10557692 8323 Heinrich Peters 14 Supervised Classification 18591 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(1) 8275574 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 "median" 17407 verbose 0 17407 C 0.001 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 memory null 18591 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"}}] 18591 verbose false 18591 openml-python Sklearn_0.21.2. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 22040344 description https://api.openml.org/data/download/22040344/description.xml -1 22040345 predictions https://api.openml.org/data/download/22040345/predictions.arff area_under_roc_curve 0.9551936111111111 [0.999756,0.916325,0.988911,0.979239,0.918992,0.987464,0.903592,0.981203,0.979831,0.896625] average_cost 0 f_measure 0.7563822809066966 [0.982278,0.704301,0.913151,0.836735,0.685237,0.839002,0.484375,0.783599,0.874439,0.460705] kappa 0.7366666666666667 kb_relative_information_score 0.41425616059560866 mean_absolute_error 0.1434100551188661 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.763 [0.97,0.655,0.92,0.82,0.615,0.925,0.465,0.86,0.975,0.425] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.7579031631120215 [0.994872,0.761628,0.906404,0.854167,0.773585,0.767635,0.505435,0.719665,0.792683,0.502959] predictive_accuracy 0.763 prior_entropy 3.3219280948872383 relative_absolute_error 0.7967225284381203 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.24630010740918373 root_relative_squared_error 0.8210003580305998 total_cost 0 unweighted_recall 0.7629999999999999 [0.97,0.655,0.92,0.82,0.615,0.925,0.465,0.86,0.975,0.425] area_under_roc_curve 0.9580833333333334 [0.9975,0.916111,0.993889,0.984444,0.939444,0.997222,0.835278,0.981111,0.995556,0.940278] area_under_roc_curve 0.9536666666666668 [1,0.911389,0.976667,0.990833,0.883611,0.992222,0.932222,0.980833,0.966111,0.902778] area_under_roc_curve 0.950388888888889 [1,0.914444,0.991944,0.958056,0.915556,0.991944,0.905,0.960833,0.998889,0.867222] area_under_roc_curve 0.9571111111111111 [0.999722,0.893056,0.998889,0.9925,0.978056,0.990556,0.905,0.964444,0.948056,0.900833] area_under_roc_curve 0.9526666666666667 [1,0.866389,0.985833,0.961944,0.915278,0.988333,0.903889,0.986944,1,0.918056] area_under_roc_curve 0.9592222222222223 [1,0.915,0.995833,0.973611,0.919444,0.981389,0.924444,0.991389,1,0.891111] area_under_roc_curve 0.9597222222222221 [1,0.921111,0.994722,0.985,0.904167,0.965278,0.96,0.992222,0.996667,0.878056] area_under_roc_curve 0.9649722222222222 [1,0.948333,0.989444,0.995,0.8875,0.994444,0.917222,0.986944,0.993333,0.9375] area_under_roc_curve 0.9609722222222223 [1,0.909444,0.999167,0.987222,0.943333,0.975556,0.918333,0.989444,0.998889,0.888333] area_under_roc_curve 0.9421666666666666 [1,0.974444,0.961667,0.963611,0.915278,0.994444,0.860556,0.985556,0.909444,0.856667] 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 0.713862173647613 [0.947368,0.736842,0.809524,0.8,0.833333,0.904762,0.243902,0.682927,0.816327,0.363636] f_measure 0.7689511030974445 [1,0.628571,0.926829,0.871795,0.666667,0.844444,0.615385,0.727273,0.844444,0.564103] f_measure 0.7648332343783593 [0.947368,0.684211,0.923077,0.761905,0.736842,0.8,0.540541,0.829268,0.869565,0.555556] f_measure 0.7683789855155684 [0.974359,0.588235,0.974359,0.857143,0.7,0.863636,0.611111,0.744186,0.844444,0.526316] f_measure 0.7352998954188987 [1,0.594595,0.894737,0.829268,0.611111,0.75,0.55,0.755556,0.930233,0.4375] f_measure 0.7551286831721614 [1,0.777778,0.952381,0.8,0.648649,0.826087,0.342857,0.844444,0.909091,0.45] f_measure 0.7672198200689314 [1,0.702703,0.947368,0.878049,0.666667,0.818182,0.619048,0.808511,0.909091,0.322581] f_measure 0.7687470590233297 [0.95,0.769231,0.926829,0.820513,0.625,0.857143,0.55814,0.782609,0.883721,0.514286] f_measure 0.782270473171636 [1,0.769231,0.952381,0.864865,0.611111,0.818182,0.4375,0.883721,0.952381,0.533333] f_measure 0.7337493942371991 [1,0.769231,0.829268,0.888889,0.742857,0.926829,0.307692,0.772727,0.8,0.3] kappa 0.6888888888888889 kappa 0.75 kappa 0.7444444444444445 kappa 0.75 kappa 0.7166666666666667 kappa 0.7388888888888889 kappa 0.7555555555555555 kappa 0.75 kappa 0.7666666666666667 kappa 0.7055555555555556 kb_relative_information_score 0.4065724111322051 kb_relative_information_score 0.4216319465804031 kb_relative_information_score 0.40352807525430145 kb_relative_information_score 0.4144503080784711 kb_relative_information_score 0.4101194397007455 kb_relative_information_score 0.4208296628710604 kb_relative_information_score 0.4217306103207285 kb_relative_information_score 0.42781441965902445 kb_relative_information_score 0.41284486250973473 kb_relative_information_score 0.40303986984926593 mean_absolute_error 0.144281107142696 mean_absolute_error 0.1423560831915366 mean_absolute_error 0.14499988440908987 mean_absolute_error 0.14368046717330943 mean_absolute_error 0.14340496074077405 mean_absolute_error 0.14228711231332158 mean_absolute_error 0.14256157612159773 mean_absolute_error 0.14245125498937192 mean_absolute_error 0.14383620182420845 mean_absolute_error 0.14424190328275358 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 0.7207596952855573 [1,0.777778,0.772727,0.8,0.9375,0.863636,0.238095,0.666667,0.689655,0.461538] precision 0.7776178908810486 [1,0.733333,0.904762,0.894737,0.846154,0.76,0.631579,0.666667,0.76,0.578947] precision 0.7686631021197584 [1,0.722222,0.947368,0.727273,0.777778,0.72,0.588235,0.809524,0.769231,0.625] precision 0.7722841928602797 [1,0.714286,1,0.818182,0.7,0.791667,0.6875,0.695652,0.76,0.555556] precision 0.7414282771079447 [1,0.647059,0.944444,0.809524,0.6875,0.642857,0.55,0.68,0.869565,0.583333] precision 0.7597409159467984 [1,0.875,0.909091,0.933333,0.705882,0.730769,0.4,0.76,0.833333,0.45] precision 0.770434032198738 [1,0.764706,1,0.857143,0.75,0.75,0.590909,0.703704,0.833333,0.454545] precision 0.7777989782909691 [0.95,0.789474,0.904762,0.842105,0.833333,0.818182,0.521739,0.692308,0.826087,0.6] precision 0.7875752262835652 [1,0.789474,0.909091,0.941176,0.6875,0.75,0.583333,0.826087,0.909091,0.48] precision 0.7414548872180453 [1,0.789474,0.809524,1,0.866667,0.904762,0.315789,0.708333,0.72,0.3] predictive_accuracy 0.72 predictive_accuracy 0.775 predictive_accuracy 0.77 predictive_accuracy 0.775 predictive_accuracy 0.745 predictive_accuracy 0.765 predictive_accuracy 0.78 predictive_accuracy 0.775 predictive_accuracy 0.79 predictive_accuracy 0.735 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 0.8015617063483121 relative_absolute_error 0.7908671288418708 relative_absolute_error 0.8055549133838334 relative_absolute_error 0.7982248176294978 relative_absolute_error 0.7966942263376344 relative_absolute_error 0.790483957296232 relative_absolute_error 0.7920087562310993 relative_absolute_error 0.791395861052067 relative_absolute_error 0.7990900101344923 relative_absolute_error 0.8013439071264097 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 0.24777312976266636 root_mean_squared_error 0.2451260038098247 root_mean_squared_error 0.2485875370483592 root_mean_squared_error 0.24653715503077084 root_mean_squared_error 0.2466068121389143 root_mean_squared_error 0.24449583312406842 root_mean_squared_error 0.24476119386634246 root_mean_squared_error 0.2442668004566804 root_mean_squared_error 0.24672786917675546 root_mean_squared_error 0.24807404070173142 root_relative_squared_error 0.8259104325422217 root_relative_squared_error 0.8170866793660828 root_relative_squared_error 0.8286251234945311 root_relative_squared_error 0.8217905167692366 root_relative_squared_error 0.8220227071297148 root_relative_squared_error 0.8149861104135618 root_relative_squared_error 0.815870646221142 root_relative_squared_error 0.8142226681889352 root_relative_squared_error 0.8224262305891853 root_relative_squared_error 0.8269134690057719 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 0.72 [0.9,0.7,0.85,0.8,0.75,0.95,0.25,0.7,1,0.3] unweighted_recall 0.775 [1,0.55,0.95,0.85,0.55,0.95,0.6,0.8,0.95,0.55] unweighted_recall 0.77 [0.9,0.65,0.9,0.8,0.7,0.9,0.5,0.85,1,0.5] unweighted_recall 0.775 [0.95,0.5,0.95,0.9,0.7,0.95,0.55,0.8,0.95,0.5] unweighted_recall 0.7449999999999999 [1,0.55,0.85,0.85,0.55,0.9,0.55,0.85,1,0.35] unweighted_recall 0.765 [1,0.7,1,0.7,0.6,0.95,0.3,0.95,1,0.45] unweighted_recall 0.78 [1,0.65,0.9,0.9,0.6,0.9,0.65,0.95,1,0.25] unweighted_recall 0.7750000000000001 [0.95,0.75,0.95,0.8,0.5,0.9,0.6,0.9,0.95,0.45] unweighted_recall 0.7899999999999999 [1,0.75,1,0.8,0.55,0.9,0.35,0.95,1,0.6] unweighted_recall 0.7350000000000001 [1,0.75,0.85,0.8,0.65,0.95,0.3,0.85,0.9,0.3] usercpu_time_millis 151.36800000027506 usercpu_time_millis 179.13799999996627 usercpu_time_millis 178.00800000031813 usercpu_time_millis 182.69400000008318 usercpu_time_millis 186.97800000018105 usercpu_time_millis 182.09999999953652 usercpu_time_millis 182.35199999980978 usercpu_time_millis 178.2100000000355 usercpu_time_millis 177.80000000038854 usercpu_time_millis 187.54200000012133 usercpu_time_millis_testing 1.9339999998919666 usercpu_time_millis_testing 1.9240000001445878 usercpu_time_millis_testing 1.8939999999929569 usercpu_time_millis_testing 1.9280000001344888 usercpu_time_millis_testing 1.9999999999527063 usercpu_time_millis_testing 1.9279999996797414 usercpu_time_millis_testing 2.1659999997609702 usercpu_time_millis_testing 1.9280000001344888 usercpu_time_millis_testing 2.0060000001649314 usercpu_time_millis_testing 1.7920000000231084 usercpu_time_millis_training 149.4340000003831 usercpu_time_millis_training 177.21399999982168 usercpu_time_millis_training 176.11400000032518 usercpu_time_millis_training 180.7659999999487 usercpu_time_millis_training 184.97800000022835 usercpu_time_millis_training 180.17199999985678 usercpu_time_millis_training 180.1860000000488 usercpu_time_millis_training 176.28199999990102 usercpu_time_millis_training 175.7940000002236 usercpu_time_millis_training 185.75000000009823 wall_clock_time_millis 44.16394233703613 wall_clock_time_millis 45.22442817687988 wall_clock_time_millis 44.80385780334473 wall_clock_time_millis 46.16880416870117 wall_clock_time_millis 53.69710922241211 wall_clock_time_millis 46.03981971740723 wall_clock_time_millis 46.98300361633301 wall_clock_time_millis 45.11594772338867 wall_clock_time_millis 44.81792449951172 wall_clock_time_millis 47.605037689208984 wall_clock_time_millis_testing 0.5202293395996094 wall_clock_time_millis_testing 0.5152225494384766 wall_clock_time_millis_testing 0.5121231079101562 wall_clock_time_millis_testing 0.5168914794921875 wall_clock_time_millis_testing 0.5369186401367188 wall_clock_time_millis_testing 0.5156993865966797 wall_clock_time_millis_testing 0.5710124969482422 wall_clock_time_millis_testing 0.5152225494384766 wall_clock_time_millis_testing 0.537872314453125 wall_clock_time_millis_testing 0.47898292541503906 wall_clock_time_millis_training 43.64371299743652 wall_clock_time_millis_training 44.709205627441406 wall_clock_time_millis_training 44.29173469543457 wall_clock_time_millis_training 45.651912689208984 wall_clock_time_millis_training 53.16019058227539 wall_clock_time_millis_training 45.52412033081055 wall_clock_time_millis_training 46.411991119384766 wall_clock_time_millis_training 44.600725173950195 wall_clock_time_millis_training 44.280052185058594 wall_clock_time_millis_training 47.126054763793945 weighted_recall 0.72 [0.9,0.7,0.85,0.8,0.75,0.95,0.25,0.7,1,0.3] weighted_recall 0.775 [1,0.55,0.95,0.85,0.55,0.95,0.6,0.8,0.95,0.55] weighted_recall 0.77 [0.9,0.65,0.9,0.8,0.7,0.9,0.5,0.85,1,0.5] weighted_recall 0.775 [0.95,0.5,0.95,0.9,0.7,0.95,0.55,0.8,0.95,0.5] weighted_recall 0.745 [1,0.55,0.85,0.85,0.55,0.9,0.55,0.85,1,0.35] weighted_recall 0.765 [1,0.7,1,0.7,0.6,0.95,0.3,0.95,1,0.45] weighted_recall 0.78 [1,0.65,0.9,0.9,0.6,0.9,0.65,0.95,1,0.25] weighted_recall 0.775 [0.95,0.75,0.95,0.8,0.5,0.9,0.6,0.9,0.95,0.45] weighted_recall 0.79 [1,0.75,1,0.8,0.55,0.9,0.35,0.95,1,0.6] weighted_recall 0.735 [1,0.75,0.85,0.8,0.65,0.95,0.3,0.85,0.9,0.3]