10543468 8323 Heinrich Peters 16 Supervised Classification 18601 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2) 8275618 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "median" 12737 verbose 0 12737 C 0.001 13106 class_weight null 13106 dual false 13106 fit_intercept true 13106 intercept_scaling 1 13106 l1_ratio null 13106 max_iter 10000 13106 multi_class "warn" 13106 n_jobs null 13106 penalty "l2" 13106 random_state 1 13106 solver "lbfgs" 13106 tol 0.0001 13106 verbose 0 13106 warm_start false 13106 copy true 13294 with_mean true 13294 with_std true 13294 memory null 18601 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "logisticregression", "step_name": "logisticregression"}}] 18601 verbose false 18601 openml-python Sklearn_0.21.2. 16 mfeat-karhunen https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff -1 22011891 description https://api.openml.org/data/download/22011891/description.xml -1 22011892 predictions https://api.openml.org/data/download/22011892/predictions.arff area_under_roc_curve 0.9865999999999999 [0.991,0.989642,0.998164,0.980353,0.994636,0.979622,0.988378,0.994208,0.963781,0.986217] average_cost 0 f_measure 0.9105341774155947 [0.955665,0.894472,0.960591,0.913706,0.902148,0.904884,0.891041,0.925373,0.858696,0.898765] kappa 0.9011111111111112 kb_relative_information_score 0.4734562504449616 mean_absolute_error 0.13754863263475314 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.911 [0.97,0.89,0.975,0.9,0.945,0.88,0.92,0.93,0.79,0.91] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.9122328007937572 [0.941748,0.89899,0.946602,0.927835,0.863014,0.931217,0.86385,0.920792,0.940476,0.887805] predictive_accuracy 0.9109999999999999 prior_entropy 3.3219280948872383 relative_absolute_error 0.7641590701930495 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.23395034266437081 root_relative_squared_error 0.7798344755478908 total_cost 0 unweighted_recall 0.9109999999999999 [0.97,0.89,0.975,0.9,0.945,0.88,0.92,0.93,0.79,0.91] area_under_roc_curve 0.9825000000000002 [0.977222,0.995278,1,0.990278,0.998889,0.948056,0.991667,0.999167,0.925556,0.998889] area_under_roc_curve 0.9858333333333333 [1,0.953333,0.998333,0.986111,0.982778,0.988056,0.989167,0.999167,0.971389,0.99] area_under_roc_curve 0.9887777777777776 [0.998056,0.9925,1,0.981389,1,0.985278,0.996111,0.973333,0.981389,0.979722] area_under_roc_curve 0.9850000000000001 [0.985,0.999167,1,0.969444,0.998889,0.946667,0.992778,0.998889,0.996667,0.9625] area_under_roc_curve 0.9826388888888888 [0.998333,0.989167,0.988333,0.973056,0.9975,0.993889,0.980556,0.988333,0.926944,0.990278] area_under_roc_curve 0.9888055555555555 [0.999444,0.991389,1,0.973333,0.990833,0.987778,0.995,0.997222,0.983056,0.97] area_under_roc_curve 0.9891666666666667 [0.961111,0.993611,0.996944,0.998889,0.992222,0.989444,0.998611,0.997778,0.964722,0.998333] area_under_roc_curve 0.9855555555555555 [0.989722,0.989167,0.999722,0.994167,0.996389,0.981389,0.990278,1,0.921389,0.993333] area_under_roc_curve 0.9919444444444443 [0.996111,0.993333,1,0.965556,0.999722,0.994167,0.994444,0.998611,0.985,0.9925] area_under_roc_curve 0.983888888888889 [1,0.996389,1,0.97,0.989167,0.980556,0.954167,0.991111,0.978889,0.978611] 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 0.8954917541807786 [0.904762,0.9,0.97561,0.9,0.909091,0.923077,0.878049,0.95,0.6875,0.926829] f_measure 0.9152530599555706 [0.97561,0.864865,0.974359,0.918919,0.878049,0.878049,0.883721,0.904762,0.947368,0.926829] f_measure 0.9096127265497658 [0.904762,0.926829,0.930233,0.923077,0.95,0.871795,0.95,0.918919,0.820513,0.9] f_measure 0.9352430026114236 [0.95,0.95,0.952381,0.947368,0.974359,0.871795,0.909091,0.974359,0.923077,0.9] f_measure 0.8793273894923823 [0.97561,0.857143,0.926829,0.85,0.926829,0.833333,0.8,0.9,0.823529,0.9] f_measure 0.8988900706323161 [0.930233,0.871795,0.97561,0.947368,0.904762,0.926829,0.894737,0.883721,0.833333,0.820513] f_measure 0.921859439992207 [0.974359,0.894737,0.974359,0.97561,0.808511,0.947368,0.904762,0.95,0.888889,0.9] f_measure 0.914985983783488 [0.974359,0.85,0.95,0.9,0.883721,0.918919,0.926829,0.952381,0.888889,0.904762] f_measure 0.9300561911344967 [0.974359,0.926829,0.97561,0.904762,0.926829,0.923077,0.974359,0.9,0.894737,0.9] f_measure 0.905204145448048 [1,0.9,0.974359,0.871795,0.878049,0.95,0.8,0.923077,0.85,0.904762] kappa 0.888888888888889 kappa 0.9055555555555556 kappa 0.9 kappa 0.9277777777777778 kappa 0.8666666666666667 kappa 0.888888888888889 kappa 0.9111111111111112 kappa 0.9055555555555556 kappa 0.9222222222222223 kappa 0.8944444444444445 kb_relative_information_score 0.47356463930681586 kb_relative_information_score 0.4695747206178785 kb_relative_information_score 0.47384909362081035 kb_relative_information_score 0.4869346667010705 kb_relative_information_score 0.4605290672921471 kb_relative_information_score 0.4658106668423779 kb_relative_information_score 0.47751680846184885 kb_relative_information_score 0.47871838042844905 kb_relative_information_score 0.4816790553583089 kb_relative_information_score 0.46638540581973664 mean_absolute_error 0.13706365828875827 mean_absolute_error 0.1378705954619558 mean_absolute_error 0.1377723323211303 mean_absolute_error 0.1359210618564244 mean_absolute_error 0.13892611354010576 mean_absolute_error 0.13850730056739852 mean_absolute_error 0.13734733606524846 mean_absolute_error 0.13693058292590668 mean_absolute_error 0.13681578815239007 mean_absolute_error 0.13833155716821582 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 0.902529049897471 [0.863636,0.9,0.952381,0.9,0.833333,0.947368,0.857143,0.95,0.916667,0.904762] precision 0.920232836217491 [0.952381,0.941176,1,1,0.857143,0.857143,0.826087,0.863636,1,0.904762] precision 0.9122174012105362 [0.863636,0.904762,0.869565,0.947368,0.95,0.894737,0.95,1,0.842105,0.9] precision 0.9384529505582136 [0.95,0.95,0.909091,1,1,0.894737,0.833333,1,0.947368,0.9] precision 0.888758658008658 [0.952381,0.818182,0.904762,0.85,0.904762,0.9375,0.72,0.9,1,0.9] precision 0.9035217944399867 [0.869565,0.894737,0.952381,1,0.863636,0.904762,0.944444,0.826087,0.9375,0.842105] precision 0.9314165464165464 [1,0.944444,1,0.952381,0.703704,1,0.863636,0.95,1,0.9] precision 0.9203576134010918 [1,0.85,0.95,0.9,0.826087,1,0.904762,0.909091,1,0.863636] precision 0.9317353991038202 [1,0.904762,0.952381,0.863636,0.904762,0.947368,1,0.9,0.944444,0.9] precision 0.9062884483937116 [1,0.9,1,0.894737,0.857143,0.95,0.8,0.947368,0.85,0.863636] predictive_accuracy 0.9 predictive_accuracy 0.915 predictive_accuracy 0.91 predictive_accuracy 0.935 predictive_accuracy 0.88 predictive_accuracy 0.9 predictive_accuracy 0.92 predictive_accuracy 0.915 predictive_accuracy 0.93 predictive_accuracy 0.905 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 0.76146476827088 relative_absolute_error 0.7659477525664219 relative_absolute_error 0.7654018462285025 relative_absolute_error 0.7551170103134698 relative_absolute_error 0.7718117418894773 relative_absolute_error 0.7694850031522149 relative_absolute_error 0.7630407559180479 relative_absolute_error 0.7607254606994824 relative_absolute_error 0.7600877119577234 relative_absolute_error 0.7685086509345332 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 0.2334543225466831 root_mean_squared_error 0.23483110281807174 root_mean_squared_error 0.2340350942408043 root_mean_squared_error 0.23089648069755586 root_mean_squared_error 0.23647850592742986 root_mean_squared_error 0.23535631380672492 root_mean_squared_error 0.23351573340460272 root_mean_squared_error 0.23309742403723058 root_mean_squared_error 0.2321994326127409 root_mean_squared_error 0.23558478105799624 root_relative_squared_error 0.7781810751556109 root_relative_squared_error 0.7827703427269063 root_relative_squared_error 0.7801169808026814 root_relative_squared_error 0.7696549356585201 root_relative_squared_error 0.7882616864247667 root_relative_squared_error 0.7845210460224169 root_relative_squared_error 0.7783857780153428 root_relative_squared_error 0.7769914134574357 root_relative_squared_error 0.7739981087091369 root_relative_squared_error 0.7852826035266546 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 0.9 [0.95,0.9,1,0.9,1,0.9,0.9,0.95,0.55,0.95] unweighted_recall 0.915 [1,0.8,0.95,0.85,0.9,0.9,0.95,0.95,0.9,0.95] unweighted_recall 0.9099999999999999 [0.95,0.95,1,0.9,0.95,0.85,0.95,0.85,0.8,0.9] unweighted_recall 0.9349999999999999 [0.95,0.95,1,0.9,0.95,0.85,1,0.95,0.9,0.9] unweighted_recall 0.8800000000000001 [1,0.9,0.95,0.85,0.95,0.75,0.9,0.9,0.7,0.9] unweighted_recall 0.9 [1,0.85,1,0.9,0.95,0.95,0.85,0.95,0.75,0.8] unweighted_recall 0.9200000000000002 [0.95,0.85,0.95,1,0.95,0.9,0.95,0.95,0.8,0.9] unweighted_recall 0.9149999999999998 [0.95,0.85,0.95,0.9,0.95,0.85,0.95,1,0.8,0.95] unweighted_recall 0.93 [0.95,0.95,1,0.95,0.95,0.9,0.95,0.9,0.85,0.9] unweighted_recall 0.9049999999999999 [1,0.9,0.95,0.85,0.9,0.95,0.8,0.9,0.85,0.95] usercpu_time_millis 80.38470096653327 usercpu_time_millis 80.87949999026023 usercpu_time_millis 77.96121900901198 usercpu_time_millis 73.1551100325305 usercpu_time_millis 72.04275598633103 usercpu_time_millis 72.18896396807395 usercpu_time_millis 72.17425899580121 usercpu_time_millis 76.23725599842146 usercpu_time_millis 72.29223303147592 usercpu_time_millis 72.20132197835483 usercpu_time_millis_testing 0.8264939824584872 usercpu_time_millis_testing 0.8516239759046584 usercpu_time_millis_testing 0.772833009250462 usercpu_time_millis_testing 0.8213380060624331 usercpu_time_millis_testing 0.8035639766603708 usercpu_time_millis_testing 0.7674709777347744 usercpu_time_millis_testing 0.7235149969346821 usercpu_time_millis_testing 0.8278960012830794 usercpu_time_millis_testing 0.7848460227251053 usercpu_time_millis_testing 0.7706479809712619 usercpu_time_millis_training 79.55820698407479 usercpu_time_millis_training 80.02787601435557 usercpu_time_millis_training 77.18838599976152 usercpu_time_millis_training 72.33377202646807 usercpu_time_millis_training 71.23919200967066 usercpu_time_millis_training 71.42149299033917 usercpu_time_millis_training 71.45074399886653 usercpu_time_millis_training 75.40935999713838 usercpu_time_millis_training 71.50738700875081 usercpu_time_millis_training 71.43067399738356 wall_clock_time_millis 80.39140701293945 wall_clock_time_millis 80.88374137878418 wall_clock_time_millis 77.97098159790039 wall_clock_time_millis 73.16112518310547 wall_clock_time_millis 72.04961776733398 wall_clock_time_millis 72.19386100769043 wall_clock_time_millis 72.18003273010254 wall_clock_time_millis 76.24506950378418 wall_clock_time_millis 72.29876518249512 wall_clock_time_millis 72.20959663391113 wall_clock_time_millis_testing 0.8337497711181641 wall_clock_time_millis_testing 0.8552074432373047 wall_clock_time_millis_testing 0.7793903350830078 wall_clock_time_millis_testing 0.8268356323242188 wall_clock_time_millis_testing 0.8101463317871094 wall_clock_time_millis_testing 0.7736682891845703 wall_clock_time_millis_testing 0.7266998291015625 wall_clock_time_millis_testing 0.8323192596435547 wall_clock_time_millis_testing 0.7913112640380859 wall_clock_time_millis_testing 0.7770061492919922 wall_clock_time_millis_training 79.55765724182129 wall_clock_time_millis_training 80.02853393554688 wall_clock_time_millis_training 77.19159126281738 wall_clock_time_millis_training 72.33428955078125 wall_clock_time_millis_training 71.23947143554688 wall_clock_time_millis_training 71.42019271850586 wall_clock_time_millis_training 71.45333290100098 wall_clock_time_millis_training 75.41275024414062 wall_clock_time_millis_training 71.50745391845703 wall_clock_time_millis_training 71.43259048461914 weighted_recall 0.9 [0.95,0.9,1,0.9,1,0.9,0.9,0.95,0.55,0.95] weighted_recall 0.915 [1,0.8,0.95,0.85,0.9,0.9,0.95,0.95,0.9,0.95] weighted_recall 0.91 [0.95,0.95,1,0.9,0.95,0.85,0.95,0.85,0.8,0.9] weighted_recall 0.935 [0.95,0.95,1,0.9,0.95,0.85,1,0.95,0.9,0.9] weighted_recall 0.88 [1,0.9,0.95,0.85,0.95,0.75,0.9,0.9,0.7,0.9] weighted_recall 0.9 [1,0.85,1,0.9,0.95,0.95,0.85,0.95,0.75,0.8] weighted_recall 0.92 [0.95,0.85,0.95,1,0.95,0.9,0.95,0.95,0.8,0.9] weighted_recall 0.915 [0.95,0.85,0.95,0.9,0.95,0.85,0.95,1,0.8,0.95] weighted_recall 0.93 [0.95,0.95,1,0.95,0.95,0.9,0.95,0.9,0.85,0.9] weighted_recall 0.905 [1,0.9,0.95,0.85,0.9,0.95,0.8,0.9,0.85,0.95]