10363624 8323 Heinrich Peters 3481 Supervised Classification 16345 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1) 8219070 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 326.31131040223244 13389 cache_size 200 13389 class_weight null 13389 coef0 -0.5116187321824732 13389 decision_function_shape "ovr" 13389 degree 4 13389 gamma 0.00010216486460066312 13389 kernel "rbf" 13389 max_iter -1 13389 probability false 13389 random_state 35388 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. 300 isolet https://www.openml.org/data/download/52405/phpB0xrNj -1 21648950 description https://api.openml.org/data/download/21648950/description.xml -1 21648951 predictions https://api.openml.org/data/download/21648951/predictions.arff area_under_roc_curve 0.983860637671383 [0.999533,0.957599,0.994466,0.966999,0.973666,0.980677,0.977733,0.991667,0.995,0.989733,0.994667,0.998133,0.96676,0.963866,0.998267,0.960533,0.999733,0.9998,0.981133,0.970933,0.9916,0.960266,0.9966,0.9948,1,0.976133] average_cost 0 f_measure 0.9689866767831542 [0.988468,0.901961,0.981818,0.935108,0.942149,0.959866,0.963087,0.991597,0.994975,0.983278,0.986711,0.993355,0.93178,0.936242,0.996667,0.93266,0.993377,0.995025,0.968174,0.952862,0.989933,0.926421,0.994992,0.99,1,0.962963] kappa 0.9677209195974662 kb_relative_information_score 0.968587129045606 mean_absolute_error 0.0023875060427580564 mean_prior_absolute_error 0.07396449117237175 number_of_instances 7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300] precision 0.9691110316706804 [0.977199,0.884615,0.97377,0.933555,0.934426,0.956667,0.969595,1,1,0.986577,0.983444,0.990066,0.927152,0.942568,0.996667,0.942177,0.986842,0.990099,0.973064,0.962585,0.996622,0.92953,0.996656,0.99,1,0.972789] predictive_accuracy 0.9689624214441451 prior_entropy 4.700438279892712 recall 0.9689624214441452 [1,0.92,0.99,0.936667,0.95,0.963087,0.956667,0.983333,0.99,0.98,0.99,0.996667,0.936455,0.93,0.996667,0.923333,1,1,0.963333,0.943333,0.983333,0.923333,0.993333,0.99,1,0.953333] relative_absolute_error 0.032279084259419215 root_mean_prior_squared_error 0.19230768465256318 root_mean_squared_error 0.04886211254907074 root_relative_squared_error 0.2540829953693661 total_cost 0 area_under_roc_curve 0.9806666666666669 [0.998667,0.965333,0.982,0.981333,0.965333,0.982,0.983333,0.983333,1,1,1,0.998667,0.966,0.966,0.983333,0.916,0.998667,1,0.982667,0.982,0.966667,0.965333,1,0.966,1,0.964667] area_under_roc_curve 0.9853333333333333 [0.998667,0.930667,1,0.982667,0.998,0.999333,0.982,0.983333,0.983333,0.998667,0.983333,1,0.966,0.982,1,0.932,1,0.999333,1,0.966667,0.983333,0.949333,1,1,1,1] area_under_roc_curve 0.9800000000000001 [0.999333,0.880667,0.998667,0.932667,0.980667,0.998667,0.966667,0.983333,0.983333,0.983333,0.982667,1,0.999333,0.983333,1,0.964667,1,0.999333,0.966667,0.948667,1,0.962,1,1,1,0.966] area_under_roc_curve 0.9846666666666668 [1,0.998,0.999333,0.95,1,0.982667,0.998667,0.983333,1,0.966667,0.998667,1,0.947333,0.931333,1,0.965333,1,1,0.982667,0.948667,1,0.95,1,0.999333,1,0.999333] area_under_roc_curve 0.9806666666666668 [0.999333,0.962,1,0.965333,0.965333,0.964667,0.982,1,1,0.982667,0.983333,0.983333,0.948667,0.964667,0.999333,0.982667,1,1,0.948667,0.966,1,0.949333,0.983333,0.983333,1,0.983333] area_under_roc_curve 0.9926666666666666 [1,0.998667,0.983333,0.998,0.966667,0.982667,1,1,1,1,1,1,0.966667,0.998667,1,0.966667,1,1,0.983333,0.983333,1,0.999333,1,0.999333,1,0.982667] area_under_roc_curve 0.9826666666666667 [0.999333,0.980667,0.999333,0.965333,0.931333,0.983333,0.999333,0.983333,1,1,1,1,0.948,0.948,1,0.898,0.999333,1,1,0.999333,0.982667,0.965333,1,1,1,0.966667] area_under_roc_curve 0.9833146417445481 [1,0.963996,0.983333,0.948665,0.981331,0.965332,0.948665,1,1,0.999332,1,1,0.997333,0.933333,1,0.999332,1,1,0.965332,0.981998,1,0.916667,1,1,1,0.981998] area_under_roc_curve 0.9833110814419226 [1,0.948665,1,0.963329,0.981998,0.982759,0.95,1,0.983333,0.966667,0.998665,0.999332,0.963996,0.965999,1,0.981331,1,0.999332,1,0.933333,1,0.980663,1,1,1,0.966667] area_under_roc_curve 0.9853146417445482 [1,0.94733,0.998665,0.982666,0.965999,0.964851,0.966667,1,1,1,1,1,0.965332,0.965332,1,0.999332,0.999332,1,0.981998,0.999332,0.983333,0.964664,0.982666,1,1,0.95] 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 0.9627251038881803 [0.967742,0.933333,0.95082,0.935484,0.933333,0.95082,0.983051,0.983051,1,1,1,0.967742,0.949153,0.949153,0.983051,0.892857,0.967742,1,0.966667,0.95082,0.965517,0.933333,1,0.949153,1,0.918033] f_measure 0.9717119229299105 [0.967742,0.866667,1,0.966667,0.952381,0.983607,0.95082,0.983051,0.983051,0.967742,0.983051,1,0.949153,0.95082,1,0.896552,1,0.983607,1,0.965517,0.983051,0.931034,1,1,1,1] f_measure 0.9615430491033986 [0.983607,0.807018,0.967742,0.912281,0.920635,0.967742,0.965517,0.983051,0.983051,0.983051,0.966667,1,0.983607,0.983051,1,0.918033,1,0.983607,0.965517,0.915254,1,0.861538,1,1,1,0.949153] f_measure 0.9704043140084453 [1,0.952381,0.983607,0.947368,1,0.966667,0.967742,0.983051,1,0.965517,0.967742,1,0.885246,0.881356,1,0.933333,1,1,0.966667,0.915254,1,0.947368,1,0.983607,1,0.983607] f_measure 0.9631379445842352 [0.983607,0.861538,1,0.933333,0.933333,0.918033,0.95082,1,1,0.966667,0.983051,0.983051,0.915254,0.918033,0.983607,0.966667,1,1,0.915254,0.949153,1,0.931034,0.983051,0.983051,1,0.983051] f_measure 0.9859275206902668 [1,0.967742,0.983051,0.952381,0.965517,0.966667,1,1,1,1,1,1,0.965517,0.967742,1,0.965517,1,1,0.983051,0.983051,1,0.983607,1,0.983607,1,0.966667] f_measure 0.9664261989426672 [0.983607,0.920635,0.983607,0.933333,0.881356,0.983051,0.983607,0.983051,1,1,1,1,0.9,0.9,1,0.842105,0.983607,1,1,0.983607,0.966667,0.933333,1,1,1,0.965517] f_measure 0.9677696356123546 [1,0.903226,0.983051,0.915254,0.935484,0.933333,0.915254,1,1,0.983607,1,1,0.935484,0.928571,1,0.983607,1,1,0.933333,0.95082,1,0.909091,1,1,1,0.95082] f_measure 0.968092982201006 [1,0.915254,1,0.888889,0.95082,0.982456,0.947368,1,0.983051,0.965517,0.967742,0.983607,0.903226,0.949153,1,0.935484,1,0.983607,1,0.928571,1,0.920635,1,1,1,0.965517] f_measure 0.9717665658877056 [1,0.885246,0.967742,0.966667,0.949153,0.947368,0.965517,1,1,1,1,1,0.933333,0.933333,1,0.983607,0.983607,1,0.95082,0.983607,0.983051,0.918033,0.966667,1,1,0.947368] kappa 0.9613333333333334 kappa 0.9706666666666667 kappa 0.9600000000000001 kappa 0.9693333333333334 kappa 0.9613333333333334 kappa 0.9853333333333334 kappa 0.9653333333333334 kappa 0.9666240505634922 kappa 0.9666237645651492 kappa 0.9706289128173313 kb_relative_information_score 0.9623721276711269 kb_relative_information_score 0.9714560213820461 kb_relative_information_score 0.9610798214276005 kb_relative_information_score 0.9701549062198426 kb_relative_information_score 0.9623683517946702 kb_relative_information_score 0.9857242348145664 kb_relative_information_score 0.966262888362603 kb_relative_information_score 0.9675198015358574 kb_relative_information_score 0.9675197631917467 kb_relative_information_score 0.9714142649166692 mean_absolute_error 0.002859960552268244 mean_absolute_error 0.0021696252465483227 mean_absolute_error 0.0029585798816568047 mean_absolute_error 0.002268244575936883 mean_absolute_error 0.002859960552268244 mean_absolute_error 0.0010848126232741616 mean_absolute_error 0.002564102564102563 mean_absolute_error 0.002468648168263058 mean_absolute_error 0.002468648168263058 mean_absolute_error 0.0021724103880714912 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396449704142057 mean_prior_absolute_error 0.07396448587535052 mean_prior_absolute_error 0.07396447325283656 mean_prior_absolute_error 0.07396447325283656 number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] number_of_instances 779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30] precision 0.9635840104499191 [0.9375,0.933333,0.935484,0.90625,0.933333,0.935484,1,1,1,1,1,0.9375,0.965517,0.965517,1,0.961538,0.9375,1,0.966667,0.935484,1,0.933333,1,0.965517,1,0.903226] precision 0.9723942399832277 [0.9375,0.866667,1,0.966667,0.909091,0.967742,0.935484,1,1,0.9375,1,1,0.965517,0.935484,1,0.928571,1,0.967742,1,1,1,0.964286,1,1,1,1] precision 0.9630104883580968 [0.967742,0.851852,0.9375,0.962963,0.878788,0.9375,1,1,1,1,0.966667,1,0.967742,1,1,0.903226,1,0.967742,1,0.931034,1,0.8,1,1,1,0.965517] precision 0.9712514358092778 [1,0.909091,0.967742,1,1,0.966667,0.9375,1,1,1,0.9375,1,0.870968,0.896552,1,0.933333,1,1,0.966667,0.931034,1,1,1,0.967742,1,0.967742] precision 0.9642035106161914 [0.967742,0.8,1,0.933333,0.933333,0.903226,0.935484,1,1,0.966667,1,1,0.931034,0.903226,0.967742,0.966667,1,1,0.931034,0.965517,1,0.964286,1,1,1,1] precision 0.9866503120535377 [1,0.9375,1,0.909091,1,0.966667,1,1,1,1,1,1,1,0.9375,1,1,1,1,1,1,1,0.967742,1,0.967742,1,0.966667] precision 0.9667796731756688 [0.967742,0.878788,0.967742,0.933333,0.896552,1,0.967742,1,1,1,1,1,0.9,0.9,1,0.888889,0.967742,1,1,0.967742,0.966667,0.933333,1,1,1,1] precision 0.9691629856706834 [1,0.875,1,0.931034,0.90625,0.933333,0.931034,1,1,0.967742,1,1,0.878788,1,1,0.967742,1,1,0.933333,0.935484,1,1,1,1,1,0.935484] precision 0.9697127930685291 [1,0.931034,1,0.848485,0.935484,1,1,1,1,1,0.9375,0.967742,0.875,0.965517,1,0.90625,1,0.967742,1,1,1,0.878788,1,1,1,1] precision 0.9723259303335797 [1,0.870968,0.9375,0.966667,0.965517,0.964286,1,1,1,1,1,1,0.933333,0.933333,1,0.967742,0.967742,1,0.935484,0.967742,1,0.903226,0.966667,1,1,1] predictive_accuracy 0.9628205128205128 predictive_accuracy 0.9717948717948718 predictive_accuracy 0.9615384615384616 predictive_accuracy 0.9705128205128206 predictive_accuracy 0.9628205128205128 predictive_accuracy 0.985897435897436 predictive_accuracy 0.9666666666666667 predictive_accuracy 0.9679075738125802 predictive_accuracy 0.9679075738125802 predictive_accuracy 0.9717586649550707 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700441149362989 prior_entropy 4.700435698259304 prior_entropy 4.700429514669705 prior_entropy 4.700429514669705 recall 0.9628205128205128 [1,0.933333,0.966667,0.966667,0.933333,0.966667,0.966667,0.966667,1,1,1,1,0.933333,0.933333,0.966667,0.833333,1,1,0.966667,0.966667,0.933333,0.933333,1,0.933333,1,0.933333] recall 0.9717948717948718 [1,0.866667,1,0.966667,1,1,0.966667,0.966667,0.966667,1,0.966667,1,0.933333,0.966667,1,0.866667,1,1,1,0.933333,0.966667,0.9,1,1,1,1] recall 0.9615384615384616 [1,0.766667,1,0.866667,0.966667,1,0.933333,0.966667,0.966667,0.966667,0.966667,1,1,0.966667,1,0.933333,1,1,0.933333,0.9,1,0.933333,1,1,1,0.933333] recall 0.9705128205128205 [1,1,1,0.9,1,0.966667,1,0.966667,1,0.933333,1,1,0.9,0.866667,1,0.933333,1,1,0.966667,0.9,1,0.9,1,1,1,1] recall 0.9628205128205128 [1,0.933333,1,0.933333,0.933333,0.933333,0.966667,1,1,0.966667,0.966667,0.966667,0.9,0.933333,1,0.966667,1,1,0.9,0.933333,1,0.9,0.966667,0.966667,1,0.966667] recall 0.985897435897436 [1,1,0.966667,1,0.933333,0.966667,1,1,1,1,1,1,0.933333,1,1,0.933333,1,1,0.966667,0.966667,1,1,1,1,1,0.966667] recall 0.9666666666666667 [1,0.966667,1,0.933333,0.866667,0.966667,1,0.966667,1,1,1,1,0.9,0.9,1,0.8,1,1,1,1,0.966667,0.933333,1,1,1,0.933333] recall 0.9679075738125802 [1,0.933333,0.966667,0.9,0.966667,0.933333,0.9,1,1,1,1,1,1,0.866667,1,1,1,1,0.933333,0.966667,1,0.833333,1,1,1,0.966667] recall 0.9679075738125802 [1,0.9,1,0.933333,0.966667,0.965517,0.9,1,0.966667,0.933333,1,1,0.933333,0.933333,1,0.966667,1,1,1,0.866667,1,0.966667,1,1,1,0.933333] recall 0.9717586649550706 [1,0.9,1,0.966667,0.933333,0.931034,0.933333,1,1,1,1,1,0.933333,0.933333,1,1,1,1,0.966667,1,0.966667,0.933333,0.966667,1,1,0.9] relative_absolute_error 0.038666666666666426 relative_absolute_error 0.029333333333333145 relative_absolute_error 0.03999999999999976 relative_absolute_error 0.030666666666666467 relative_absolute_error 0.038666666666666426 relative_absolute_error 0.014666666666666576 relative_absolute_error 0.034666666666666436 relative_absolute_error 0.033376128273552456 relative_absolute_error 0.03337613396940381 relative_absolute_error 0.029370997893075356 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230769991209876 root_mean_prior_squared_error 0.19230767088031558 root_mean_prior_squared_error 0.19230763806177284 root_mean_prior_squared_error 0.19230763806177284 root_mean_squared_error 0.0534785990118313 root_mean_squared_error 0.04657923621688448 root_mean_squared_error 0.05439282932204212 root_mean_squared_error 0.04762609133591463 root_mean_squared_error 0.0534785990118313 root_mean_squared_error 0.03293649379144905 root_mean_squared_error 0.05063696835418332 root_mean_squared_error 0.04968549253316362 root_mean_squared_error 0.04968549253316362 root_mean_squared_error 0.046609123442428 root_relative_squared_error 0.2780887038650852 root_relative_squared_error 0.24221201875003037 root_relative_squared_error 0.28284270129019456 root_relative_squared_error 0.24765566515372955 root_relative_squared_error 0.2780887038650852 root_relative_squared_error 0.1712697609430297 root_relative_squared_error 0.2633122250296207 root_relative_squared_error 0.2583645899600429 root_relative_squared_error 0.2583646340516319 root_relative_squared_error 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