10317668 8323 Heinrich Peters 3481 Supervised Classification 12736 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1) 8155058 l2_regularization 1e-05 12677 learning_rate 0.001 12677 loss "auto" 12677 max_bins 4 12677 max_depth 8 12677 max_iter 450 12677 max_leaf_nodes 8 12677 min_samples_leaf 15 12677 n_iter_no_change null 12677 random_state 42186 12677 scoring null 12677 tol 1e-07 12677 validation_fraction 0.2 12677 verbose 0 12677 memory null 12736 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "histgradientboostingclassifier", "step_name": "histgradientboostingclassifier"}}] 12736 verbose false 12736 add_indicator false 12737 copy true 12737 fill_value null 12737 missing_values NaN 12737 strategy "most_frequent" 12737 verbose 0 12737 openml-python Sklearn_0.21.2. 300 isolet https://www.openml.org/data/download/52405/phpB0xrNj -1 21557019 description https://api.openml.org/data/download/21557019/description.xml -1 21557020 predictions https://api.openml.org/data/download/21557020/predictions.arff area_under_roc_curve 0.9925252821115068 [0.989046,0.99348,0.997339,0.989801,0.987102,0.994063,0.993228,0.99491,0.99917,0.996505,0.977284,0.998483,0.991681,0.989822,0.998552,0.986034,0.995644,0.9994,0.996845,0.98725,0.993324,0.980493,0.988493,0.997514,0.999813,0.990388] average_cost 0 f_measure 0.8874466371274972 [0.862992,0.824645,0.948929,0.796085,0.756014,0.869565,0.883249,0.96633,0.950331,0.878939,0.82087,0.93617,0.857627,0.82069,0.926667,0.821429,0.942529,0.965058,0.898839,0.884746,0.923333,0.778702,0.886165,0.971714,0.981575,0.920204] kappa 0.883021657685399 kb_relative_information_score 0.608098891308852 mean_absolute_error 0.0517963099158487 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 0.8883833100727002 [0.81791,0.783784,0.938111,0.779553,0.780142,0.866667,0.896907,0.97619,0.944079,0.874587,0.858182,0.919614,0.869416,0.85,0.926667,0.800633,0.928803,0.963455,0.894389,0.9,0.923333,0.777409,0.933579,0.9701,0.986532,0.937716] predictive_accuracy 0.8875208413492369 prior_entropy 4.700438279892712 recall 0.8875208413492369 [0.913333,0.87,0.96,0.813333,0.733333,0.872483,0.87,0.956667,0.956667,0.883333,0.786667,0.953333,0.846154,0.793333,0.926667,0.843333,0.956667,0.966667,0.903333,0.87,0.923333,0.78,0.843333,0.973333,0.976667,0.903333] relative_absolute_error 0.7002861656296553 root_mean_prior_squared_error 0.19230768465256318 root_mean_squared_error 0.13811904213866527 root_relative_squared_error 0.7182190477109691 total_cost 0 area_under_roc_curve 0.9928564102564102 [0.993556,0.983822,0.997467,0.976044,0.995422,0.998444,0.997956,0.999956,0.999956,0.996533,0.962,0.9984,0.9848,0.993378,0.995378,0.986444,0.994,0.999778,1,0.984844,0.996578,0.996444,0.986044,0.998844,0.999289,0.998889] area_under_roc_curve 0.9927709401709399 [0.980889,0.994667,0.999778,0.989689,0.992489,0.995511,0.992978,0.999956,0.996578,0.999067,0.984622,0.999511,0.989467,0.994133,0.999467,0.968711,0.999867,0.997378,0.998178,0.992889,0.999022,0.960756,0.999733,0.998133,0.999911,0.988667] area_under_roc_curve 0.9940529914529915 [0.9932,0.997111,0.992489,0.993333,0.996844,0.998356,0.992622,0.987778,0.998933,0.995378,0.986311,0.997733,0.998267,0.991911,0.999378,0.995244,0.998844,0.998311,0.996756,0.996578,0.9996,0.985867,0.986356,0.984133,0.999778,0.984267] area_under_roc_curve 0.9929111111111111 [0.9892,0.995467,0.993511,0.991467,0.983022,0.995911,0.9992,0.994622,0.999778,0.994667,0.972667,0.997511,0.994356,0.986089,0.9992,0.987822,0.991556,1,0.993333,0.995867,0.999467,0.975022,0.999867,0.999644,1,0.986444] area_under_roc_curve 0.9911162393162393 [0.9948,0.994711,0.999111,0.997156,0.976178,0.990044,0.997867,0.983333,0.999689,0.992978,0.980311,0.997689,0.989956,0.977422,0.9992,0.987378,0.999778,1,0.986622,0.975911,0.982133,0.990844,0.978933,0.999733,0.999956,0.997289] area_under_roc_curve 0.9925606837606837 [0.995067,0.994444,0.999556,0.9716,0.982933,0.987333,0.9976,0.999556,1,0.999022,0.975156,0.998311,0.986444,0.994044,0.999689,0.9784,0.995511,0.999422,0.999333,0.997022,0.999867,0.968444,0.992578,0.998489,0.999822,0.996933] area_under_roc_curve 0.9927008547008547 [0.983733,0.992933,0.999467,0.997911,0.982444,0.991467,0.998133,0.987378,0.999156,0.997689,0.967822,0.998933,0.992444,0.986578,0.994756,0.977556,0.994,0.999733,0.998978,0.9964,0.991422,0.996178,0.997289,0.999956,1,0.987867] area_under_roc_curve 0.9950229894316369 [0.996796,0.990743,0.999955,0.992968,0.985937,0.998086,0.989987,0.999288,1,0.998353,0.998264,0.999822,0.997977,0.992746,0.999199,0.998175,0.996262,1,0.998887,0.965198,0.99911,0.984869,0.997997,0.99822,0.999955,0.9919] area_under_roc_curve 0.9898714737607639 [0.997018,0.99368,0.992701,0.987272,0.99506,0.989701,0.97441,0.997374,0.99773,0.991945,0.971562,0.997775,0.991811,0.992879,0.999599,0.990432,0.987494,0.999377,0.997463,0.971785,0.97401,0.98923,0.970049,0.999911,0.999688,0.986693] area_under_roc_curve 0.9924453508971884 [0.970449,0.995416,0.999911,0.998487,0.981486,0.997195,0.995639,0.999466,0.999822,0.998932,0.976547,0.998264,0.991055,0.990654,0.999733,0.991188,0.998843,0.999777,0.999021,0.999421,0.992434,0.965376,0.976324,1,0.999644,0.988652] 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 0.8882706811760558 [0.90625,0.754098,0.933333,0.78125,0.806452,0.949153,0.877193,1,0.931034,0.870968,0.8,0.903226,0.814815,0.825397,0.90625,0.827586,0.933333,0.95082,1,0.870968,0.9,0.83871,0.814815,0.95082,0.965517,0.983051] f_measure 0.8926239957318868 [0.830769,0.8,0.95082,0.733333,0.776119,0.9,0.833333,1,0.949153,0.918033,0.872727,0.967742,0.852459,0.793103,0.949153,0.8,1,0.966667,0.870968,0.912281,0.965517,0.766667,0.933333,0.983051,0.967742,0.915254] f_measure 0.8956075223130772 [0.857143,0.881356,0.888889,0.8125,0.827586,0.895522,0.862069,0.95082,0.861538,0.881356,0.857143,0.983051,0.888889,0.821429,0.947368,0.931034,0.935484,0.896552,0.912281,0.915254,0.983051,0.761905,0.912281,0.965517,0.983051,0.872727] f_measure 0.8834263140591916 [0.903226,0.787879,0.95082,0.806452,0.75,0.847458,0.892308,0.983051,1,0.827586,0.745763,0.896552,0.847458,0.785714,0.920635,0.8,0.95082,1,0.915254,0.827586,0.95082,0.727273,0.95082,0.967742,0.983051,0.95082] f_measure 0.8689949139321398 [0.848485,0.835821,0.966667,0.813559,0.689655,0.774194,0.933333,0.947368,0.966667,0.862069,0.758621,0.931034,0.793651,0.736842,0.920635,0.794118,0.9375,1,0.763636,0.9,0.896552,0.8,0.842105,0.983051,0.983051,0.915254] f_measure 0.8893088651793205 [0.877193,0.83871,0.966667,0.666667,0.666667,0.833333,0.881356,0.966667,1,0.949153,0.821429,0.920635,0.877193,0.885246,0.949153,0.774194,0.920635,0.966667,0.9,0.903226,0.95082,0.806452,0.9,0.95082,1,0.949153] f_measure 0.886967651153963 [0.8,0.852941,0.965517,0.847458,0.703704,0.896552,0.95082,0.949153,0.949153,0.852459,0.827586,0.935484,0.821429,0.807018,0.881356,0.8,0.931034,0.966667,0.935484,0.949153,0.857143,0.84375,0.857143,1,0.983607,0.896552] f_measure 0.90418259729751 [0.903226,0.818182,0.9375,0.779661,0.714286,0.870968,0.881356,0.949153,0.967742,0.918033,0.931034,0.983607,0.966667,0.881356,0.966667,0.865672,0.965517,0.983051,0.885246,0.827586,0.931034,0.754717,0.928571,0.966667,1,0.933333] f_measure 0.8752318460756388 [0.869565,0.857143,0.949153,0.786885,0.827586,0.892857,0.821429,0.966667,0.933333,0.793651,0.785714,0.935484,0.866667,0.814815,0.947368,0.794118,0.918033,0.95082,0.920635,0.769231,0.866667,0.78125,0.892857,0.966667,0.966667,0.881356] f_measure 0.8874071552178877 [0.83871,0.819672,0.983607,0.935484,0.779661,0.836364,0.892857,0.949153,0.95082,0.918033,0.807018,0.90625,0.842105,0.847458,0.881356,0.836364,0.935484,0.967742,0.875,0.952381,0.935484,0.698413,0.814815,0.983607,0.983051,0.9] kappa 0.884 kappa 0.888 kappa 0.8906666666666667 kappa 0.88 kappa 0.864 kappa 0.8853333333333333 kappa 0.8826666666666666 kappa 0.9012068510476399 kappa 0.8704999845757826 kappa 0.8838503025722497 kb_relative_information_score 0.6025413662913292 kb_relative_information_score 0.6173752497392409 kb_relative_information_score 0.6146854433422313 kb_relative_information_score 0.6052192082782204 kb_relative_information_score 0.6011927714146975 kb_relative_information_score 0.604090372472164 kb_relative_information_score 0.6079690706043607 kb_relative_information_score 0.6183319527870285 kb_relative_information_score 0.6000486691333342 kb_relative_information_score 0.6095394499208117 mean_absolute_error 0.052161609737630586 mean_absolute_error 0.051422449524188486 mean_absolute_error 0.05147477690436369 mean_absolute_error 0.0518867490353424 mean_absolute_error 0.05212897439403665 mean_absolute_error 0.05202382072660223 mean_absolute_error 0.05182864960879129 mean_absolute_error 0.051429357288281734 mean_absolute_error 0.05199023067694151 mean_absolute_error 0.05161602829630051 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 0.8919646239618184 [0.852941,0.741935,0.933333,0.735294,0.78125,0.965517,0.925926,1,0.964286,0.84375,0.88,0.875,0.916667,0.787879,0.852941,0.857143,0.933333,0.935484,1,0.84375,0.9,0.8125,0.916667,0.935484,1,1] precision 0.8957728639312343 [0.771429,0.8,0.935484,0.733333,0.702703,0.9,0.833333,1,0.965517,0.903226,0.96,0.9375,0.83871,0.821429,0.965517,0.88,1,0.966667,0.84375,0.962963,1,0.766667,0.933333,1,0.9375,0.931034] precision 0.9005920388142497 [0.818182,0.896552,0.848485,0.764706,0.857143,0.810811,0.892857,0.935484,0.8,0.896552,0.818182,1,0.848485,0.884615,1,0.964286,0.90625,0.928571,0.962963,0.931034,1,0.727273,0.962963,1,1,0.96] precision 0.8850479724835311 [0.875,0.722222,0.935484,0.78125,0.807692,0.862069,0.828571,1,1,0.857143,0.758621,0.928571,0.862069,0.846154,0.878788,0.8,0.935484,1,0.931034,0.857143,0.935484,0.8,0.935484,0.9375,1,0.935484] precision 0.8735171437141118 [0.777778,0.756757,0.966667,0.827586,0.714286,0.75,0.933333,1,0.966667,0.892857,0.785714,0.964286,0.757576,0.777778,0.878788,0.710526,0.882353,1,0.84,0.9,0.928571,0.88,0.888889,1,1,0.931034] precision 0.8910588036879534 [0.925926,0.8125,0.966667,0.636364,0.75,0.833333,0.896552,0.966667,1,0.965517,0.884615,0.878788,0.925926,0.870968,0.965517,0.75,0.878788,0.966667,0.9,0.875,0.935484,0.78125,0.9,0.935484,1,0.965517] precision 0.891047248646337 [0.742857,0.763158,1,0.862069,0.791667,0.928571,0.935484,0.965517,0.965517,0.83871,0.857143,0.90625,0.884615,0.851852,0.896552,0.742857,0.964286,0.966667,0.90625,0.965517,0.818182,0.794118,0.923077,1,0.967742,0.928571] precision 0.9073757777034954 [0.875,0.75,0.882353,0.793103,0.769231,0.84375,0.896552,0.965517,0.9375,0.903226,0.964286,0.967742,0.935484,0.896552,0.966667,0.783784,1,1,0.870968,0.857143,0.964286,0.869565,1,0.966667,1,0.933333] precision 0.8814283197229641 [0.769231,0.818182,0.965517,0.774194,0.857143,0.925926,0.884615,0.966667,0.933333,0.757576,0.846154,0.90625,0.866667,0.916667,1,0.710526,0.903226,0.935484,0.878788,0.909091,0.866667,0.735294,0.961538,0.966667,0.966667,0.896552] precision 0.8901003380744908 [0.8125,0.806452,0.967742,0.90625,0.793103,0.884615,0.961538,0.965517,0.935484,0.903226,0.851852,0.852941,0.888889,0.862069,0.896552,0.92,0.90625,0.9375,0.823529,0.909091,0.90625,0.666667,0.916667,0.967742,1,0.9] predictive_accuracy 0.8884615384615384 predictive_accuracy 0.8923076923076922 predictive_accuracy 0.8948717948717949 predictive_accuracy 0.8846153846153847 predictive_accuracy 0.8692307692307693 predictive_accuracy 0.8897435897435898 predictive_accuracy 0.8871794871794871 predictive_accuracy 0.9050064184852374 predictive_accuracy 0.8754813863928114 predictive_accuracy 0.8883183568677793 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 0.8884615384615384 [0.966667,0.766667,0.933333,0.833333,0.833333,0.933333,0.833333,1,0.9,0.9,0.733333,0.933333,0.733333,0.866667,0.966667,0.8,0.933333,0.966667,1,0.9,0.9,0.866667,0.733333,0.966667,0.933333,0.966667] recall 0.8923076923076924 [0.9,0.8,0.966667,0.733333,0.866667,0.9,0.833333,1,0.933333,0.933333,0.8,1,0.866667,0.766667,0.933333,0.733333,1,0.966667,0.9,0.866667,0.933333,0.766667,0.933333,0.966667,1,0.9] recall 0.8948717948717949 [0.9,0.866667,0.933333,0.866667,0.8,1,0.833333,0.966667,0.933333,0.866667,0.9,0.966667,0.933333,0.766667,0.9,0.9,0.966667,0.866667,0.866667,0.9,0.966667,0.8,0.866667,0.933333,0.966667,0.8] recall 0.8846153846153846 [0.933333,0.866667,0.966667,0.833333,0.7,0.833333,0.966667,0.966667,1,0.8,0.733333,0.866667,0.833333,0.733333,0.966667,0.8,0.966667,1,0.9,0.8,0.966667,0.666667,0.966667,1,0.966667,0.966667] recall 0.8692307692307693 [0.933333,0.933333,0.966667,0.8,0.666667,0.8,0.933333,0.9,0.966667,0.833333,0.733333,0.9,0.833333,0.7,0.966667,0.9,1,1,0.7,0.9,0.866667,0.733333,0.8,0.966667,0.966667,0.9] recall 0.8897435897435897 [0.833333,0.866667,0.966667,0.7,0.6,0.833333,0.866667,0.966667,1,0.933333,0.766667,0.966667,0.833333,0.9,0.933333,0.8,0.966667,0.966667,0.9,0.933333,0.966667,0.833333,0.9,0.966667,1,0.933333] recall 0.8871794871794871 [0.866667,0.966667,0.933333,0.833333,0.633333,0.866667,0.966667,0.933333,0.933333,0.866667,0.8,0.966667,0.766667,0.766667,0.866667,0.866667,0.9,0.966667,0.966667,0.933333,0.9,0.9,0.8,1,1,0.866667] recall 0.9050064184852374 [0.933333,0.9,1,0.766667,0.666667,0.9,0.866667,0.933333,1,0.933333,0.9,1,1,0.866667,0.966667,0.966667,0.933333,0.966667,0.9,0.8,0.9,0.666667,0.866667,0.966667,1,0.933333] recall 0.8754813863928113 [1,0.9,0.933333,0.8,0.8,0.862069,0.766667,0.966667,0.933333,0.833333,0.733333,0.966667,0.866667,0.733333,0.9,0.9,0.933333,0.966667,0.966667,0.666667,0.866667,0.833333,0.833333,0.966667,0.966667,0.866667] recall 0.8883183568677792 [0.866667,0.833333,1,0.966667,0.766667,0.793103,0.833333,0.933333,0.966667,0.933333,0.766667,0.966667,0.8,0.833333,0.866667,0.766667,0.966667,1,0.933333,1,0.966667,0.733333,0.733333,1,0.966667,0.9] relative_absolute_error 0.7052249636527612 relative_absolute_error 0.6952315175670242 relative_absolute_error 0.6959389837469928 relative_absolute_error 0.7015088469578251 relative_absolute_error 0.7047837338073712 relative_absolute_error 0.7033620562236578 relative_absolute_error 0.7007233427108541 relative_absolute_error 0.6953250155074915 relative_absolute_error 0.7029081448227263 relative_absolute_error 0.6978489270093061 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 0.1390808218182383 root_mean_squared_error 0.13706383636196612 root_mean_squared_error 0.13706015592197812 root_mean_squared_error 0.1384036361561341 root_mean_squared_error 0.13919081507950246 root_mean_squared_error 0.1387599621406699 root_mean_squared_error 0.13822981846351423 root_mean_squared_error 0.1369294575330709 root_mean_squared_error 0.1387887194254379 root_mean_squared_error 0.13765700873352701 root_relative_squared_error 0.7232202448566036 root_relative_squared_error 0.7127319208987271 root_relative_squared_error 0.7127127826115462 root_relative_squared_error 0.7196988795529067 root_relative_squared_error 0.7237922097925601 root_relative_squared_error 0.7215517745992241 root_relative_squared_error 0.7187950275870244 root_relative_squared_error 0.7120332585083939 root_relative_squared_error 0.7217015445889692 root_relative_squared_error 0.715816647331028 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 290418.45424899657 usercpu_time_millis 315855.799629011 usercpu_time_millis 291310.51284800196 usercpu_time_millis 289792.14449399296 usercpu_time_millis 316020.81852000265 usercpu_time_millis 291335.8319510007 usercpu_time_millis 289615.8053370018 usercpu_time_millis 290833.6780979953 usercpu_time_millis 281145.26660800766 usercpu_time_millis 280535.9008499945 usercpu_time_millis_testing 387.7282899993588 usercpu_time_millis_testing 411.86341100546997 usercpu_time_millis_testing 455.0483630009694 usercpu_time_millis_testing 444.715396995889 usercpu_time_millis_testing 445.1299520005705 usercpu_time_millis_testing 443.6608059986611 usercpu_time_millis_testing 850.127641002473 usercpu_time_millis_testing 429.2085449997103 usercpu_time_millis_testing 494.95165700500365 usercpu_time_millis_testing 452.7762189973146 usercpu_time_millis_training 290030.7259589972 usercpu_time_millis_training 315443.93621800555 usercpu_time_millis_training 290855.464485001 usercpu_time_millis_training 289347.4290969971 usercpu_time_millis_training 315575.6885680021 usercpu_time_millis_training 290892.17114500207 usercpu_time_millis_training 288765.67769599933 usercpu_time_millis_training 290404.4695529956 usercpu_time_millis_training 280650.31495100266 usercpu_time_millis_training 280083.1246309972 wall_clock_time_millis 290445.1584815979 wall_clock_time_millis 407067.2061443329 wall_clock_time_millis 291339.84756469727 wall_clock_time_millis 289807.01994895935 wall_clock_time_millis 316046.44441604614 wall_clock_time_millis 291368.99614334106 wall_clock_time_millis 289682.9102039337 wall_clock_time_millis 290901.72481536865 wall_clock_time_millis 281259.96804237366 wall_clock_time_millis 280605.85284233093 wall_clock_time_millis_testing 387.7396583557129 wall_clock_time_millis_testing 411.87596321105957 wall_clock_time_millis_testing 455.0642967224121 wall_clock_time_millis_testing 444.7298049926758 wall_clock_time_millis_testing 445.1425075531006 wall_clock_time_millis_testing 443.71485710144043 wall_clock_time_millis_testing 850.6796360015869 wall_clock_time_millis_testing 429.3854236602783 wall_clock_time_millis_testing 494.9662685394287 wall_clock_time_millis_testing 452.82602310180664 wall_clock_time_millis_training 290057.4188232422 wall_clock_time_millis_training 406655.3301811218 wall_clock_time_millis_training 290884.78326797485 wall_clock_time_millis_training 289362.2901439667 wall_clock_time_millis_training 315601.30190849304 wall_clock_time_millis_training 290925.2812862396 wall_clock_time_millis_training 288832.2305679321 wall_clock_time_millis_training 290472.3393917084 wall_clock_time_millis_training 280765.0017738342 wall_clock_time_millis_training 280153.0268192291