6000514 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) 4035246 bootstrap false 6902 class_weight null 6902 criterion "gini" 6902 max_depth null 6902 max_features 0.8458962901968512 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 13 6902 min_samples_split 17 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 46186 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 "mean" 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 12924145 description https://api.openml.org/data/download/12924145/description.xml -1 12924146 predictions https://api.openml.org/data/download/12924146/predictions.arff area_under_roc_curve 0.97959655145202 [0.951468,0.9927,0.995975,0.998106,0.997238,0.9884,0.992424,0.990096,0.992661,0.999329,0.987137,0.986585,0.991832,0.962437,0.99637,0.975971,0.997593,0.969342,0.96804,0.969263,0.995226,0.990215,0.988281,0.999171,0.994792,0.920257,0.921895,0.976484,0.979246,0.99783,0.992109,0.958767,0.992306,0.974156,0.993884,0.993924,0.98114,0.9622,0.990767,0.995857,0.994634,0.997199,0.990945,0.983073,0.988991,0.994437,0.99057,0.993845,0.982915,0.911754,0.982363,0.981968,0.980232,0.965791,0.980607,0.963226,0.999388,0.978042,0.98544,0.957781,0.998106,0.990925,0.919705,0.976326,0.996291,0.988557,0.974195,0.988045,0.932134,0.972143,0.955492,0.996113,0.945589,0.990412,0.936592,0.989781,0.996094,0.948114,0.995522,0.990372,0.975576,0.955788,0.985953,0.959557,0.979403,0.968691,0.995107,0.979403,0.989189,0.99566,0.998146,0.997277,0.987453,0.976997,0.972479,0.975813,0.980548,0.975852,0.931147,0.994437] average_cost 0 f_measure 0.502834478804061 [0.4375,0.461538,0.722222,0.785714,0.705882,0.3125,0.6875,0.514286,0.516129,0.9375,0.4,0.606061,0.421053,0.363636,0.594595,0.529412,0.787879,0.387097,0.190476,0,0.510638,0.521739,0.352941,0.8,0.709677,0,0.083333,0.482759,0.8125,0.774194,0.648649,0.647059,0.6,0.3125,0.578947,0.702703,0.4,0.181818,0.413793,0.705882,0.705882,0.777778,0.634146,0.4,0.434783,0.541667,0.645161,0.6875,0.648649,0.571429,0.5,0.387097,0.457143,0.25,0.514286,0.25,0.9375,0.580645,0.342857,0.363636,0.727273,0.684211,0.333333,0.666667,0.666667,0.526316,0.1875,0.434783,0.210526,0.230769,0.117647,0.6875,0.512821,0.625,0.24,0.5,0.666667,0.344828,0.628571,0.384615,0.26087,0.606061,0.25,0.363636,0.487805,0.592593,0.75,0.5,0.594595,0.717949,0.8,0.648649,0.428571,0.333333,0.551724,0.484848,0.413793,0.307692,0,0.585366] kappa 0.5176767676767676 kb_relative_information_score 1045.9600279409078 mean_absolute_error 0.0136489921049716 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 0.5210800725355653 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[0.4375,0.5625,0.8125,0.6875,0.75,0.3125,0.6875,0.5625,0.5,0.9375,0.4375,0.625,0.5,0.25,0.6875,0.5625,0.8125,0.375,0.125,0,0.75,0.375,0.375,0.875,0.6875,0,0.0625,0.4375,0.8125,0.75,0.75,0.6875,0.75,0.3125,0.6875,0.8125,0.5,0.1875,0.375,0.75,0.75,0.875,0.8125,0.375,0.3125,0.8125,0.625,0.6875,0.75,0.625,0.5,0.375,0.5,0.1875,0.5625,0.25,0.9375,0.5625,0.375,0.375,0.75,0.8125,0.3125,0.75,0.75,0.625,0.1875,0.3125,0.125,0.1875,0.0625,0.6875,0.625,0.625,0.1875,0.375,0.75,0.3125,0.6875,0.3125,0.1875,0.625,0.25,0.375,0.625,0.5,0.75,0.5,0.6875,0.875,0.875,0.75,0.375,0.25,0.5,0.5,0.375,0.25,0,0.75] relative_absolute_error 0.689343035604625 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.07984060720409358 root_relative_squared_error 0.8024282943337105 total_cost 0 area_under_roc_curve 0.9737053180479261 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[0.876582,0.949686,1,1,1,0.993671,0.987421,0.990506,1,1,0.990506,0.987342,1,0.823899,1,1,1,0.996835,1,0.990506,0.996835,1,1,1,1,0.955696,0.968354,1,1,0.996835,1,0.393082,1,0.939873,1,0.996835,0.984177,0.898734,0.990506,0.996835,0.996835,1,1,0.993711,0.993711,1,1,0.996835,0.955696,1,0.987421,0.974843,1,0.987421,0.93038,0.955696,0.996855,0.987342,1,0.993711,0.996835,1,1,1,1,1,0.899371,0.974684,0.933544,0.981013,0.984177,0.996835,1,0.993711,0.879747,0.993711,0.996835,0.977848,1,1,1,1,0.981013,0.993671,0.937107,0.883648,1,1,1,0.990506,1,0.993671,0.949686,1,0.856013,0.968553,0.990506,0.981132,0.974843,0.993671] area_under_roc_curve 0.987751522569859 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[0.792453,1,0.955975,1,1,0.981132,1,0.974843,1,1,1,0.993711,0.984177,0.939873,1,0.974843,1,0.968553,0.981013,1,0.990506,0.990506,1,1,1,0.918239,0.987421,0.96519,0.993671,1,1,1,1,0.981132,0.993671,0.993671,0.971519,0.96519,0.984177,1,0.993711,0.996835,0.984177,0.981013,0.996835,0.996835,1,0.977848,1,0.987421,0.943038,0.996835,1,0.977848,1,0.955975,1,0.987421,0.990506,0.993671,1,1,0.484177,0.939873,0.993711,0.993711,0.984177,0.993711,0.974684,0.937107,0.962264,1,0.949367,1,0.914557,0.987342,1,0.974843,1,0.993671,0.987342,0.987421,1,0.484277,0.996835,0.990506,0.996835,0.987342,1,0.993671,1,1,0.984177,0.993671,1,1,0.880503,0.993671,0.974684,1] 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 0.46963418965313125 kappa 0.5264030310206015 kappa 0.5391050430116012 kappa 0.5075563271909402 kappa 0.5514845230574859 kappa 0.526328254519618 kappa 0.5831524099001303 kappa 0.5765356507999211 kappa 0.44431288973083904 kappa 0.4506708760852407 kb_relative_information_score 101.2562392081664 kb_relative_information_score 104.21440744545687 kb_relative_information_score 104.79399456561521 kb_relative_information_score 104.26565872802377 kb_relative_information_score 104.99252161306995 kb_relative_information_score 105.74392544646713 kb_relative_information_score 110.63987822909645 kb_relative_information_score 104.33310083014281 kb_relative_information_score 103.51565992523598 kb_relative_information_score 102.20464194963377 mean_absolute_error 0.013885519174980834 mean_absolute_error 0.01324604879637233 mean_absolute_error 0.013753548585849807 mean_absolute_error 0.01371414124516652 mean_absolute_error 0.013468976000687107 mean_absolute_error 0.013851426348488804 mean_absolute_error 0.013161954854149375 mean_absolute_error 0.013718498482575881 mean_absolute_error 0.013758807837861483 mean_absolute_error 0.013930999723584012 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 0.475 predictive_accuracy 0.53125 predictive_accuracy 0.54375 predictive_accuracy 0.5125 predictive_accuracy 0.55625 predictive_accuracy 0.53125 predictive_accuracy 0.5875 predictive_accuracy 0.58125 predictive_accuracy 0.45 predictive_accuracy 0.45625 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 0.475 [1,0,0.5,1,0,1,1,1,0,1,0,0.5,0.5,0,0.5,0,0,0,0,0,0,0,0,1,0,0,0.5,0.5,0.5,0,0.5,0.5,0.5,0,0.5,0,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,0.5,0.5,0,0,0,1,1,1,1,0,1,1,1,0,0.5,1,0.5,0.5,1,0,0,0.5,1,0,1,0,1,0.5,0.5,1,0,0,1,0,1,0.5,0,0,1,0.5,0,1,1,0.5,0.5,0.5,0.5,1,0,0,1] recall 0.53125 [0,1,1,1,1,0,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0,0,1,0,0,1,1,0,0,0,1,1,0.5,1,0.5,0.5,0,0,0,1,0,1,1,1,1,0.5,0.5,1,0,1,0.5,1,1,0.5,1,0,0,0,1,1,1,0,1,0,0.5,0.5,1,0,0,1,0,0,0,1,1,1,0,0.5,0.5,0.5,1,0,0.5,0.5,0,1,0.5,0.5,1,1,1,1,0.5,1,0,0.5,0.5,0,0,0,0,1] recall 0.54375 [0.5,0.5,1,0,1,0.5,1,0.5,0.5,1,0.5,1,1,0.5,1,1,1,0,0,0,1,0,0,1,1,0,0,1,1,1,1,1,0.5,0.5,1,1,1,0,1,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,0.5,1,1,0,1,0,1,1,0,0.5,0,1,0.5,1,0.5,0.5,0.5,0.5,1,0,0,1,1,0,0,0,1,0.5,0,0,0,1,0,0,1,0,1,0.5,1,1,1,1,0,0,0.5,1,0,0.5,0,0.5] recall 0.5125 [0,1,1,1,1,0.5,1,0.5,0.5,1,0.5,0,1,0,1,0.5,1,0.5,0,0,1,1,1,0,0,0,0,1,0.5,1,1,0,1,0.5,1,1,1,0,0,1,1,1,1,1,0.5,0,0,1,1,0,0,0,0,0,1,0.5,1,0,1,0.5,1,0,0.5,1,1,1,0,0,0,0,0,0.5,1,0.5,0,0.5,0.5,0,1,0.5,0,0.5,0,0.5,1,0,1,0.5,0.5,1,1,1,1,0,1,0,0,0.5,0,0.5] recall 0.55625 [0.5,0,1,0.5,1,0,0,0.5,0,1,0.5,0,0,0,1,1,1,0.5,0,0,1,1,1,1,1,0,0,0,1,0.5,1,0,1,0,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,0,1,0,0,1,1,1,0.5,1,0,0,0,0.5,0,0.5,1,1,0.5,0,1,0.5,1,1,0,1,0,0.5,0,0,1,1,1,1,1,0,0,1,0,0,0.5,0,0,1] recall 0.53125 [0,1,1,1,1,0.5,1,0,1,0.5,0.5,1,0,1,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0,0,1,0.5,0,1,0.5,0.5,1,0.5,0.5,0,0,0,1,1,0,0,0,1,0.5,0,1,0.5,1,0,0.5,1,0.5,0.5,1,1,0.5,1,1,1,0,1,1,1,1,0,0,0,0,0,1,1,0.5,0,0.5,0,0.5,0,0,0.5,0.5,0.5,0,1,1,0,0,1,1,0,0,1,0.5,1,1,0,0,0.5] recall 0.5875 [1,0,0,0.5,1,0,0.5,0.5,1,1,1,1,0,1,1,0,1,1,0.5,0,0.5,0,0.5,1,0.5,0,0,1,1,1,0.5,0,1,0,1,1,0.5,0.5,0,1,0,1,1,1,0,1,0.5,0.5,1,1,0,0.5,1,0,0.5,0,0.5,0.5,0,0,1,1,1,1,0.5,1,0,0.5,0.5,0,0,1,1,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1] recall 0.58125 [1,1,1,0.5,1,0.5,1,1,0,1,0,1,0.5,0,0,0.5,1,0,0.5,0,0.5,0,0,1,1,0,0,0.5,0,0.5,1,1,1,1,1,1,0,0,0.5,1,1,1,1,0,0,1,1,1,1,1,0,0.5,0.5,1,1,0.5,1,1,0,0,1,1,0,1,1,0,0,0.5,0,0.5,0,1,1,1,0,1,1,0,0,1,0,0,0.5,0,0,0.5,1,0,1,1,0,1,1,0,1,0.5,0,0,0,1] recall 0.45 [0,1,1,1,0,0,0,1,0.5,1,0,1,1,0,0.5,0,1,1,0,0,1,0,0,0.5,0.5,0,0,0,1,1,1,1,1,0,0.5,1,0.5,0,1,0,1,0.5,0.5,0,0,0.5,1,1,0,1,0.5,0.5,0.5,0.5,0,0,1,0,0,0,0.5,0.5,0,0.5,0,1,0,0,0,1,0,0,0,0,0,0,1,0,1,0.5,0.5,0,0,0,1,1,1,0.5,0,1,1,1,1,0,0,1,0,0,0,0] recall 0.45625 [0,0,0,0.5,1,0,1,0,1,1,1,1,0.5,0,0.5,0,1,0,0,0,0.5,0.5,0,1,0.5,0,0,0.5,1,1,1,1,1,0,0.5,1,0.5,0,0,1,0,1,0.5,0,0.5,0.5,1,0.5,1,0,0.5,0.5,0,0,0.5,0,1,0,0.5,0.5,1,1,0,0.5,1,0,0,0,0,0,0,1,0,0.5,0,0.5,1,0,1,0,0,0,1,0,1,0.5,0,0,1,0.5,1,1,0,0,1,1,0,0.5,0,1] relative_absolute_error 0.7012888472212531 relative_absolute_error 0.6689923634531469 relative_absolute_error 0.6946236659520093 relative_absolute_error 0.6926333962205301 relative_absolute_error 0.6802513131660145 relative_absolute_error 0.6995669872974132 relative_absolute_error 0.6647451946540076 relative_absolute_error 0.6928534587159524 relative_absolute_error 0.6948892847404777 relative_absolute_error 0.7035858446254539 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 0.08169330877383292 root_mean_squared_error 0.07869366082968351 root_mean_squared_error 0.07919489931410018 root_mean_squared_error 0.08020575797263828 root_mean_squared_error 0.07915394118643201 root_mean_squared_error 0.0800033409513874 root_mean_squared_error 0.07690002562949678 root_mean_squared_error 0.07919279738052111 root_mean_squared_error 0.0812288397042899 root_mean_squared_error 0.08200501495304983 root_relative_squared_error 0.8210486457134921 root_relative_squared_error 0.7909010495501451 root_relative_squared_error 0.7959386858631647 root_relative_squared_error 0.8060981976402946 root_relative_squared_error 0.7955270411916774 root_relative_squared_error 0.8040638300322019 root_relative_squared_error 0.7728743375204682 root_relative_squared_error 0.7959175606358434 root_relative_squared_error 0.8163805559244021 root_relative_squared_error 0.8241814106871217 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 4021.949687000415 usercpu_time_millis 3718.8226270000087 usercpu_time_millis 3892.6042540001617 usercpu_time_millis 3722.722861999955 usercpu_time_millis 3838.233795999713 usercpu_time_millis 3748.846154000148 usercpu_time_millis 3774.725935999868 usercpu_time_millis 3745.637686000009 usercpu_time_millis 3704.117042999769 usercpu_time_millis 3715.4775540002447 usercpu_time_millis_testing 38.603335000061634 usercpu_time_millis_testing 34.71394300004249 usercpu_time_millis_testing 34.7709229999964 usercpu_time_millis_testing 34.54128399971523 usercpu_time_millis_testing 34.880089000125736 usercpu_time_millis_testing 34.512037000240525 usercpu_time_millis_testing 34.56379499994 usercpu_time_millis_testing 34.72156499992707 usercpu_time_millis_testing 34.535879000031855 usercpu_time_millis_testing 34.52336100008324 usercpu_time_millis_training 3983.3463520003534 usercpu_time_millis_training 3684.108683999966 usercpu_time_millis_training 3857.8333310001653 usercpu_time_millis_training 3688.18157800024 usercpu_time_millis_training 3803.3537069995873 usercpu_time_millis_training 3714.3341169999076 usercpu_time_millis_training 3740.162140999928 usercpu_time_millis_training 3710.916121000082 usercpu_time_millis_training 3669.5811639997373 usercpu_time_millis_training 3680.9541930001615