6021907 1 Jan van Rijn 9954 Supervised Classification 6969 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1) 4056592 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.8786210683027665 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 10 6902 min_samples_split 18 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 33400 6902 verbose 0 6902 warm_start false 6902 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "median" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse false 6948 threshold 0.0 6949 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12966933 description https://api.openml.org/data/download/12966933/description.xml -1 12966934 predictions https://api.openml.org/data/download/12966934/predictions.arff area_under_roc_curve 0.9789855587121213 [0.970683,0.993332,0.999724,0.998264,0.993174,0.978378,0.993371,0.960602,0.992898,0.997475,0.995818,0.993411,0.992306,0.961529,0.993411,0.983507,0.999053,0.960069,0.96583,0.9491,0.995107,0.993687,0.974195,1,0.984454,0.9506,0.956084,0.93604,0.994003,0.997909,0.99712,0.999053,0.988479,0.969934,0.991438,0.997238,0.968434,0.971275,0.997475,0.998737,0.96804,0.98907,0.997317,0.990017,0.986742,0.96149,0.998106,0.99053,0.958373,0.986427,0.976997,0.968947,0.991201,0.94334,0.945885,0.944642,1,0.995344,0.984848,0.937382,0.995778,0.985914,0.990491,0.985164,0.995344,0.989702,0.966343,0.998974,0.901772,0.945115,0.959576,0.964173,0.985717,0.986387,0.95782,0.956577,0.996962,0.948153,0.995147,0.996804,0.952671,0.977786,0.982876,0.982086,0.977865,0.951862,0.992582,0.974905,0.988242,0.992266,0.99779,0.997633,0.98331,0.971749,0.952967,0.990688,0.985322,0.982757,0.938881,0.974511] average_cost 0 f_measure 0.4979321555449976 [0.387097,0.648649,0.903226,0.608696,0.685714,0.322581,0.5625,0.647059,0.387097,0.758621,0.526316,0.611111,0.470588,0.148148,0.628571,0.333333,0.722222,0.4,0.375,0.095238,0.645161,0.666667,0.461538,1,0.5,0.173913,0.342857,0.5,0.666667,0.685714,0.514286,0.8,0.5625,0.242424,0.727273,0.742857,0.322581,0.294118,0.8125,0.722222,0.5,0.473684,0.727273,0.5625,0.6875,0.357143,0.8,0.666667,0.222222,0.625,0.439024,0.277778,0.514286,0.153846,0.5,0.176471,0.888889,0.619048,0.285714,0.451613,0.451613,0.424242,0.432432,0.285714,0.606061,0.388889,0.193548,0.756757,0.222222,0.266667,0.129032,0.666667,0.411765,0.606061,0.153846,0.611111,0.75,0.181818,0.857143,0.666667,0.642857,0.258065,0.4375,0.375,0.457143,0.6875,0.521739,0.424242,0.272727,0.526316,0.666667,0.717949,0.482759,0.25,0.5,0.540541,0.588235,0.296296,0,0.551724] kappa 0.5037878787878788 kb_relative_information_score 1060.2946945342048 mean_absolute_error 0.013220679549402732 mean_prior_absolute_error 0.019800000000000036 number_of_instances 1600 [16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] precision 0.5060289193348791 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[0.375,0.75,0.875,0.4375,0.75,0.3125,0.5625,0.6875,0.375,0.6875,0.625,0.6875,0.5,0.125,0.6875,0.25,0.8125,0.5,0.375,0.0625,0.625,0.6875,0.5625,1,0.5,0.125,0.375,0.5625,0.5625,0.75,0.5625,0.875,0.5625,0.25,0.75,0.8125,0.3125,0.3125,0.8125,0.8125,0.5,0.5625,0.75,0.5625,0.6875,0.3125,0.75,0.625,0.1875,0.625,0.5625,0.3125,0.5625,0.125,0.5,0.1875,1,0.8125,0.25,0.4375,0.4375,0.4375,0.5,0.25,0.625,0.4375,0.1875,0.875,0.25,0.25,0.125,0.6875,0.4375,0.625,0.125,0.6875,0.75,0.125,0.75,0.625,0.5625,0.25,0.4375,0.375,0.5,0.6875,0.375,0.4375,0.1875,0.625,0.75,0.875,0.4375,0.1875,0.4375,0.625,0.625,0.25,0,0.5] relative_absolute_error 0.6677110883536721 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.0788504464677573 root_relative_squared_error 0.7924768045016818 total_cost 0 area_under_roc_curve 0.9822664148953107 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[0.974684,1,1,1,0.993711,0.968354,0.968553,1,0.987421,0.996835,0.987342,0.984177,1,0.861635,1,0.990506,1,1,0.993711,0.996835,0.974684,0.977848,1,1,0.996835,0.924051,0.968354,1,1,0.993671,1,1,0.987342,0.924051,1,1,0.981013,0.927215,0.987342,1,1,0.993671,0.981132,1,1,0.974843,1,0.987342,0.993671,0.968354,0.974843,0.861635,1,0.968553,0.691456,0.908228,1,0.984177,0.993671,0.981132,1,0.996835,1,1,0.993671,0.993671,0.90566,1,0.648734,0.917722,0.990506,1,1,0.974843,0.955696,1,0.996835,0.917722,1,0.993711,0.993711,1,0.987342,0.987342,0.981132,1,1,1,1,1,1,0.990506,0.937107,0.993711,0.688291,1,0.977848,0.993711,0.949686,0.981013] area_under_roc_curve 0.980971732943237 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[0.974843,0.952532,0.993711,1,1,0.993711,1,0.389937,0.990506,1,1,1,0.993671,0.987342,0.996835,1,1,1,0.990506,1,1,1,1,1,1,0.886792,1,0.987342,0.993671,1,0.996835,1,1,0.981132,0.996835,0.993671,0.962025,1,1,1,0.968553,0.996835,1,0.974684,1,0.898734,1,0.984177,1,0.993711,0.996835,0.962025,1,0.971519,0.962025,0.90566,1,0.993711,0.962025,1,1,0.977848,0.987342,0.981013,1,1,0.984177,1,0.990506,0.949686,0.930818,1,0.96519,1,0.952532,0.996835,1,0.987421,0.955975,0.996835,1,0.962264,1,0.955975,0.993671,1,0.984177,0.990506,0.974843,0.996835,1,1,1,0.977848,1,1,1,1,0.993671,1] 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 kappa 0.5136586136112428 kappa 0.5454007339883983 kappa 0.48837392917768746 kappa 0.4820166607446011 kappa 0.5010263698089372 kappa 0.4759687475337385 kappa 0.4442909578876742 kappa 0.46312963840202115 kappa 0.5452751243388333 kappa 0.5767195767195767 kb_relative_information_score 107.93161355764991 kb_relative_information_score 107.45255656851482 kb_relative_information_score 103.87913635593623 kb_relative_information_score 102.77406205945545 kb_relative_information_score 103.11024527157612 kb_relative_information_score 104.07397356272449 kb_relative_information_score 105.58206332505355 kb_relative_information_score 104.39623993962401 kb_relative_information_score 110.29872474329716 kb_relative_information_score 110.79607915037542 mean_absolute_error 0.012928159060812797 mean_absolute_error 0.013057474809251377 mean_absolute_error 0.013248130359121571 mean_absolute_error 0.013522513199379962 mean_absolute_error 0.013527254903641896 mean_absolute_error 0.01328684203830445 mean_absolute_error 0.013581407876174244 mean_absolute_error 0.013462378842509327 mean_absolute_error 0.012826588443204234 mean_absolute_error 0.012766045961627781 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 mean_prior_absolute_error 0.019800000000000033 number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] number_of_instances 160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1] predictive_accuracy 0.51875 predictive_accuracy 0.55 predictive_accuracy 0.49375 predictive_accuracy 0.4875 predictive_accuracy 0.50625 predictive_accuracy 0.48125 predictive_accuracy 0.45 predictive_accuracy 0.46875 predictive_accuracy 0.55 predictive_accuracy 0.58125 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 prior_entropy 6.6438561897747395 recall 0.51875 [1,1,1,0,0.5,1,0.5,1,0,1,1,0.5,0,0,1,1,1,0,0,0,1,0,1,1,0,0,0.5,0.5,0.5,0,1,1,0.5,0,1,0,0,1,0,1,1,0,1,1,1,0.5,1,1,0,0.5,0.5,0.5,1,0,1,0,1,1,0,0.5,0,1,0,0,1,0.5,0,1,0,0,0,1,0.5,0.5,1,1,0.5,0.5,0.5,0.5,1,0,1,1,0.5,0.5,0,0.5,0,0,1,1,1,0,0.5,0.5,1,0,0,1] recall 0.55 [1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,0,0,1,1,0.5,0.5,0,0.5,1,0.5,1,0.5,0.5,1,1,0,0,0,1,0,1,1,0.5,0.5,0,1,1,0,1,0,0.5,1,0.5,1,0,1,1,0,0.5,1,1,1,0.5,1,0.5,0.5,1,0,0,0,1,0.5,0.5,0,1,0.5,0,1,0.5,0.5,0,0,0,0.5,0.5,0.5,0.5,0,0,0.5,1,0.5,0,0,0.5,1,0,0,1] recall 0.49375 [0,0.5,1,1,0.5,0,0,1,0.5,0.5,0.5,0.5,1,0,0,0,1,0.5,0,0,1,0,0,1,0,0.5,0,1,1,1,0,1,1,0,0,1,1,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,1,1,0,0,1,0.5,1,1,0,0,0,0,0.5,1,0.5,0.5,0,1,0,0,0.5,1,0,0.5,0,0.5,1,0,0.5,1,0,0,1,0.5,1,0,1,1,0.5,1,0.5,1,0,0,0.5,1,0.5,0.5,0,0.5] recall 0.4875 [0.5,1,1,1,0.5,0,1,0.5,0,0,1,0.5,0,0,1,0,0.5,0.5,0,0,0,1,0.5,1,0,0,0.5,0,0.5,0.5,1,1,0.5,0.5,1,0,1,0,1,1,0.5,0,1,1,1,1,0.5,1,0,1,0,1,0,0,1,1,1,1,0,0.5,1,0,1,0,0.5,0.5,0.5,1,0,0.5,0,0,0,1,0,0.5,1,0,1,0.5,0,0,1,0,0,0,1,0.5,0,1,1,1,0,0,1,0,0.5,0,0,0] recall 0.50625 [0.5,1,0.5,1,0,0.5,0,0,0,1,0,0.5,1,0,1,0,0.5,1,1,0,0,0.5,1,1,0.5,0,0.5,1,1,0.5,1,1,0,0,0,1,0.5,0,0.5,1,1,0.5,0,1,1,0,1,0,0.5,0.5,0,0,0,0,0.5,0,1,0.5,1,0,1,1,1,0,0.5,0,0,1,0,0,0,0.5,1,0,0,1,0.5,0,0.5,1,1,1,0,0.5,0,1,1,1,1,1,1,1,0,1,0.5,1,0.5,1,0,0.5] recall 0.48125 [0,1,1,0,1,0,1,0.5,1,0.5,0.5,1,1,0,1,0.5,1,1,0,0,1,0.5,0.5,1,0.5,0,0.5,1,1,1,0,1,0.5,0,0,1,0,0.5,1,0.5,1,0.5,1,1,1,0,1,0.5,0,0.5,1,0,0.5,0,0,0,1,1,0.5,1,0.5,0,0,0,0.5,0.5,0,1,0.5,0.5,0,1,1,1,0,0,0.5,0,1,0,1,0,0,0,0,1,0,0,0,1,1,0.5,0,0,0,0,0.5,0,0,0.5] recall 0.45 [0.5,0,1,0,1,0,1,1,1,0.5,1,1,0.5,0,0,0,0,0,0,0,0.5,1,0.5,1,0.5,0,0,0.5,0,1,0.5,0,1,1,1,0.5,0,0.5,1,0,0,0.5,1,0,1,0,0,0.5,0,1,1,0,0.5,0,0.5,0,1,1,0.5,0,0,0,0,0,0,1,0,1,0.5,0,0,1,0,0,0,1,1,0,1,1,0.5,1,0.5,0.5,1,1,0,0,0,0,1,1,0.5,1,0,0.5,1,0,0,0.5] recall 0.46875 [0.5,1,1,0,1,0.5,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,1,0.5,1,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0.5,0,1,1,1,0.5,1,0,1,0.5,1,1,0,0,0,0,0.5,1,0.5,0,1,0.5,0,1,0,0.5,0,0.5,1,0,0,0.5,0,0.5,0,1,1,0,0,1,1,0,1,0,0,0,0,1,0,0.5,1,0,0,0.5,0,1,0,0,0,1,0.5,0,0,0.5] recall 0.55 [0,1,1,0.5,1,1,0.5,1,0,1,0,1,0.5,0.5,1,0,1,1,1,0,1,1,1,1,0.5,0,0,1,0.5,1,1,1,0,0,1,1,0.5,0,1,0,0,0.5,0,0.5,0,0.5,1,0.5,0,1,1,0,1,0,0,0,1,0,0,0,0,1,1,0,1,1,0.5,0,0.5,1,1,0,0.5,1,0,0.5,1,1,1,0.5,1,1,0,0,0.5,1,0,0,0,1,1,0.5,0.5,0,1,0.5,0,0.5,0,1] recall 0.58125 [0,0,0,0.5,1,0,0,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,0.5,0.5,1,0,1,1,0,1,1,1,0,1,0.5,0.5,1,0.5,1,0.5,1,0,1,0.5,1,0,0.5,0,1,1,0,1,1,0,0,0.5,1,0,0,1,0.5,0,0,0,0,1,0.5,0.5,1,0,0,1,0.5,0,1,0,1,1,0,0.5,0,0.5,0.5,1,1,0.5,1,1,1,0.5,0,0] relative_absolute_error 0.6529373263036756 relative_absolute_error 0.6594684247096645 relative_absolute_error 0.6690974928849266 relative_absolute_error 0.682955212089896 relative_absolute_error 0.6831946921031249 relative_absolute_error 0.6710526281971932 relative_absolute_error 0.6859296907158697 relative_absolute_error 0.6799181233590558 relative_absolute_error 0.6478074971315259 relative_absolute_error 0.644749796041806 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_prior_squared_error 0.09949874371066206 root_mean_squared_error 0.0776551747280369 root_mean_squared_error 0.07738071192688813 root_mean_squared_error 0.07972842375967955 root_mean_squared_error 0.08016698578304148 root_mean_squared_error 0.08023374528273587 root_mean_squared_error 0.08012756914249684 root_mean_squared_error 0.08071110480259011 root_mean_squared_error 0.07961445053828126 root_mean_squared_error 0.0765106233037278 root_mean_squared_error 0.07620998167221041 root_relative_squared_error 0.7804638715223854 root_relative_squared_error 0.7777054165820205 root_relative_squared_error 0.8013008082948894 root_relative_squared_error 0.8057085224730427 root_relative_squared_error 0.8063794806902491 root_relative_squared_error 0.8053123703300642 root_relative_squared_error 0.811177124379524 root_relative_squared_error 0.8001553343205674 root_relative_squared_error 0.768960696892991 root_relative_squared_error 0.7659391348078288 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 10216.971712000486 usercpu_time_millis 10148.971959000392 usercpu_time_millis 9979.357241999878 usercpu_time_millis 10009.477985000103 usercpu_time_millis 10058.693259999927 usercpu_time_millis 10101.40205000016 usercpu_time_millis 10024.835478000114 usercpu_time_millis 10093.906325999797 usercpu_time_millis 10118.166645000201 usercpu_time_millis 10103.89330199996 usercpu_time_millis_testing 37.83088900036091 usercpu_time_millis_testing 40.38142500030517 usercpu_time_millis_testing 36.458917999880214 usercpu_time_millis_testing 34.88248099984048 usercpu_time_millis_testing 35.191152000152215 usercpu_time_millis_testing 36.239484999896376 usercpu_time_millis_testing 35.069948000000295 usercpu_time_millis_testing 39.608910999959335 usercpu_time_millis_testing 35.98096799987616 usercpu_time_millis_testing 35.66412800000762 usercpu_time_millis_training 10179.140823000125 usercpu_time_millis_training 10108.590534000086 usercpu_time_millis_training 9942.898323999998 usercpu_time_millis_training 9974.595504000263 usercpu_time_millis_training 10023.502107999775 usercpu_time_millis_training 10065.162565000264 usercpu_time_millis_training 9989.765530000113 usercpu_time_millis_training 10054.297414999837 usercpu_time_millis_training 10082.185677000325 usercpu_time_millis_training 10068.229173999953