10396177 8323 Heinrich Peters 6 Supervised Classification 16357 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(2) 8235394 memory null 16357 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"}}] 16357 verbose false 16357 add_indicator false 16358 copy true 16358 fill_value null 16358 missing_values NaN 16358 strategy "median" 16358 verbose 0 16358 copy true 16359 with_mean true 16359 with_std true 16359 C 8829.986986237445 16360 cache_size 200 16360 class_weight null 16360 coef0 0.0 16360 decision_function_shape "ovr" 16360 degree 3 16360 gamma 2.305877221785047 16360 kernel "rbf" 16360 max_iter -1 16360 probability false 16360 random_state 1 16360 shrinking true 16360 tol 0.001 16360 verbose false 16360 openml-python Sklearn_0.21.2. 6 letter https://www.openml.org/data/download/6/dataset_6_letter.arff -1 21714086 description https://api.openml.org/data/download/21714086/description.xml -1 21714087 predictions https://api.openml.org/data/download/21714087/predictions.arff area_under_roc_curve 0.912946352937481 [0.920152,0.91478,0.921092,0.929241,0.904037,0.914449,0.922585,0.869975,0.887872,0.913675,0.910797,0.908595,0.944061,0.89964,0.895008,0.911408,0.94558,0.9222,0.935595,0.926953,0.913847,0.898929,0.918805,0.887339,0.929025,0.885429] average_cost 0 f_measure 0.8736800343376786 [0.913223,0.898305,0.911765,0.911126,0.887777,0.897418,0.905817,0.83628,0.868792,0.890007,0.872493,0.897547,0.917969,0.886058,0.880829,0.342932,0.924603,0.900914,0.925479,0.91706,0.90457,0.880866,0.909747,0.868327,0.915254,0.867433] kappa 0.8261088726522477 kb_relative_information_score 0.8306333294283371 mean_absolute_error 0.01285769230769161 mean_prior_absolute_error 0.07396191835229461 number_of_instances 20000 [789,766,736,805,768,775,773,734,755,747,739,761,792,783,753,803,783,758,748,796,813,764,752,787,786,734] precision 0.9480835220423898 [1,0.978462,0.99359,0.969188,0.984152,0.977204,0.974665,0.959436,0.986532,0.96118,0.926941,0.9952,0.947581,0.993651,0.994983,0.207882,0.958848,0.96391,0.986384,0.989811,0.997037,0.982287,0.995261,0.987055,0.979681,0.991243] predictive_accuracy 0.83285 prior_entropy 4.6998107276322685 recall 0.83285 [0.840304,0.830287,0.842391,0.859627,0.808594,0.829677,0.846054,0.741144,0.776159,0.828648,0.824087,0.817346,0.890152,0.799489,0.790173,0.978829,0.89272,0.845646,0.871658,0.854271,0.827798,0.798429,0.837766,0.775095,0.858779,0.771117] relative_absolute_error 0.17384206080821202 root_mean_prior_squared_error 0.19230433563020993 root_mean_squared_error 0.11339176472606646 root_relative_squared_error 0.5896474687087254 total_cost 0 area_under_roc_curve 0.9161601730278721 [0.917722,0.921818,0.939189,0.925405,0.88909,0.88961,0.908831,0.855645,0.867382,0.9184,0.951664,0.921053,0.961244,0.903846,0.89974,0.923958,0.928967,0.953687,0.946407,0.917201,0.914634,0.896104,0.933333,0.935897,0.904803,0.891632] area_under_roc_curve 0.9135608774800584 [0.891026,0.88909,0.93893,0.900974,0.908571,0.901557,0.928311,0.883043,0.875,0.945427,0.896572,0.901056,0.91668,0.949107,0.86,0.898438,0.967428,0.907375,0.966407,0.936709,0.969136,0.902337,0.933074,0.873157,0.949107,0.858108] area_under_roc_curve 0.9093956946889837 [0.898734,0.948052,0.925416,0.949575,0.881059,0.903586,0.908571,0.861976,0.920793,0.910345,0.931654,0.868421,0.961505,0.911392,0.913333,0.913802,0.928447,0.867382,0.911903,0.968094,0.895062,0.921298,0.886667,0.867089,0.898474,0.885135] area_under_roc_curve 0.9159042148948714 [0.962025,0.902077,0.884876,0.961719,0.914214,0.928967,0.941298,0.827989,0.868421,0.926407,0.915992,0.927632,0.924219,0.905063,0.89974,0.919271,0.966908,0.907635,0.932173,0.898734,0.969136,0.895844,0.92,0.841772,0.948586,0.911643] area_under_roc_curve 0.9174588795273028 [0.936709,0.914804,0.885135,0.936979,0.960779,0.909996,0.915324,0.910959,0.888158,0.905887,0.904627,0.934211,0.94375,0.891026,0.906667,0.917969,0.972798,0.920533,0.91974,0.90599,0.91358,0.914214,0.953333,0.867089,0.929227,0.890411] area_under_roc_curve 0.9106931791627398 [0.917722,0.953687,0.912162,0.886979,0.902337,0.884355,0.910256,0.909662,0.886667,0.879481,0.883837,0.881579,0.936449,0.910256,0.887898,0.91276,0.942257,0.953947,0.9,0.925,0.944444,0.913694,0.906667,0.872377,0.941787,0.917549] area_under_roc_curve 0.9151186495217865 [0.911392,0.855263,0.90411,0.95599,0.902337,0.993069,0.947938,0.891632,0.879481,0.91974,0.8776,0.940789,0.970779,0.884355,0.921053,0.913802,0.930119,0.906855,0.959221,0.930729,0.858025,0.87474,0.913333,0.929859,0.916667,0.89726] area_under_roc_curve 0.9155986365544818 [0.955696,0.94027,0.931247,0.93125,0.87013,0.908571,0.922557,0.871622,0.913333,0.912814,0.883837,0.920793,0.979711,0.871535,0.861842,0.893576,0.947805,0.94027,0.946667,0.9375,0.925405,0.901056,0.92,0.898734,0.948198,0.863014] area_under_roc_curve 0.9049169333514927 [0.911392,0.887898,0.938356,0.924363,0.915584,0.86987,0.927271,0.837578,0.893074,0.918961,0.925156,0.902337,0.942778,0.871795,0.886667,0.907845,0.916407,0.952294,0.933074,0.91849,0.878049,0.861842,0.901316,0.922817,0.92327,0.855905] area_under_roc_curve 0.9106525997411695 [0.898734,0.934545,0.952055,0.919493,0.896104,0.954285,0.915324,0.850053,0.886667,0.89974,0.937112,0.888158,0.903762,0.897176,0.913333,0.912795,0.954868,0.912294,0.94,0.93125,0.871951,0.907895,0.920533,0.865385,0.93038,0.883562] 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 0.8781878540456122 [0.910345,0.909091,0.935252,0.907895,0.863309,0.875912,0.893617,0.818898,0.823529,0.898551,0.924138,0.914286,0.941935,0.893617,0.882353,0.353982,0.911565,0.945205,0.937063,0.897959,0.906667,0.884058,0.928571,0.931507,0.888889,0.87218] f_measure 0.8733628693359192 [0.877698,0.863309,0.928571,0.884354,0.887324,0.867133,0.916667,0.854962,0.857143,0.929577,0.836879,0.884058,0.885906,0.940397,0.837209,0.337778,0.954248,0.885714,0.958904,0.932432,0.968153,0.885714,0.921986,0.848921,0.940397,0.834646] f_measure 0.8672589652301226 [0.887324,0.945205,0.913043,0.924051,0.852941,0.887324,0.887324,0.815385,0.907801,0.859155,0.907801,0.848485,0.948052,0.902778,0.905109,0.339056,0.899329,0.823529,0.897059,0.961039,0.882759,0.896552,0.87218,0.846715,0.881119,0.870229] f_measure 0.875832286551306 [0.960526,0.879433,0.863636,0.942675,0.9,0.911565,0.931507,0.774194,0.848485,0.914286,0.865248,0.921986,0.900662,0.895105,0.882353,0.355056,0.941935,0.892086,0.920863,0.887324,0.968153,0.877698,0.913043,0.81203,0.928105,0.890511] f_measure 0.8808973846857393 [0.932432,0.888889,0.870229,0.921053,0.95302,0.895105,0.901408,0.902256,0.874074,0.877698,0.875912,0.929577,0.940397,0.877698,0.897059,0.351111,0.936709,0.901408,0.906475,0.890411,0.905405,0.9,0.951049,0.846715,0.917808,0.876923] f_measure 0.8711400176493971 [0.910345,0.945205,0.903704,0.861111,0.885714,0.863309,0.901408,0.869565,0.87218,0.850746,0.838235,0.865672,0.926174,0.901408,0.867647,0.33617,0.921053,0.951724,0.888889,0.918919,0.941176,0.887324,0.897059,0.830986,0.926174,0.903704] f_measure 0.8739851850077711 [0.902778,0.830769,0.893939,0.948052,0.885714,0.980892,0.927152,0.87218,0.850746,0.906475,0.842105,0.937063,0.887574,0.863309,0.914286,0.353741,0.918919,0.873239,0.938776,0.913907,0.834532,0.850746,0.905109,0.912752,0.909091,0.885496] f_measure 0.8768136551144731 [0.953642,0.924138,0.919708,0.926174,0.850746,0.887324,0.90411,0.852713,0.905109,0.892086,0.838235,0.907801,0.95,0.846715,0.839695,0.340045,0.910256,0.924138,0.943662,0.933333,0.907895,0.884058,0.913043,0.887324,0.933333,0.84127] f_measure 0.8625866024411472 [0.902778,0.867647,0.934307,0.884615,0.907801,0.844444,0.891892,0.8,0.874074,0.887324,0.906475,0.885714,0.933333,0.852941,0.87218,0.325866,0.902778,0.92517,0.921986,0.905405,0.861111,0.839695,0.890511,0.910345,0.899329,0.825397] f_measure 0.8707585934279354 [0.887324,0.917808,0.94964,0.906667,0.884058,0.945946,0.901408,0.793893,0.87218,0.882353,0.884354,0.874074,0.864865,0.879433,0.905109,0.338983,0.946667,0.879433,0.93617,0.926174,0.853147,0.898551,0.901408,0.844444,0.92517,0.868217] kappa 0.8325134554892805 kappa 0.8273108423043704 kappa 0.8189859781753266 kappa 0.8319902523137102 kappa 0.8351132776983686 kappa 0.8215873111647332 kappa 0.8304304076770291 kappa 0.8314563343157244 kappa 0.8101223514343956 kappa 0.8215747356067903 kb_relative_information_score 0.8369148516927218 kb_relative_information_score 0.8317749060789555 kb_relative_information_score 0.8236810202180425 kb_relative_information_score 0.8362048560494295 kb_relative_information_score 0.839412739451907 kb_relative_information_score 0.8262417614460409 kb_relative_information_score 0.8348492466271301 kb_relative_information_score 0.8357666825420267 kb_relative_information_score 0.8151276164054317 kb_relative_information_score 0.8263592919141333 mean_absolute_error 0.01238461538461535 mean_absolute_error 0.012769230769230732 mean_absolute_error 0.013384615384615346 mean_absolute_error 0.012423076923076887 mean_absolute_error 0.012192307692307659 mean_absolute_error 0.013192307692307654 mean_absolute_error 0.012538461538461504 mean_absolute_error 0.012461538461538427 mean_absolute_error 0.014038461538461498 mean_absolute_error 0.013192307692307654 mean_prior_absolute_error 0.07396194754511427 mean_prior_absolute_error 0.07396200900367966 mean_prior_absolute_error 0.07396191681583157 mean_prior_absolute_error 0.07396192641873242 mean_prior_absolute_error 0.07396195714801512 mean_prior_absolute_error 0.07396196483033579 mean_prior_absolute_error 0.07396196867149613 mean_prior_absolute_error 0.07396191489525139 mean_prior_absolute_error 0.07396179389870075 mean_prior_absolute_error 0.0739617842957999 number_of_instances 2000 [79,77,74,81,77,77,77,73,76,74,74,76,79,78,75,80,78,76,75,79,82,77,75,78,79,74] number_of_instances 2000 [78,77,74,81,77,77,77,73,76,74,74,76,79,79,75,80,78,76,75,79,81,77,75,79,79,74] number_of_instances 2000 [79,77,74,81,76,78,77,73,76,74,74,76,79,79,75,80,78,76,74,79,81,77,75,79,79,74] number_of_instances 2000 [79,77,74,80,76,78,77,73,76,75,73,76,80,79,75,80,78,76,74,79,81,77,75,79,79,74] number_of_instances 2000 [79,77,74,80,77,78,77,73,76,75,74,76,80,78,75,80,78,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,74,80,77,78,78,73,75,75,74,76,79,78,76,80,79,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,73,80,77,78,78,74,75,75,74,76,79,78,76,80,79,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,73,80,77,77,78,74,75,75,74,76,79,78,76,81,79,76,75,80,81,76,75,79,78,73] number_of_instances 2000 [79,76,73,81,77,77,77,74,75,75,74,77,79,78,75,81,78,75,75,80,82,76,76,78,79,73] number_of_instances 2000 [79,77,73,81,77,77,77,74,75,75,74,76,79,78,75,81,78,75,75,80,82,76,76,78,79,73] precision 0.9511132291265488 [1,0.984848,1,0.971831,0.967742,1,0.984375,0.962963,0.933333,0.96875,0.943662,1,0.960526,1,0.983607,0.215054,0.971014,0.985714,0.985294,0.970588,1,1,1,1,0.984615,0.983051] precision 0.9463821327110663 [1,0.967742,0.984848,0.984848,0.969231,0.939394,0.985075,0.965517,1,0.970588,0.880597,0.983871,0.942857,0.986111,1,0.205405,0.973333,0.96875,0.985915,1,1,0.984127,0.984848,0.983333,0.986111,1] precision 0.9446092839642836 [1,1,0.984375,0.948052,0.966667,0.984375,0.969231,0.929825,0.984615,0.897059,0.955224,1,0.973333,1,1,0.204663,0.943662,0.933333,0.983871,0.986667,1,0.955882,1,1,0.984375,1] precision 0.9475943494052202 [1,0.96875,0.982759,0.961039,0.984375,0.971014,0.985507,0.941176,1,0.984615,0.897059,1,0.957746,1,0.983607,0.216438,0.948052,0.984127,0.984615,1,1,0.983871,1,1,0.959459,0.968254] precision 0.9540230089866393 [1,0.955224,1,0.972222,0.986111,0.984615,0.984615,1,1,0.953125,0.952381,1,1,1,1,0.213514,0.925,0.969697,0.984375,0.984848,1,0.984375,1,1,0.985294,1] precision 0.9492530846894123 [1,0.985714,1,0.96875,0.984127,0.983607,1,0.923077,1,0.966102,0.919355,1,0.985714,1,0.983333,0.202564,0.958904,1,1,1,1,0.954545,1,0.936508,0.971831,0.983871] precision 0.9459641515404789 [1,1,1,0.986486,0.984127,0.974684,0.958904,0.983051,0.966102,0.984375,0.949153,1,0.833333,0.983607,1,0.216066,0.985507,0.939394,0.958333,0.971831,1,0.982759,1,0.971429,1,1] precision 0.9490502971927718 [1,0.971014,0.984375,1,1,0.969231,0.970588,1,1,0.96875,0.919355,0.984615,0.938272,0.983051,1,0.20765,0.922078,0.971014,1,1,0.971831,0.983871,1,1,0.972222,1] precision 0.9474645526610844 [1,0.983333,1,0.92,1,0.982759,0.929577,0.980392,0.983333,0.940299,0.969231,0.984127,0.985915,1,1,0.195122,0.984848,0.944444,0.984848,0.985294,1,1,1,0.985075,0.957143,0.981132] precision 0.949586547044096 [1,0.971014,1,0.985507,1,0.985915,0.984615,0.912281,1,0.983607,0.890411,1,0.927536,0.984127,1,0.204604,0.986111,0.939394,1,1,1,1,0.969697,1,1,1] predictive_accuracy 0.8390000000000001 predictive_accuracy 0.8340000000000001 predictive_accuracy 0.826 predictive_accuracy 0.8384999999999999 predictive_accuracy 0.8415 predictive_accuracy 0.8284999999999999 predictive_accuracy 0.8370000000000001 predictive_accuracy 0.838 predictive_accuracy 0.8175 predictive_accuracy 0.8284999999999999 prior_entropy 4.699825815607033 prior_entropy 4.699854731688913 prior_entropy 4.699809751694497 prior_entropy 4.699813724681224 prior_entropy 4.6998289081692235 prior_entropy 4.699832499136173 prior_entropy 4.69983445932086 prior_entropy 4.699808889896364 prior_entropy 4.69975160696033 prior_entropy 4.699746889170326 recall 0.839 [0.835443,0.844156,0.878378,0.851852,0.779221,0.779221,0.818182,0.712329,0.736842,0.837838,0.905405,0.842105,0.924051,0.807692,0.8,1,0.858974,0.907895,0.893333,0.835443,0.829268,0.792208,0.866667,0.871795,0.810127,0.783784] recall 0.834 [0.782051,0.779221,0.878378,0.802469,0.818182,0.805195,0.857143,0.767123,0.75,0.891892,0.797297,0.802632,0.835443,0.898734,0.72,0.95,0.935897,0.815789,0.933333,0.873418,0.938272,0.805195,0.866667,0.746835,0.898734,0.716216] recall 0.826 [0.797468,0.896104,0.851351,0.901235,0.763158,0.807692,0.818182,0.726027,0.842105,0.824324,0.864865,0.736842,0.924051,0.822785,0.826667,0.9875,0.858974,0.736842,0.824324,0.936709,0.790123,0.844156,0.773333,0.734177,0.797468,0.77027] recall 0.8385 [0.924051,0.805195,0.77027,0.925,0.828947,0.858974,0.883117,0.657534,0.736842,0.853333,0.835616,0.855263,0.85,0.810127,0.8,0.9875,0.935897,0.815789,0.864865,0.797468,0.938272,0.792208,0.84,0.683544,0.898734,0.824324] recall 0.8415 [0.873418,0.831169,0.77027,0.875,0.922078,0.820513,0.831169,0.821918,0.776316,0.813333,0.810811,0.868421,0.8875,0.782051,0.813333,0.9875,0.948718,0.842105,0.84,0.8125,0.82716,0.828947,0.906667,0.734177,0.858974,0.780822] recall 0.8285 [0.835443,0.907895,0.824324,0.775,0.805195,0.769231,0.820513,0.821918,0.773333,0.76,0.77027,0.763158,0.873418,0.820513,0.776316,0.9875,0.886076,0.907895,0.8,0.85,0.888889,0.828947,0.813333,0.746835,0.884615,0.835616] recall 0.837 [0.822785,0.710526,0.808219,0.9125,0.805195,0.987179,0.897436,0.783784,0.76,0.84,0.756757,0.881579,0.949367,0.769231,0.842105,0.975,0.860759,0.815789,0.92,0.8625,0.716049,0.75,0.826667,0.860759,0.833333,0.794521] recall 0.838 [0.911392,0.881579,0.863014,0.8625,0.74026,0.818182,0.846154,0.743243,0.826667,0.826667,0.77027,0.842105,0.962025,0.74359,0.723684,0.938272,0.898734,0.881579,0.893333,0.875,0.851852,0.802632,0.84,0.797468,0.897436,0.726027] recall 0.8175 [0.822785,0.776316,0.876712,0.851852,0.831169,0.74026,0.857143,0.675676,0.786667,0.84,0.851351,0.805195,0.886076,0.74359,0.773333,0.987654,0.833333,0.906667,0.866667,0.8375,0.756098,0.723684,0.802632,0.846154,0.848101,0.712329] recall 0.8285 [0.797468,0.87013,0.90411,0.839506,0.792208,0.909091,0.831169,0.702703,0.773333,0.8,0.878378,0.776316,0.810127,0.794872,0.826667,0.987654,0.910256,0.826667,0.88,0.8625,0.743902,0.815789,0.842105,0.730769,0.860759,0.767123] relative_absolute_error 0.16744577172012887 relative_absolute_error 0.17264580750633007 relative_absolute_error 0.18096631294648066 relative_absolute_error 0.1679658376222402 relative_absolute_error 0.1648456606942946 relative_absolute_error 0.17836610645174175 relative_absolute_error 0.16952579499541695 relative_absolute_error 0.16848588194595945 relative_absolute_error 0.1898069367772339 relative_absolute_error 0.17836654182850495 root_mean_prior_squared_error 0.1923044115328483 root_mean_prior_squared_error 0.19230457132777806 root_mean_prior_squared_error 0.19230433163533361 root_mean_prior_squared_error 0.19230435660331052 root_mean_prior_squared_error 0.19230443650081483 root_mean_prior_squared_error 0.19230445647518574 root_mean_prior_squared_error 0.1923044664623704 root_mean_prior_squared_error 0.19230432664173788 root_mean_prior_squared_error 0.192304012044943 root_mean_prior_squared_error 0.19230398707692134 root_mean_squared_error 0.11128618685450298 root_mean_squared_error 0.11300102109817739 root_mean_squared_error 0.1156918985262812 root_mean_squared_error 0.1114588575353116 root_mean_squared_error 0.11041878324047796 root_mean_squared_error 0.11485777157993121 root_mean_squared_error 0.111975271995479 root_mean_squared_error 0.11163126113028746 root_mean_squared_error 0.11848401385191801 root_mean_squared_error 0.11485777157993121 root_relative_squared_error 0.5786980442489419 root_relative_squared_error 0.58761484616801 root_relative_squared_error 0.6016083857417605 root_relative_squared_error 0.5795961126623422 root_relative_squared_error 0.5741873939554697 root_relative_squared_error 0.5972704620849598 root_relative_squared_error 0.5822811817914277 root_relative_squared_error 0.5804927173492878 root_relative_squared_error 0.6161286631098853 root_relative_squared_error 0.5972719199731842 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 55794.22400000112 usercpu_time_millis 59684.9319999983 usercpu_time_millis 56465.48000000075 usercpu_time_millis 56523.09200000127 usercpu_time_millis 57505.58000000092 usercpu_time_millis 58140.142000000196 usercpu_time_millis 56533.66999999889 usercpu_time_millis 53798.179999999775 usercpu_time_millis 45768.809999999576 usercpu_time_millis 45491.735999999946 usercpu_time_millis_testing 3537.4680000004446 usercpu_time_millis_testing 3631.7459999991115 usercpu_time_millis_testing 3718.3960000002116 usercpu_time_millis_testing 3735.316000000239 usercpu_time_millis_testing 3738.119999999981 usercpu_time_millis_testing 3808.8520000001154 usercpu_time_millis_testing 3717.7259999989474 usercpu_time_millis_testing 3032.0339999998396 usercpu_time_millis_testing 3060.1000000006024 usercpu_time_millis_testing 3141.1499999994703 usercpu_time_millis_training 52256.75600000068 usercpu_time_millis_training 56053.18599999919 usercpu_time_millis_training 52747.08400000054 usercpu_time_millis_training 52787.77600000103 usercpu_time_millis_training 53767.46000000094 usercpu_time_millis_training 54331.29000000008 usercpu_time_millis_training 52815.943999999945 usercpu_time_millis_training 50766.145999999935 usercpu_time_millis_training 42708.70999999897 usercpu_time_millis_training 42350.586000000476 wall_clock_time_millis 28424.365758895874 wall_clock_time_millis 32439.06807899475 wall_clock_time_millis 29023.46897125244 wall_clock_time_millis 28813.889026641846 wall_clock_time_millis 29306.387186050415 wall_clock_time_millis 29682.12080001831 wall_clock_time_millis 28943.211793899536 wall_clock_time_millis 27336.10987663269 wall_clock_time_millis 23068.383932113647 wall_clock_time_millis 22899.112939834595 wall_clock_time_millis_testing 1792.8929328918457 wall_clock_time_millis_testing 1863.6598587036133 wall_clock_time_millis_testing 1889.343023300171 wall_clock_time_millis_testing 1905.2081108093262 wall_clock_time_millis_testing 1889.8720741271973 wall_clock_time_millis_testing 1931.1299324035645 wall_clock_time_millis_testing 1905.890941619873 wall_clock_time_millis_testing 1526.2527465820312 wall_clock_time_millis_testing 1543.7440872192383 wall_clock_time_millis_testing 1582.1259021759033 wall_clock_time_millis_training 26631.47282600403 wall_clock_time_millis_training 30575.408220291138 wall_clock_time_millis_training 27134.12594795227 wall_clock_time_millis_training 26908.68091583252 wall_clock_time_millis_training 27416.515111923218 wall_clock_time_millis_training 27750.990867614746 wall_clock_time_millis_training 27037.320852279663 wall_clock_time_millis_training 25809.85713005066 wall_clock_time_millis_training 21524.63984489441 wall_clock_time_millis_training 21316.98703765869