10550987 8323 Heinrich Peters 14 Supervised Classification 18601 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2) 8275629 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "median" 12737 verbose 0 12737 C 500 13106 class_weight null 13106 dual false 13106 fit_intercept true 13106 intercept_scaling 1 13106 l1_ratio null 13106 max_iter 100 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. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 22026929 description https://api.openml.org/data/download/22026929/description.xml -1 22026930 predictions https://api.openml.org/data/download/22026930/predictions.arff area_under_roc_curve 0.9712877777777779 [0.999967,0.948269,0.992281,0.981033,0.953925,0.977214,0.944231,0.987522,0.995222,0.933214] average_cost 0 f_measure 0.8018922985854049 [0.995,0.728606,0.910941,0.862944,0.739454,0.852941,0.586207,0.846535,0.94898,0.547315] kappa 0.7794444444444444 kb_relative_information_score 0.8012365167073758 mean_absolute_error 0.05286918516831766 mean_prior_absolute_error 0.18000000000000554 weighted_recall 0.8015 [0.995,0.745,0.895,0.85,0.745,0.87,0.595,0.855,0.93,0.535] number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.802706169041302 [0.995,0.712919,0.927461,0.876289,0.73399,0.836538,0.57767,0.838235,0.96875,0.560209] predictive_accuracy 0.8015000000000001 prior_entropy 3.3219280948872383 relative_absolute_error 0.2937176953795335 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.17155785417678526 root_relative_squared_error 0.5718595139226088 total_cost 0 unweighted_recall 0.8014999999999999 [0.995,0.745,0.895,0.85,0.745,0.87,0.595,0.855,0.93,0.535] area_under_roc_curve 0.9748055555555556 [1,0.9525,0.998333,0.9875,0.966111,0.998611,0.929722,0.988333,0.999444,0.9275] area_under_roc_curve 0.9642777777777777 [1,0.918889,0.990556,0.9775,0.926667,0.944722,0.943056,0.990556,0.993889,0.956944] area_under_roc_curve 0.9669444444444444 [1,0.955556,0.995833,0.944444,0.970833,0.974444,0.899722,0.979722,1,0.948889] area_under_roc_curve 0.9860555555555557 [1,0.972222,0.990556,0.998611,0.978333,0.976111,0.986389,0.991667,0.993611,0.973056] area_under_roc_curve 0.9655555555555556 [1,0.916944,0.993333,0.968333,0.962778,0.971111,0.953333,0.987778,0.999444,0.9025] area_under_roc_curve 0.9685833333333334 [1,0.944722,0.993333,0.976944,0.916667,0.988889,0.956944,0.987778,0.998889,0.921667] area_under_roc_curve 0.9709444444444444 [1,0.947222,0.978056,0.995,0.966667,0.974167,0.95,0.981389,0.997778,0.919167] area_under_roc_curve 0.9803333333333335 [1,0.973889,0.996667,0.997778,0.963056,0.986667,0.945556,0.994722,0.993889,0.951111] area_under_roc_curve 0.9696111111111111 [1,0.921944,0.998333,0.9975,0.9675,0.973333,0.933889,0.992778,1,0.910833] area_under_roc_curve 0.9736111111111111 [0.999722,0.990278,0.985278,0.989722,0.941944,0.994722,0.936111,0.989167,0.977778,0.931389] 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 0.7905271371038993 [1,0.765957,0.95,0.864865,0.780488,0.904762,0.421053,0.833333,0.952381,0.432432] f_measure 0.7754711659485222 [1,0.648649,0.842105,0.790698,0.717949,0.857143,0.52381,0.8,0.974359,0.6] f_measure 0.7709115702103506 [0.974359,0.761905,0.85,0.742857,0.711111,0.8,0.590909,0.864865,0.97561,0.4375] f_measure 0.8573450210434637 [1,0.789474,0.95,0.888889,0.782609,0.829268,0.789474,0.842105,0.974359,0.727273] f_measure 0.7696331696576495 [1,0.604651,0.864865,0.809524,0.684211,0.8,0.6,0.818182,0.974359,0.540541] f_measure 0.7873921435859818 [1,0.717949,0.95,0.857143,0.682927,0.85,0.526316,0.878049,0.95,0.461538] f_measure 0.8049508242256848 [1,0.717949,0.894737,0.926829,0.790698,0.810811,0.590909,0.883721,0.947368,0.486486] f_measure 0.8388500166761037 [1,0.8,0.923077,0.952381,0.777778,0.9,0.695652,0.863636,0.864865,0.611111] f_measure 0.8043294211137599 [1,0.666667,0.926829,0.894737,0.75,0.878049,0.526316,0.829268,1,0.571429] f_measure 0.8073232673791619 [0.97561,0.8,0.95,0.894737,0.705882,0.9,0.578947,0.85,0.864865,0.553191] kappa 0.7722222222222223 kappa 0.75 kappa 0.75 kappa 0.8388888888888889 kappa 0.7444444444444445 kappa 0.7666666666666667 kappa 0.7833333333333334 kappa 0.8222222222222222 kappa 0.7833333333333334 kappa 0.7833333333333334 kb_relative_information_score 0.7990476718546735 kb_relative_information_score 0.7990766158361596 kb_relative_information_score 0.7914296367394271 kb_relative_information_score 0.8358183349760744 kb_relative_information_score 0.767276497648365 kb_relative_information_score 0.8042777593553195 kb_relative_information_score 0.7887341109863623 kb_relative_information_score 0.8156481036031795 kb_relative_information_score 0.8081264695330281 kb_relative_information_score 0.8029299665408937 mean_absolute_error 0.054156774550375146 mean_absolute_error 0.05406596340340707 mean_absolute_error 0.0556330750563082 mean_absolute_error 0.048099090491046194 mean_absolute_error 0.0569716048610346 mean_absolute_error 0.05142341491021361 mean_absolute_error 0.053930735999684225 mean_absolute_error 0.049292433841950416 mean_absolute_error 0.053295226056521754 mean_absolute_error 0.05182353251263517 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 0.7945007851625498 [1,0.666667,0.95,0.941176,0.761905,0.863636,0.444444,0.9375,0.909091,0.470588] precision 0.7788925600057649 [1,0.705882,0.888889,0.73913,0.736842,0.818182,0.5,0.8,1,0.6] precision 0.782249681690858 [1,0.727273,0.85,0.866667,0.64,0.72,0.541667,0.941176,0.952381,0.583333] precision 0.8674053724053725 [1,0.833333,0.95,1,0.692308,0.809524,0.833333,0.888889,1,0.666667] precision 0.7739578650959725 [1,0.565217,0.941176,0.772727,0.722222,0.8,0.6,0.75,1,0.588235] precision 0.7858073213336371 [1,0.736842,0.95,0.818182,0.666667,0.85,0.555556,0.857143,0.95,0.473684] precision 0.8104697218322873 [1,0.736842,0.944444,0.904762,0.73913,0.882353,0.541667,0.826087,1,0.529412] precision 0.8467187082783058 [1,0.8,0.947368,0.909091,0.875,0.9,0.615385,0.791667,0.941176,0.6875] precision 0.8051093643198907 [1,0.684211,0.904762,0.944444,0.75,0.857143,0.555556,0.809524,1,0.545455] precision 0.8207737317149081 [0.952381,0.72,0.95,0.944444,0.857143,0.9,0.611111,0.85,0.941176,0.481481] predictive_accuracy 0.795 predictive_accuracy 0.775 predictive_accuracy 0.775 predictive_accuracy 0.855 predictive_accuracy 0.77 predictive_accuracy 0.79 predictive_accuracy 0.805 predictive_accuracy 0.84 predictive_accuracy 0.805 predictive_accuracy 0.805 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 0.3008709697243067 relative_absolute_error 0.30036646335226186 relative_absolute_error 0.3090726392017126 relative_absolute_error 0.26721716939470136 relative_absolute_error 0.31650891589463703 relative_absolute_error 0.28568563839007594 relative_absolute_error 0.29961519999824604 relative_absolute_error 0.27384685467750264 relative_absolute_error 0.29608458920289893 relative_absolute_error 0.28790851395908457 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 0.1712367038395079 root_mean_squared_error 0.17486511840993355 root_mean_squared_error 0.17717354557537865 root_mean_squared_error 0.15352212727502895 root_mean_squared_error 0.1887577706318059 root_mean_squared_error 0.17262233914498276 root_mean_squared_error 0.17944989568547384 root_mean_squared_error 0.16163344446509192 root_mean_squared_error 0.16538157775707804 root_mean_squared_error 0.16838935971704952 root_relative_squared_error 0.5707890127983599 root_relative_squared_error 0.5828837280331122 root_relative_squared_error 0.5905784852512624 root_relative_squared_error 0.5117404242500968 root_relative_squared_error 0.6291925687726867 root_relative_squared_error 0.5754077971499428 root_relative_squared_error 0.5981663189515798 root_relative_squared_error 0.5387781482169735 root_relative_squared_error 0.5512719258569272 root_relative_squared_error 0.5612978657234987 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 0.795 [1,0.9,0.95,0.8,0.8,0.95,0.4,0.75,1,0.4] unweighted_recall 0.775 [1,0.6,0.8,0.85,0.7,0.9,0.55,0.8,0.95,0.6] unweighted_recall 0.775 [0.95,0.8,0.85,0.65,0.8,0.9,0.65,0.8,1,0.35] unweighted_recall 0.8550000000000001 [1,0.75,0.95,0.8,0.9,0.85,0.75,0.8,0.95,0.8] unweighted_recall 0.77 [1,0.65,0.8,0.85,0.65,0.8,0.6,0.9,0.95,0.5] unweighted_recall 0.79 [1,0.7,0.95,0.9,0.7,0.85,0.5,0.9,0.95,0.45] unweighted_recall 0.805 [1,0.7,0.85,0.95,0.85,0.75,0.65,0.95,0.9,0.45] unweighted_recall 0.8400000000000001 [1,0.8,0.9,1,0.7,0.9,0.8,0.95,0.8,0.55] unweighted_recall 0.8049999999999999 [1,0.65,0.95,0.85,0.75,0.9,0.5,0.85,1,0.6] unweighted_recall 0.8049999999999999 [1,0.9,0.95,0.85,0.6,0.9,0.55,0.85,0.8,0.65] usercpu_time_millis 354.55650702351704 usercpu_time_millis 346.68544598389417 usercpu_time_millis 331.22498396551237 usercpu_time_millis 321.8503989628516 usercpu_time_millis 310.4716599918902 usercpu_time_millis 340.61680699232966 usercpu_time_millis 334.1672259848565 usercpu_time_millis 333.2100959960371 usercpu_time_millis 336.33956901030615 usercpu_time_millis 340.2048220159486 usercpu_time_millis_testing 0.7493619923479855 usercpu_time_millis_testing 0.7975450134836137 usercpu_time_millis_testing 0.7395719876512885 usercpu_time_millis_testing 0.7220389670692384 usercpu_time_millis_testing 0.7852989947423339 usercpu_time_millis_testing 0.7320049917325377 usercpu_time_millis_testing 0.8169270004145801 usercpu_time_millis_testing 0.7543590036220849 usercpu_time_millis_testing 0.8084489963948727 usercpu_time_millis_testing 0.7827520021237433 usercpu_time_millis_training 353.80714503116906 usercpu_time_millis_training 345.88790097041056 usercpu_time_millis_training 330.4854119778611 usercpu_time_millis_training 321.1283599957824 usercpu_time_millis_training 309.68636099714786 usercpu_time_millis_training 339.8848020005971 usercpu_time_millis_training 333.3502989844419 usercpu_time_millis_training 332.45573699241504 usercpu_time_millis_training 335.5311200139113 usercpu_time_millis_training 339.42207001382485 wall_clock_time_millis 354.56371307373047 wall_clock_time_millis 346.6906547546387 wall_clock_time_millis 331.24399185180664 wall_clock_time_millis 321.87938690185547 wall_clock_time_millis 310.5027675628662 wall_clock_time_millis 340.620756149292 wall_clock_time_millis 334.1715335845947 wall_clock_time_millis 333.21523666381836 wall_clock_time_millis 336.46488189697266 wall_clock_time_millis 342.06080436706543 wall_clock_time_millis_testing 0.7526874542236328 wall_clock_time_millis_testing 0.8003711700439453 wall_clock_time_millis_testing 0.7424354553222656 wall_clock_time_millis_testing 0.7250308990478516 wall_clock_time_millis_testing 0.7877349853515625 wall_clock_time_millis_testing 0.7345676422119141 wall_clock_time_millis_testing 0.8203983306884766 wall_clock_time_millis_testing 0.7569789886474609 wall_clock_time_millis_testing 0.8111000061035156 wall_clock_time_millis_testing 0.7855892181396484 wall_clock_time_millis_training 353.81102561950684 wall_clock_time_millis_training 345.8902835845947 wall_clock_time_millis_training 330.5015563964844 wall_clock_time_millis_training 321.1543560028076 wall_clock_time_millis_training 309.71503257751465 wall_clock_time_millis_training 339.8861885070801 wall_clock_time_millis_training 333.35113525390625 wall_clock_time_millis_training 332.4582576751709 wall_clock_time_millis_training 335.65378189086914 wall_clock_time_millis_training 341.2752151489258 weighted_recall 0.795 [1,0.9,0.95,0.8,0.8,0.95,0.4,0.75,1,0.4] weighted_recall 0.775 [1,0.6,0.8,0.85,0.7,0.9,0.55,0.8,0.95,0.6] weighted_recall 0.775 [0.95,0.8,0.85,0.65,0.8,0.9,0.65,0.8,1,0.35] weighted_recall 0.855 [1,0.75,0.95,0.8,0.9,0.85,0.75,0.8,0.95,0.8] weighted_recall 0.77 [1,0.65,0.8,0.85,0.65,0.8,0.6,0.9,0.95,0.5] weighted_recall 0.79 [1,0.7,0.95,0.9,0.7,0.85,0.5,0.9,0.95,0.45] weighted_recall 0.805 [1,0.7,0.85,0.95,0.85,0.75,0.65,0.95,0.9,0.45] weighted_recall 0.84 [1,0.8,0.9,1,0.7,0.9,0.8,0.95,0.8,0.55] weighted_recall 0.805 [1,0.65,0.95,0.85,0.75,0.9,0.5,0.85,1,0.6] weighted_recall 0.805 [1,0.9,0.95,0.85,0.6,0.9,0.55,0.85,0.8,0.65]