.12257355397049449 relative_absolute_error 0.09630385001456393 relative_absolute_error 0.09588915637543625 relative_absolute_error 0.11228734705452512 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_prior_squared_error 0.2999999999999998 root_mean_squared_error 0.08647879449831607 root_mean_squared_error 0.09099829904875802 root_mean_squared_error 0.08694147678825169 root_mean_squared_error 0.0756231025300345 root_mean_squared_error 0.1031484702909344 root_mean_squared_error 0.08565028368237171 root_mean_squared_error 0.09055492001705721 root_mean_squared_error 0.07671732607088817 root_mean_squared_error 0.08078436366411833 root_mean_squared_error 0.09585853264280143 root_relative_squared_error 0.28826264832772036 root_relative_squared_error 0.30332766349586027 root_relative_squared_error 0.2898049226275058 root_relative_squared_error 0.2520770084334485 root_relative_squared_error 0.3438282343031148 root_relative_squared_error 0.28550094560790584 root_relative_squared_error 0.3018497333901909 root_relative_squared_error 0.25572442023629405 root_relative_squared_error 0.2692812122137279 root_relative_squared_error 0.3195284421426716 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 0.9550000000000001 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1] unweighted_recall 0.95 [1,0.95,1,0.9,0.95,0.9,0.95,0.9,1,0.95] unweighted_recall 0.9550000000000001 [1,0.95,0.95,0.9,0.95,0.9,1,0.9,1,1] unweighted_recall 0.97 [0.95,1,1,0.95,0.95,0.95,1,1,0.95,0.95] unweighted_recall 0.9200000000000002 [1,1,0.85,0.85,0.9,0.9,0.9,1,0.85,0.95] unweighted_recall 0.9550000000000001 [1,1,1,0.95,0.95,0.9,0.9,1,0.95,0.9] unweighted_recall 0.9549999999999998 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85] unweighted_recall 0.9650000000000001 [1,1,0.95,1,1,0.85,0.95,1,0.9,1] unweighted_recall 0.9550000000000001 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1] unweighted_recall 0.9349999999999999 [1,1,1,0.95,0.85,0.95,0.85,0.9,0.95,0.9] usercpu_time_millis 5301.102793000155 usercpu_time_millis 5332.0256510000945 usercpu_time_millis 5297.54908599989 usercpu_time_millis 5299.34351299994 usercpu_time_millis 5285.119680999742 usercpu_time_millis 5327.8133640001215 usercpu_time_millis 5275.034554000058 usercpu_time_millis 5287.157053999863 usercpu_time_millis 5300.290810999968 usercpu_time_millis 5271.287406999818 usercpu_time_millis_testing 8.56788900000538 usercpu_time_millis_testing 8.616989000074682 usercpu_time_millis_testing 8.77250999997159 usercpu_time_millis_testing 8.720895999886125 usercpu_time_millis_testing 8.745649999809757 usercpu_time_millis_testing 8.703542000148445 usercpu_time_millis_testing 8.597333000125218 usercpu_time_millis_testing 8.601054999871849 usercpu_time_millis_testing 8.698847999994541 usercpu_time_millis_testing 8.555488999945737 usercpu_time_millis_training 5292.534904000149 usercpu_time_millis_training 5323.40866200002 usercpu_time_millis_training 5288.776575999918 usercpu_time_millis_training 5290.622617000054 usercpu_time_millis_training 5276.374030999932 usercpu_time_millis_training 5319.109821999973 usercpu_time_millis_training 5266.437220999933 usercpu_time_millis_training 5278.555998999991 usercpu_time_millis_training 5291.5919629999735 usercpu_time_millis_training 5262.731917999872 wall_clock_time_millis 5309.80920791626 wall_clock_time_millis 5335.055112838745 wall_clock_time_millis 5297.715187072754 wall_clock_time_millis 5299.41201210022 wall_clock_time_millis 5285.897493362427 wall_clock_time_millis 5327.876329421997 wall_clock_time_millis 5275.138378143311 wall_clock_time_millis 5287.568092346191 wall_clock_time_millis 5300.51851272583 wall_clock_time_millis 5271.34370803833 wall_clock_time_millis_testing 8.571147918701172 wall_clock_time_millis_testing 8.619308471679688 wall_clock_time_millis_testing 8.775711059570312 wall_clock_time_millis_testing 8.72349739074707 wall_clock_time_millis_testing 8.749008178710938 wall_clock_time_millis_testing 8.70656967163086 wall_clock_time_millis_testing 8.59975814819336 wall_clock_time_millis_testing 8.603572845458984 wall_clock_time_millis_testing 8.701562881469727 wall_clock_time_millis_testing 8.558034896850586 wall_clock_time_millis_training 5301.238059997559 wall_clock_time_millis_training 5326.435804367065 wall_clock_time_millis_training 5288.939476013184 wall_clock_time_millis_training 5290.688514709473 wall_clock_time_millis_training 5277.148485183716 wall_clock_time_millis_training 5319.169759750366 wall_clock_time_millis_training 5266.538619995117 wall_clock_time_millis_training 5278.964519500732 wall_clock_time_millis_training 5291.81694984436 wall_clock_time_millis_training 5262.7856731414795 weighted_recall 0.955 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1] weighted_recall 0.95 [1,0.95,1,0.9,0.95,0.9,0.95,0.9,1,0.95] weighted_recall 0.955 [1,0.95,0.95,0.9,0.95,0.9,1,0.9,1,1] weighted_recall 0.97 [0.95,1,1,0.95,0.95,0.95,1,1,0.95,0.95] weighted_recall 0.92 [1,1,0.85,0.85,0.9,0.9,0.9,1,0.85,0.95] weighted_recall 0.955 [1,1,1,0.95,0.95,0.9,0.9,1,0.95,0.9] weighted_recall 0.955 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85] weighted_recall 0.965 [1,1,0.95,1,1,0.85,0.95,1,0.9,1] weighted_recall 0.955 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1] weighted_recall 0.935 [1,1,1,0.95,0.85,0.95,0.85,0.9,0.95,0.9]