10326854 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) 8182524 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 copy true 13294 with_mean true 13294 with_std true 13294 C 42.8718089702478 13389 cache_size 200 13389 class_weight null 13389 coef0 -0.6390272054347252 13389 decision_function_shape "ovr" 13389 degree 5 13389 gamma 0.02965844567448009 13389 kernel "rbf" 13389 max_iter -1 13389 probability false 13389 random_state 5071 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 21575394 description https://api.openml.org/data/download/21575394/description.xml -1 21575395 predictions https://api.openml.org/data/download/21575395/predictions.arff area_under_roc_curve 0.9050000000000001 [0.9875,0.878611,0.973889,0.942778,0.918611,0.972778,0.731111,0.949444,0.986389,0.708889] average_cost 0 f_measure 0.8286786260982013 [0.987342,0.785894,0.964467,0.90404,0.848635,0.936275,0.509804,0.88835,0.977444,0.484536] kappa 0.8099999999999999 kb_relative_information_score 0.8211754691141314 mean_absolute_error 0.034200000000000216 mean_prior_absolute_error 0.18000000000000554 number_of_instances 2000 [200,200,200,200,200,200,200,200,200,200] precision 0.8288265729456434 [1,0.791878,0.979381,0.913265,0.842365,0.918269,0.5,0.863208,0.979899,0.5] predictive_accuracy 0.8290000000000001 prior_entropy 3.3219280948872383 recall 0.829 [0.975,0.78,0.95,0.895,0.855,0.955,0.52,0.915,0.975,0.47] relative_absolute_error 0.18999999999999534 root_mean_prior_squared_error 0.3000000000000046 root_mean_squared_error 0.18493242008906988 root_relative_squared_error 0.6164414002968902 total_cost 0 area_under_roc_curve 0.8972222222222223 [0.975,0.9,0.972222,0.925,0.916667,0.972222,0.697222,0.869444,0.997222,0.747222] area_under_roc_curve 0.8916666666666666 [0.975,0.888889,0.975,0.916667,0.883333,0.947222,0.697222,0.913889,0.975,0.744444] area_under_roc_curve 0.9027777777777779 [0.95,0.858333,1,0.922222,0.961111,0.969444,0.722222,0.919444,1,0.725] area_under_roc_curve 0.9333333333333332 [1,0.844444,0.975,0.966667,0.991667,0.972222,0.877778,0.966667,0.975,0.763889] area_under_roc_curve 0.886111111111111 [1,0.808333,0.95,0.894444,0.919444,0.991667,0.691667,0.936111,1,0.669444] area_under_roc_curve 0.9138888888888889 [1,0.95,1,0.897222,0.883333,0.969444,0.747222,0.994444,1,0.697222] area_under_roc_curve 0.911111111111111 [0.975,0.863889,0.95,0.966667,0.894444,0.963889,0.869444,0.988889,0.997222,0.641667] area_under_roc_curve 0.9166666666666665 [1,0.891667,0.972222,0.994444,0.897222,1,0.744444,0.941667,0.972222,0.752778] area_under_roc_curve 0.9222222222222222 [1,0.891667,1,0.997222,0.969444,0.975,0.608333,0.997222,1,0.783333] area_under_roc_curve 0.875 [1,0.888889,0.944444,0.947222,0.869444,0.966667,0.655556,0.966667,0.947222,0.563889] 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 0.8166952722360993 [0.974359,0.73913,0.95,0.918919,0.85,0.95,0.461538,0.810811,0.97561,0.536585] f_measure 0.807267488608952 [0.974359,0.8,0.974359,0.85,0.761905,0.923077,0.461538,0.829268,0.974359,0.52381] f_measure 0.8248893596775495 [0.947368,0.731707,1,0.894737,0.863636,0.926829,0.5,0.871795,1,0.512821] f_measure 0.8772096250003227 [1,0.777778,0.974359,0.904762,0.930233,0.95,0.727273,0.904762,0.974359,0.628571] f_measure 0.7944657883637494 [1,0.666667,0.947368,0.842105,0.871795,0.930233,0.439024,0.837209,1,0.410256] f_measure 0.8451472095888013 [1,0.947368,1,0.864865,0.761905,0.926829,0.536585,0.952381,1,0.461538] f_measure 0.8300891095261265 [0.974359,0.769231,0.947368,0.904762,0.842105,0.883721,0.680851,0.909091,0.97561,0.413793] f_measure 0.8503719506158529 [1,0.820513,0.95,0.952381,0.864865,1,0.52381,0.878049,0.95,0.564103] f_measure 0.8537167887187558 [1,0.820513,1,0.97561,0.926829,0.974359,0.322581,0.97561,1,0.541667] f_measure 0.7746341046341045 [1,0.8,0.9,0.923077,0.810811,0.904762,0.363636,0.904762,0.923077,0.216216] kappa 0.7944444444444444 kappa 0.7833333333333334 kappa 0.8055555555555555 kappa 0.8666666666666667 kappa 0.7722222222222223 kappa 0.8277777777777777 kappa 0.8222222222222222 kappa 0.8333333333333333 kappa 0.8444444444444444 kappa 0.75 kb_relative_information_score 0.8065348642462777 kb_relative_information_score 0.7960772893406711 kb_relative_information_score 0.8169924391518844 kb_relative_information_score 0.8745091011327207 kb_relative_information_score 0.7856197144350645 kb_relative_information_score 0.8379075889630976 kb_relative_information_score 0.8326788015102943 kb_relative_information_score 0.8431363764159009 kb_relative_information_score 0.8535939513215075 kb_relative_information_score 0.7647045646238513 mean_absolute_error 0.03700000000000002 mean_absolute_error 0.03900000000000002 mean_absolute_error 0.03500000000000002 mean_absolute_error 0.024000000000000007 mean_absolute_error 0.041000000000000016 mean_absolute_error 0.031000000000000014 mean_absolute_error 0.032000000000000015 mean_absolute_error 0.030000000000000013 mean_absolute_error 0.02800000000000001 mean_absolute_error 0.045 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 0.8236073781739417 [1,0.653846,0.95,1,0.85,0.95,0.473684,0.882353,0.952381,0.52381] precision 0.8107849168375484 [1,0.8,1,0.85,0.727273,0.947368,0.473684,0.809524,1,0.5] precision 0.8276211361737676 [1,0.714286,1,0.944444,0.791667,0.904762,0.5,0.894737,1,0.526316] precision 0.8821837944664032 [1,0.875,1,0.863636,0.869565,0.95,0.666667,0.863636,1,0.733333] precision 0.7969634230503796 [1,0.684211,1,0.888889,0.894737,0.869565,0.428571,0.782609,1,0.421053] precision 0.8479795746049618 [1,1,1,0.941176,0.727273,0.904762,0.52381,0.909091,1,0.473684] precision 0.8413059438231062 [1,0.789474,1,0.863636,0.888889,0.826087,0.592593,0.833333,0.952381,0.666667] precision 0.8528462868400949 [1,0.842105,0.95,0.909091,0.941176,1,0.5,0.857143,0.95,0.578947] precision 0.8570460241512872 [1,0.842105,1,0.952381,0.904762,1,0.454545,0.952381,1,0.464286] precision 0.7772989961534854 [1,0.8,0.9,0.947368,0.882353,0.863636,0.333333,0.863636,0.947368,0.235294] predictive_accuracy 0.815 predictive_accuracy 0.805 predictive_accuracy 0.825 predictive_accuracy 0.88 predictive_accuracy 0.795 predictive_accuracy 0.845 predictive_accuracy 0.84 predictive_accuracy 0.85 predictive_accuracy 0.86 predictive_accuracy 0.775 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 0.815 [0.95,0.85,0.95,0.85,0.85,0.95,0.45,0.75,1,0.55] recall 0.805 [0.95,0.8,0.95,0.85,0.8,0.9,0.45,0.85,0.95,0.55] recall 0.825 [0.9,0.75,1,0.85,0.95,0.95,0.5,0.85,1,0.5] recall 0.88 [1,0.7,0.95,0.95,1,0.95,0.8,0.95,0.95,0.55] recall 0.795 [1,0.65,0.9,0.8,0.85,1,0.45,0.9,1,0.4] recall 0.845 [1,0.9,1,0.8,0.8,0.95,0.55,1,1,0.45] recall 0.84 [0.95,0.75,0.9,0.95,0.8,0.95,0.8,1,1,0.3] recall 0.85 [1,0.8,0.95,1,0.8,1,0.55,0.9,0.95,0.55] recall 0.86 [1,0.8,1,1,0.95,0.95,0.25,1,1,0.65] recall 0.775 [1,0.8,0.9,0.9,0.75,0.95,0.4,0.95,0.9,0.2] relative_absolute_error 0.20555555555555588 relative_absolute_error 0.21666666666666703 relative_absolute_error 0.19444444444444475 relative_absolute_error 0.13333333333333353 relative_absolute_error 0.2277777777777781 relative_absolute_error 0.1722222222222225 relative_absolute_error 0.17777777777777806 relative_absolute_error 0.16666666666666693 relative_absolute_error 0.15555555555555578 relative_absolute_error 0.2500000000000003 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 0.19235384061671348 root_mean_squared_error 0.19748417658131504 root_mean_squared_error 0.1870828693386971 root_mean_squared_error 0.1549193338482967 root_mean_squared_error 0.20248456731316591 root_mean_squared_error 0.17606816861659014 root_mean_squared_error 0.1788854381999832 root_mean_squared_error 0.17320508075688776 root_mean_squared_error 0.16733200530681513 root_mean_squared_error 0.21213203435596426 root_relative_squared_error 0.6411794687223786 root_relative_squared_error 0.6582805886043839 root_relative_squared_error 0.6236095644623241 root_relative_squared_error 0.5163977794943226 root_relative_squared_error 0.6749485577105534 root_relative_squared_error 0.5868938953886341 root_relative_squared_error 0.5962847939999444 root_relative_squared_error 0.5773502691896262 root_relative_squared_error 0.5577733510227175 root_relative_squared_error 0.707106781186548 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 962.173988998984 usercpu_time_millis 955.2303530072095 usercpu_time_millis 965.11114200257 usercpu_time_millis 963.4893590045976 usercpu_time_millis 954.3371149993618 usercpu_time_millis 947.7891709975665 usercpu_time_millis 955.1284259941895 usercpu_time_millis 967.8108080042875 usercpu_time_millis 962.8612340020481 usercpu_time_millis 947.1660869967309 usercpu_time_millis_testing 54.56982200121274 usercpu_time_millis_testing 54.532737005501986 usercpu_time_millis_testing 54.76169499888783 usercpu_time_millis_testing 54.753757001890335 usercpu_time_millis_testing 54.26296500081662 usercpu_time_millis_testing 53.97351000283379 usercpu_time_millis_testing 55.47953299537767 usercpu_time_millis_testing 54.3459270047606 usercpu_time_millis_testing 53.68409099901328 usercpu_time_millis_testing 54.79490799916675 usercpu_time_millis_training 907.6041669977712 usercpu_time_millis_training 900.6976160017075 usercpu_time_millis_training 910.3494470036821 usercpu_time_millis_training 908.7356020027073 usercpu_time_millis_training 900.0741499985452 usercpu_time_millis_training 893.8156609947328 usercpu_time_millis_training 899.6488929988118 usercpu_time_millis_training 913.4648809995269 usercpu_time_millis_training 909.1771430030349 usercpu_time_millis_training 892.3711789975641 wall_clock_time_millis 962.5377655029297 wall_clock_time_millis 987.6976013183594 wall_clock_time_millis 1028.883934020996 wall_clock_time_millis 1021.7721462249756 wall_clock_time_millis 1009.6695423126221 wall_clock_time_millis 979.8824787139893 wall_clock_time_millis 995.2154159545898 wall_clock_time_millis 1019.9098587036133 wall_clock_time_millis 1071.0597038269043 wall_clock_time_millis 1059.237003326416 wall_clock_time_millis_testing 54.58569526672363 wall_clock_time_millis_testing 54.59260940551758 wall_clock_time_millis_testing 54.77786064147949 wall_clock_time_millis_testing 54.76880073547363 wall_clock_time_millis_testing 54.279327392578125 wall_clock_time_millis_testing 53.987979888916016 wall_clock_time_millis_testing 55.49478530883789 wall_clock_time_millis_testing 98.36053848266602 wall_clock_time_millis_testing 53.707122802734375 wall_clock_time_millis_testing 54.810285568237305 wall_clock_time_millis_training 907.952070236206 wall_clock_time_millis_training 933.1049919128418 wall_clock_time_millis_training 974.1060733795166 wall_clock_time_millis_training 967.003345489502 wall_clock_time_millis_training 955.390214920044 wall_clock_time_millis_training 925.8944988250732 wall_clock_time_millis_training 939.720630645752 wall_clock_time_millis_training 921.5493202209473 wall_clock_time_millis_training 1017.3525810241699 wall_clock_time_millis_training 1004.4267177581787