10389671 8323 Heinrich Peters 14 Supervised Classification 16345 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1) 8232001 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "median" 12737 verbose 0 12737 copy true 13294 with_mean true 13294 with_std true 13294 C 18251.600704338267 13389 cache_size 200 13389 class_weight null 13389 coef0 0.0 13389 decision_function_shape "ovr" 13389 degree 3 13389 gamma 9.624749700615554e-05 13389 kernel "rbf" 13389 max_iter -1 13389 probability false 13389 random_state 1 13389 shrinking true 13389 tol 0.001 13389 verbose false 13389 memory null 16345 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": "svc", "step_name": "svc"}}] 16345 verbose false 16345 openml-python Sklearn_0.21.2. 14 mfeat-fourier https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff -1 21701051 description https://api.openml.org/data/download/21701051/description.xml -1 21701052 predictions https://api.openml.org/data/download/21701052/predictions.arff area_under_roc_curve 0.9083333333333332 [1,0.881944,0.960556,0.930833,0.8825,0.946944,0.7975,0.928611,0.984444,0.77] average_cost 0 f_measure 0.8354425144410215 [1,0.766265,0.943878,0.877193,0.784119,0.902743,0.625917,0.876574,0.979798,0.597938] kappa 0.8166666666666667 kb_relative_information_score 0.8274500140574947 mean_absolute_error 0.033000000000000196 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.8363802288217859 [1,0.739535,0.963542,0.879397,0.778325,0.900498,0.61244,0.883249,0.989796,0.617021] predictive_accuracy 0.835 prior_entropy 3.3219280948872383 recall 0.835 [1,0.795,0.925,0.875,0.79,0.905,0.64,0.87,0.97,0.58] relative_absolute_error 0.18333333333332877 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.18165902124585004 root_relative_squared_error 0.6055300708194908 total_cost 0 area_under_roc_curve 0.9194444444444446 [1,0.952778,0.972222,0.9,0.936111,0.975,0.847222,0.897222,1,0.713889] area_under_roc_curve 0.8972222222222223 [1,0.85,0.95,0.891667,0.880556,0.941667,0.688889,0.925,0.975,0.869444] area_under_roc_curve 0.9138888888888888 [1,0.911111,0.975,0.922222,0.961111,0.944444,0.794444,0.947222,1,0.683333] area_under_roc_curve 0.9361111111111111 [1,0.894444,0.975,0.986111,0.963889,0.922222,0.863889,0.897222,0.975,0.883333] area_under_roc_curve 0.8833333333333334 [1,0.875,0.925,0.936111,0.811111,0.911111,0.727778,0.919444,1,0.727778] area_under_roc_curve 0.9055555555555556 [1,0.858333,0.922222,0.869444,0.866667,0.963889,0.847222,0.969444,1,0.758333] area_under_roc_curve 0.9166666666666667 [1,0.863889,0.922222,0.994444,0.886111,0.947222,0.855556,0.961111,1,0.736111] area_under_roc_curve 0.913888888888889 [1,0.863889,0.997222,0.944444,0.813889,0.941667,0.833333,0.916667,0.947222,0.880556] area_under_roc_curve 0.9138888888888889 [1,0.891667,0.997222,0.991667,0.841667,0.95,0.730556,0.963889,1,0.772222] area_under_roc_curve 0.8833333333333332 [1,0.858333,0.969444,0.872222,0.863889,0.972222,0.786111,0.888889,0.947222,0.675] 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 0.8535953880857393 [1,0.808511,0.95,0.888889,0.837209,0.974359,0.666667,0.864865,1,0.545455] f_measure 0.8146063207490747 [1,0.681818,0.947368,0.820513,0.744186,0.878049,0.5,0.918919,0.974359,0.680851] f_measure 0.8426830238904541 [1,0.809524,0.974359,0.894737,0.863636,0.9,0.590909,0.923077,1,0.470588] f_measure 0.885417026910295 [1,0.842105,0.974359,0.888889,0.883721,0.894737,0.769231,0.864865,0.974359,0.761905] f_measure 0.788540011893745 [1,0.711111,0.918919,0.837209,0.684211,0.809524,0.526316,0.871795,1,0.526316] f_measure 0.8298540113986274 [1,0.731707,0.894737,0.810811,0.789474,0.883721,0.666667,0.926829,1,0.594595] f_measure 0.8469263941022607 [1,0.769231,0.894737,0.952381,0.780488,0.923077,0.714286,0.863636,1,0.571429] f_measure 0.8442854978107388 [1,0.769231,0.97561,0.9,0.702703,0.878049,0.7,0.85,0.923077,0.744186] f_measure 0.8426170354760975 [1,0.820513,0.97561,0.930233,0.756757,0.947368,0.540541,0.883721,1,0.571429] f_measure 0.7919801532801014 [1,0.731707,0.926829,0.833333,0.769231,0.95,0.553191,0.8,0.923077,0.432432] kappa 0.8388888888888889 kappa 0.7944444444444444 kappa 0.8277777777777777 kappa 0.8722222222222222 kappa 0.7666666666666667 kappa 0.8111111111111111 kappa 0.8333333333333333 kappa 0.8277777777777777 kappa 0.8277777777777777 kappa 0.7666666666666667 kb_relative_information_score 0.8483651638687042 kb_relative_information_score 0.8065348642462777 kb_relative_information_score 0.8379075889630976 kb_relative_information_score 0.8797378885855239 kb_relative_information_score 0.7803909269822613 kb_relative_information_score 0.8222212266046877 kb_relative_information_score 0.8431363764159009 kb_relative_information_score 0.8379075889630976 kb_relative_information_score 0.8379075889630976 kb_relative_information_score 0.7803909269822613 mean_absolute_error 0.029000000000000012 mean_absolute_error 0.03700000000000002 mean_absolute_error 0.031000000000000014 mean_absolute_error 0.023000000000000007 mean_absolute_error 0.04200000000000001 mean_absolute_error 0.034000000000000016 mean_absolute_error 0.030000000000000013 mean_absolute_error 0.031000000000000014 mean_absolute_error 0.031000000000000014 mean_absolute_error 0.04200000000000001 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 0.8669796562251806 [1,0.703704,0.95,1,0.782609,1,0.6,0.941176,1,0.692308] precision 0.8279159553473053 [1,0.625,1,0.842105,0.695652,0.857143,0.666667,1,1,0.592593] precision 0.8469302042986253 [1,0.772727,1,0.944444,0.791667,0.9,0.541667,0.947368,1,0.571429] precision 0.8917343171926561 [1,0.888889,1,0.8,0.826087,0.944444,0.789474,0.941176,1,0.727273] precision 0.7923406143818044 [1,0.64,1,0.782609,0.722222,0.772727,0.555556,0.894737,1,0.555556] precision 0.8352324118053018 [1,0.714286,0.944444,0.882353,0.833333,0.826087,0.6,0.904762,1,0.647059] precision 0.8492433735854789 [1,0.789474,0.944444,0.909091,0.761905,0.947368,0.681818,0.791667,1,0.666667] precision 0.8456723971052952 [1,0.789474,0.952381,0.9,0.764706,0.857143,0.7,0.85,0.947368,0.695652] precision 0.8447357640788787 [1,0.842105,0.952381,0.869565,0.823529,1,0.588235,0.826087,1,0.545455] precision 0.7995459441086377 [1,0.714286,0.904762,0.9375,0.789474,0.95,0.481481,0.8,0.947368,0.470588] predictive_accuracy 0.855 predictive_accuracy 0.815 predictive_accuracy 0.845 predictive_accuracy 0.885 predictive_accuracy 0.79 predictive_accuracy 0.83 predictive_accuracy 0.85 predictive_accuracy 0.845 predictive_accuracy 0.845 predictive_accuracy 0.79 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 recall 0.855 [1,0.95,0.95,0.8,0.9,0.95,0.75,0.8,1,0.45] recall 0.815 [1,0.75,0.9,0.8,0.8,0.9,0.4,0.85,0.95,0.8] recall 0.845 [1,0.85,0.95,0.85,0.95,0.9,0.65,0.9,1,0.4] recall 0.885 [1,0.8,0.95,1,0.95,0.85,0.75,0.8,0.95,0.8] recall 0.79 [1,0.8,0.85,0.9,0.65,0.85,0.5,0.85,1,0.5] recall 0.83 [1,0.75,0.85,0.75,0.75,0.95,0.75,0.95,1,0.55] recall 0.85 [1,0.75,0.85,1,0.8,0.9,0.75,0.95,1,0.5] recall 0.845 [1,0.75,1,0.9,0.65,0.9,0.7,0.85,0.9,0.8] recall 0.845 [1,0.8,1,1,0.7,0.9,0.5,0.95,1,0.6] recall 0.79 [1,0.75,0.95,0.75,0.75,0.95,0.65,0.8,0.9,0.4] relative_absolute_error 0.16111111111111134 relative_absolute_error 0.20555555555555588 relative_absolute_error 0.1722222222222225 relative_absolute_error 0.12777777777777796 relative_absolute_error 0.23333333333333364 relative_absolute_error 0.1888888888888892 relative_absolute_error 0.16666666666666693 relative_absolute_error 0.1722222222222225 relative_absolute_error 0.1722222222222225 relative_absolute_error 0.23333333333333364 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 0.17029386365926405 root_mean_squared_error 0.19235384061671348 root_mean_squared_error 0.17606816861659014 root_mean_squared_error 0.15165750888103102 root_mean_squared_error 0.20493901531919198 root_mean_squared_error 0.1843908891458578 root_mean_squared_error 0.17320508075688776 root_mean_squared_error 0.17606816861659014 root_mean_squared_error 0.17606816861659014 root_mean_squared_error 0.20493901531919198 root_relative_squared_error 0.5676462121975472 root_relative_squared_error 0.6411794687223786 root_relative_squared_error 0.5868938953886341 root_relative_squared_error 0.505525029603437 root_relative_squared_error 0.6831300510639737 root_relative_squared_error 0.6146362971528597 root_relative_squared_error 0.5773502691896262 root_relative_squared_error 0.5868938953886341 root_relative_squared_error 0.5868938953886341 root_relative_squared_error 0.6831300510639737 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 usercpu_time_millis 347.62064599999576 usercpu_time_millis 326.93344500012245 usercpu_time_millis 317.09347100002105 usercpu_time_millis 324.6827730000632 usercpu_time_millis 302.4304990000246 usercpu_time_millis 316.9054470000674 usercpu_time_millis 321.8253679999634 usercpu_time_millis 318.89182000008987 usercpu_time_millis 322.5680219999276 usercpu_time_millis 326.9232220000049 usercpu_time_millis_testing 24.848611000038545 usercpu_time_millis_testing 24.0018310000778 usercpu_time_millis_testing 23.567305000028682 usercpu_time_millis_testing 23.698509000041668 usercpu_time_millis_testing 23.762028000078317 usercpu_time_millis_testing 24.473225000065213 usercpu_time_millis_testing 24.494107000009535 usercpu_time_millis_testing 24.386661999983517 usercpu_time_millis_testing 24.230228999954306 usercpu_time_millis_testing 24.01931899998999 usercpu_time_millis_training 322.7720349999572 usercpu_time_millis_training 302.93161400004465 usercpu_time_millis_training 293.5261659999924 usercpu_time_millis_training 300.98426400002154 usercpu_time_millis_training 278.6684709999463 usercpu_time_millis_training 292.4322220000022 usercpu_time_millis_training 297.3312609999539 usercpu_time_millis_training 294.50515800010635 usercpu_time_millis_training 298.3377929999733 usercpu_time_millis_training 302.9039030000149 wall_clock_time_millis 347.6560115814209 wall_clock_time_millis 326.97081565856934 wall_clock_time_millis 317.105770111084 wall_clock_time_millis 324.6943950653076 wall_clock_time_millis 302.4411201477051 wall_clock_time_millis 316.91527366638184 wall_clock_time_millis 321.85935974121094 wall_clock_time_millis 318.9046382904053 wall_clock_time_millis 322.5820064544678 wall_clock_time_millis 326.934814453125 wall_clock_time_millis_testing 24.853229522705078 wall_clock_time_millis_testing 24.00660514831543 wall_clock_time_millis_testing 23.571014404296875 wall_clock_time_millis_testing 23.701906204223633 wall_clock_time_millis_testing 23.766040802001953 wall_clock_time_millis_testing 24.477005004882812 wall_clock_time_millis_testing 24.49798583984375 wall_clock_time_millis_testing 24.391651153564453 wall_clock_time_millis_testing 24.23548698425293 wall_clock_time_millis_testing 24.023056030273438 wall_clock_time_millis_training 322.8027820587158 wall_clock_time_millis_training 302.9642105102539 wall_clock_time_millis_training 293.5347557067871 wall_clock_time_millis_training 300.992488861084 wall_clock_time_millis_training 278.6750793457031 wall_clock_time_millis_training 292.438268661499 wall_clock_time_millis_training 297.3613739013672 wall_clock_time_millis_training 294.5129871368408 wall_clock_time_millis_training 298.34651947021484 wall_clock_time_millis_training 302.91175842285156