10363906 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) 8219351 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 32280.176938726683 13389 cache_size 200 13389 class_weight null 13389 coef0 0.20529368962033878 13389 decision_function_shape "ovr" 13389 degree 3 13389 gamma 7.680437851516324e-05 13389 kernel "rbf" 13389 max_iter -1 13389 probability false 13389 random_state 1141 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 21649516 description https://api.openml.org/data/download/21649516/description.xml -1 21649517 predictions https://api.openml.org/data/download/21649517/predictions.arff area_under_roc_curve 0.9835271620565439 [0.997866,0.957532,0.994466,0.968599,0.973466,0.978999,0.977733,0.991667,0.995,0.989733,0.994667,0.998133,0.963483,0.965399,0.998267,0.958933,0.999733,0.9998,0.981066,0.970933,0.9916,0.957066,0.996667,0.994733,1,0.976066] average_cost 0 f_measure 0.9683477206879941 [0.986799,0.900489,0.981818,0.935323,0.9375,0.958124,0.963087,0.991597,0.994975,0.983278,0.986711,0.993355,0.929766,0.934891,0.996667,0.932432,0.993377,0.995025,0.966555,0.952862,0.989933,0.925926,0.996656,0.988353,1,0.961345] kappa 0.9670539936305883 kb_relative_information_score 0.9679377059240875 mean_absolute_error 0.002436834680005124 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 0.9684896084369097 [0.977124,0.881789,0.97377,0.930693,0.925325,0.956522,0.969595,1,1,0.986577,0.983444,0.990066,0.929766,0.936455,0.996667,0.945205,0.986842,0.990099,0.969799,0.962585,0.996622,0.935374,1,0.986711,1,0.969492] predictive_accuracy 0.9683211491599333 prior_entropy 4.700438279892712 recall 0.9683211491599333 [0.996667,0.92,0.99,0.94,0.95,0.959732,0.956667,0.983333,0.99,0.98,0.99,0.996667,0.929766,0.933333,0.996667,0.92,1,1,0.963333,0.943333,0.983333,0.916667,0.993333,0.99,1,0.953333] relative_absolute_error 0.032946007487919614 root_mean_prior_squared_error 0.19230768465256318 root_mean_squared_error 0.049364305727976406 root_relative_squared_error 0.256694400003627 total_cost 0 area_under_roc_curve 0.9800000000000003 [0.998667,0.965333,0.982,0.981333,0.965333,0.965333,0.983333,0.983333,1,1,1,0.998667,0.966,0.966,0.983333,0.916,0.998667,1,0.982,0.982,0.966667,0.965333,1,0.966,1,0.964667] area_under_roc_curve 0.984 [0.982,0.930667,1,0.982,0.997333,0.999333,0.982,0.983333,0.983333,0.998667,0.983333,1,0.966,0.982,1,0.932,1,0.999333,1,0.966667,0.983333,0.932667,1,1,1,1] area_under_roc_curve 0.9806666666666668 [0.999333,0.880667,0.998667,0.949333,0.980667,0.998667,0.966667,0.983333,0.983333,0.983333,0.982667,1,0.999333,0.983333,1,0.965333,1,0.999333,0.966667,0.948667,1,0.962,1,1,1,0.966] 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 0.9800000000000001 [0.999333,0.962,1,0.965333,0.965333,0.964667,0.982,1,1,0.982667,0.983333,0.983333,0.948667,0.964667,0.999333,0.982667,1,1,0.948667,0.966,1,0.932667,0.983333,0.983333,1,0.982667] area_under_roc_curve 0.9913333333333334 [1,0.998,0.983333,0.998,0.966667,0.982667,1,1,1,1,1,1,0.95,0.998,1,0.95,1,1,0.983333,0.983333,1,0.999333,1,0.999333,1,0.982667] area_under_roc_curve 0.9833333333333333 [0.999333,0.980667,0.999333,0.965333,0.930667,0.983333,0.999333,0.983333,1,1,1,1,0.948667,0.964667,1,0.898,0.999333,1,1,0.999333,0.982667,0.966,1,1,1,0.966667] area_under_roc_curve 0.982647085002225 [1,0.94733,0.983333,0.948665,0.980663,0.965332,0.948665,1,1,0.999332,1,1,0.997333,0.933333,1,0.999332,1,1,0.965332,0.981998,1,0.916667,1,1,1,0.981998] area_under_roc_curve 0.9839786381842456 [1,0.965332,1,0.963329,0.981998,0.982759,0.95,1,0.983333,0.966667,0.998665,0.999332,0.963996,0.965999,1,0.981331,1,0.999332,1,0.933333,1,0.981331,1,1,1,0.966667] area_under_roc_curve 0.9846470850022251 [1,0.94733,0.998665,0.982666,0.965999,0.964851,0.966667,1,1,1,1,1,0.948665,0.964664,1,0.999332,0.999332,1,0.981998,0.999332,0.983333,0.964664,0.983333,0.999332,1,0.95] 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 0.9614430526061292 [0.967742,0.933333,0.95082,0.935484,0.933333,0.933333,0.983051,0.983051,1,1,1,0.967742,0.949153,0.949153,0.983051,0.892857,0.967742,1,0.95082,0.95082,0.965517,0.933333,1,0.949153,1,0.918033] f_measure 0.9691579232655477 [0.95082,0.866667,1,0.95082,0.9375,0.983607,0.95082,0.983051,0.983051,0.967742,0.983051,1,0.949153,0.95082,1,0.896552,1,0.983607,1,0.965517,0.983051,0.912281,1,1,1,1] f_measure 0.962852830928488 [0.983607,0.807018,0.967742,0.931034,0.920635,0.967742,0.965517,0.983051,0.983051,0.983051,0.966667,1,0.983607,0.983051,1,0.933333,1,0.983607,0.965517,0.915254,1,0.861538,1,1,1,0.949153] 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 0.9617864845151891 [0.983607,0.861538,1,0.933333,0.933333,0.918033,0.95082,1,1,0.966667,0.983051,0.983051,0.915254,0.918033,0.983607,0.966667,1,1,0.915254,0.949153,1,0.912281,0.983051,0.983051,1,0.966667] f_measure 0.9833498435033748 [1,0.952381,0.983051,0.952381,0.965517,0.966667,1,1,1,1,1,1,0.947368,0.952381,1,0.947368,1,1,0.983051,0.983051,1,0.983607,1,0.983607,1,0.966667] f_measure 0.9677499284686752 [0.983607,0.920635,0.983607,0.933333,0.866667,0.983051,0.983607,0.983051,1,1,1,1,0.915254,0.918033,1,0.842105,0.983607,1,1,0.983607,0.966667,0.949153,1,1,1,0.965517] f_measure 0.9665053664796811 [1,0.885246,0.983051,0.915254,0.920635,0.933333,0.915254,1,1,0.983607,1,1,0.935484,0.928571,1,0.983607,1,1,0.933333,0.95082,1,0.909091,1,1,1,0.95082] f_measure 0.969361071278465 [1,0.933333,1,0.888889,0.95082,0.982456,0.947368,1,0.983051,0.965517,0.967742,0.983607,0.903226,0.949153,1,0.935484,1,0.983607,1,0.928571,1,0.935484,1,1,1,0.965517] f_measure 0.9704807287506603 [1,0.885246,0.967742,0.966667,0.949153,0.947368,0.965517,1,1,1,1,1,0.915254,0.918033,1,0.983607,0.983607,1,0.95082,0.983607,0.983051,0.918033,0.983051,0.983607,1,0.947368] kappa 0.9600000000000001 kappa 0.968 kappa 0.9613333333333334 kappa 0.9693333333333334 kappa 0.9600000000000001 kappa 0.9826666666666666 kappa 0.9666666666666667 kappa 0.965289012586032 kappa 0.9679588139825432 kappa 0.9692938633999373 kb_relative_information_score 0.9610722696746876 kb_relative_information_score 0.9688613428105528 kb_relative_information_score 0.9623771607133473 kb_relative_information_score 0.9701549062198426 kb_relative_information_score 0.9610710125089236 kb_relative_information_score 0.9831282990773093 kb_relative_information_score 0.9675602276483497 kb_relative_information_score 0.9662207953530418 kb_relative_information_score 0.968818771083453 kb_relative_information_score 0.9701139982422632 mean_absolute_error 0.0029585798816568047 mean_absolute_error 0.002366863905325443 mean_absolute_error 0.002859960552268244 mean_absolute_error 0.002268244575936883 mean_absolute_error 0.0029585798816568047 mean_absolute_error 0.0012820512820512818 mean_absolute_error 0.0024654832347140027 mean_absolute_error 0.0025673940949935805 mean_absolute_error 0.002369902241532536 mean_absolute_error 0.0022711563148020133 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 0.9623019591678679 [0.9375,0.933333,0.935484,0.90625,0.933333,0.933333,1,1,1,1,1,0.9375,0.965517,0.965517,1,0.961538,0.9375,1,0.935484,0.935484,1,0.933333,1,0.965517,1,0.903226] precision 0.9700380998305981 [0.935484,0.866667,1,0.935484,0.882353,0.967742,0.935484,1,1,0.9375,1,1,0.965517,0.935484,1,0.928571,1,0.967742,1,1,1,0.962963,1,1,1,1] precision 0.9642193452121148 [0.967742,0.851852,0.9375,0.964286,0.878788,0.9375,1,1,1,1,0.966667,1,0.967742,1,1,0.933333,1,0.967742,1,0.931034,1,0.8,1,1,1,0.965517] 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 0.9628705842832651 [0.967742,0.8,1,0.933333,0.933333,0.903226,0.935484,1,1,0.966667,1,1,0.931034,0.903226,0.967742,0.966667,1,1,0.931034,0.965517,1,0.962963,1,1,1,0.966667] precision 0.984464997368223 [1,0.909091,1,0.909091,1,0.966667,1,1,1,1,1,1,1,0.909091,1,1,1,1,1,1,1,0.967742,1,0.967742,1,0.966667] precision 0.9681857939366283 [0.967742,0.878788,0.967742,0.933333,0.866667,1,0.967742,1,1,1,1,1,0.931034,0.903226,1,0.888889,0.967742,1,1,0.967742,0.966667,0.965517,1,1,1,1] precision 0.9679501084199784 [1,0.870968,1,0.931034,0.878788,0.933333,0.931034,1,1,0.967742,1,1,0.878788,1,1,0.967742,1,1,0.933333,0.935484,1,1,1,1,1,0.935484] precision 0.9708589152169309 [1,0.933333,1,0.848485,0.935484,1,1,1,1,1,0.9375,0.967742,0.875,0.965517,1,0.90625,1,0.967742,1,1,1,0.90625,1,1,1,1] precision 0.9711193407839303 [1,0.870968,0.9375,0.966667,0.965517,0.964286,1,1,1,1,1,1,0.931034,0.903226,1,0.967742,0.967742,1,0.935484,0.967742,1,0.903226,1,0.967742,1,1] predictive_accuracy 0.9615384615384616 predictive_accuracy 0.9692307692307692 predictive_accuracy 0.9628205128205128 predictive_accuracy 0.9705128205128206 predictive_accuracy 0.9615384615384616 predictive_accuracy 0.9833333333333333 predictive_accuracy 0.967948717948718 predictive_accuracy 0.9666238767650834 predictive_accuracy 0.9691912708600771 predictive_accuracy 0.9704749679075738 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 0.9615384615384616 [1,0.933333,0.966667,0.966667,0.933333,0.933333,0.966667,0.966667,1,1,1,1,0.933333,0.933333,0.966667,0.833333,1,1,0.966667,0.966667,0.933333,0.933333,1,0.933333,1,0.933333] recall 0.9692307692307692 [0.966667,0.866667,1,0.966667,1,1,0.966667,0.966667,0.966667,1,0.966667,1,0.933333,0.966667,1,0.866667,1,1,1,0.933333,0.966667,0.866667,1,1,1,1] recall 0.9628205128205128 [1,0.766667,1,0.9,0.966667,1,0.933333,0.966667,0.966667,0.966667,0.966667,1,1,0.966667,1,0.933333,1,1,0.933333,0.9,1,0.933333,1,1,1,0.933333] 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 0.9615384615384616 [1,0.933333,1,0.933333,0.933333,0.933333,0.966667,1,1,0.966667,0.966667,0.966667,0.9,0.933333,1,0.966667,1,1,0.9,0.933333,1,0.866667,0.966667,0.966667,1,0.966667] recall 0.9833333333333333 [1,1,0.966667,1,0.933333,0.966667,1,1,1,1,1,1,0.9,1,1,0.9,1,1,0.966667,0.966667,1,1,1,1,1,0.966667] recall 0.967948717948718 [1,0.966667,1,0.933333,0.866667,0.966667,1,0.966667,1,1,1,1,0.9,0.933333,1,0.8,1,1,1,1,0.966667,0.933333,1,1,1,0.933333] recall 0.9666238767650834 [1,0.9,0.966667,0.9,0.966667,0.933333,0.9,1,1,1,1,1,1,0.866667,1,1,1,1,0.933333,0.966667,1,0.833333,1,1,1,0.966667] recall 0.9691912708600771 [1,0.933333,1,0.933333,0.966667,0.965517,0.9,1,0.966667,0.933333,1,1,0.933333,0.933333,1,0.966667,1,1,1,0.866667,1,0.966667,1,1,1,0.933333] recall 0.9704749679075738 [1,0.9,1,0.966667,0.933333,0.931034,0.933333,1,1,1,1,1,0.9,0.933333,1,1,1,1,0.966667,1,0.966667,0.933333,0.966667,1,1,0.9] relative_absolute_error 0.03999999999999976 relative_absolute_error 0.03199999999999979 relative_absolute_error 0.038666666666666426 relative_absolute_error 0.030666666666666467 relative_absolute_error 0.03999999999999976 relative_absolute_error 0.01733333333333323 relative_absolute_error 0.03333333333333311 relative_absolute_error 0.034711173404494554 relative_absolute_error 0.03204108861062766 relative_absolute_error 0.030706043251851507 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 0.05439282932204212 root_mean_squared_error 0.04865042554105198 root_mean_squared_error 0.0534785990118313 root_mean_squared_error 0.04762609133591463 root_mean_squared_error 0.05439282932204212 root_mean_squared_error 0.03580574370197164 root_mean_squared_error 0.04965363264368482 root_mean_squared_error 0.050669459193813986 root_mean_squared_error 0.04868164173004579 root_mean_squared_error 0.04765665026837297 root_relative_squared_error 0.28284270129019456 root_relative_squared_error 0.2529822028098169 root_relative_squared_error 0.2780887038650852 root_relative_squared_error 0.24765566515372955 root_relative_squared_error 0.28284270129019456 root_relative_squared_error 0.186189859887763 root_relative_squared_error 0.2581988795372251 root_relative_squared_error 0.26348121716553147 root_relative_squared_error 0.2531446084029607 root_relative_squared_error 0.24781465129879426 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 12993.375389982248 usercpu_time_millis 13095.201669988455 usercpu_time_millis 12876.05010200059 usercpu_time_millis 13039.447594986996 usercpu_time_millis 12780.28623200953 usercpu_time_millis 12979.256565013202 usercpu_time_millis 12887.785089988029 usercpu_time_millis 12874.808294029208 usercpu_time_millis 12847.708666988183 usercpu_time_millis 12954.979430011008 usercpu_time_millis_testing 3456.0213339864276 usercpu_time_millis_testing 3484.7424300096463 usercpu_time_millis_testing 3424.445809010649 usercpu_time_millis_testing 3483.830974990269 usercpu_time_millis_testing 3400.4560809989925 usercpu_time_millis_testing 3474.6523899957538 usercpu_time_millis_testing 3437.0099430088885 usercpu_time_millis_testing 3454.1063320066314 usercpu_time_millis_testing 3428.87821799377 usercpu_time_millis_testing 3438.5652120108716 usercpu_time_millis_training 9537.35405599582 usercpu_time_millis_training 9610.459239978809 usercpu_time_millis_training 9451.604292989941 usercpu_time_millis_training 9555.616619996727 usercpu_time_millis_training 9379.830151010538 usercpu_time_millis_training 9504.604175017448 usercpu_time_millis_training 9450.77514697914 usercpu_time_millis_training 9420.701962022576 usercpu_time_millis_training 9418.830448994413 usercpu_time_millis_training 9516.414218000136 wall_clock_time_millis 12993.722200393677 wall_clock_time_millis 13095.523595809937 wall_clock_time_millis 12876.342296600342 wall_clock_time_millis 13039.77370262146 wall_clock_time_millis 12780.528545379639 wall_clock_time_millis 12979.515790939331 wall_clock_time_millis 12888.047456741333 wall_clock_time_millis 12875.087976455688 wall_clock_time_millis 12847.978115081787 wall_clock_time_millis 12955.309391021729 wall_clock_time_millis_testing 3456.1305046081543 wall_clock_time_millis_testing 3484.833240509033 wall_clock_time_millis_testing 3424.5247840881348 wall_clock_time_millis_testing 3483.9396476745605 wall_clock_time_millis_testing 3400.520086288452 wall_clock_time_millis_testing 3474.7188091278076 wall_clock_time_millis_testing 3437.0737075805664 wall_clock_time_millis_testing 3454.162836074829 wall_clock_time_millis_testing 3428.943395614624 wall_clock_time_millis_testing 3438.6677742004395 wall_clock_time_millis_training 9537.591695785522 wall_clock_time_millis_training 9610.690355300903 wall_clock_time_millis_training 9451.817512512207 wall_clock_time_millis_training 9555.8340549469 wall_clock_time_millis_training 9380.008459091187 wall_clock_time_millis_training 9504.796981811523 wall_clock_time_millis_training 9450.973749160767 wall_clock_time_millis_training 9420.92514038086 wall_clock_time_millis_training 9419.034719467163 wall_clock_time_millis_training 9516.641616821289