10115231 1 Jan van Rijn 9954 Supervised Classification 8815 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(1) 8040548 axis 0 8778 copy true 8778 missing_values "NaN" 8778 strategy "most_frequent" 8778 verbose 0 8778 copy true 8779 with_mean true 8779 with_std true 8779 memory null 8780 copy true 8781 fill_value -1 8781 missing_values NaN 8781 strategy "constant" 8781 verbose 0 8781 categorical_features null 8782 categories null 8782 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 8782 handle_unknown "ignore" 8782 n_values null 8782 sparse true 8782 class_weight null 8783 criterion "gini" 8783 max_depth null 8783 max_features 1.0 8783 max_leaf_nodes null 8783 min_impurity_decrease 0.0 8783 min_impurity_split null 8783 min_samples_leaf 13 8783 min_samples_split 9 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 44080 8783 splitter "best" 8783 n_jobs null 8812 remainder "passthrough" 8812 sparse_threshold 0.3 8812 transformer_weights null 8812 memory null 8813 memory null 8815 threshold 0.0 8816 openml-python Sklearn_0.20.0. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 21151000 description https://api.openml.org/data/download/21151000/description.xml -1 21151001 predictions https://api.openml.org/data/download/21151001/predictions.arff area_under_roc_curve 0.8473157354797981 [0.794389,0.92734,0.773457,0.839706,0.866596,0.88954,0.834339,0.92517,0.836115,0.968178,0.803129,0.833984,0.736999,0.788747,0.899108,0.764027,0.966383,0.792732,0.806542,0.817314,0.957939,0.821042,0.761265,0.934659,0.827711,0.776495,0.834458,0.793679,0.899858,0.93383,0.868608,0.899108,0.896031,0.826389,0.893091,0.93097,0.827533,0.759884,0.800722,0.898556,0.764757,0.931877,0.901791,0.890586,0.793186,0.925821,0.900943,0.901042,0.897037,0.802596,0.916943,0.834793,0.892124,0.822345,0.89175,0.814394,0.968158,0.865885,0.924972,0.761738,0.834872,0.900351,0.927162,0.769275,0.869969,0.859908,0.818793,0.885436,0.83797,0.751539,0.808949,0.901199,0.860105,0.798236,0.713088,0.765329,0.900292,0.590515,0.933416,0.859987,0.788056,0.868391,0.692294,0.928149,0.816229,0.85395,0.901851,0.891158,0.831755,0.867069,0.935133,0.898694,0.889796,0.818202,0.82339,0.801452,0.790286,0.858961,0.646405,0.835602] average_cost 0 f_measure 0.40216923509622865 [0.263158,0.391304,0.545455,0.666667,0.588235,0.2,0.580645,0.421053,0.482759,0.9375,0.4,0.516129,0.352941,0.3,0.451613,0.411765,0.727273,0.37037,0.083333,0,0.4,0.3125,0.216216,0.8,0.324324,0,0,0.216216,0.62069,0.666667,0.461538,0.545455,0.5,0.193548,0.418605,0.545455,0.307692,0.216216,0.344828,0.571429,0.428571,0.666667,0.65,0.294118,0,0.416667,0.625,0.6,0.555556,0.424242,0.235294,0.470588,0.424242,0.190476,0.375,0.148148,0.9375,0.466667,0.342857,0.275862,0.444444,0.611111,0.333333,0.5,0.594595,0.333333,0.228571,0.166667,0.266667,0.108108,0.095238,0.6875,0.457143,0.413793,0.24,0.380952,0.606061,0.064516,0.631579,0.26087,0,0.647059,0.235294,0.363636,0.292683,0.37037,0.727273,0.451613,0.4375,0.564103,0.83871,0.628571,0.428571,0.266667,0.230769,0.5625,0.285714,0.137931,0,0.444444] kappa 0.41098484848484845 kb_relative_information_score 860.5617395908237 mean_absolute_error 0.01357093467380442 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 0.4090988481056491 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[1,1,0.996855,0.745253,0.993711,0.746835,1,1,0.484277,1,0.481132,1,0.740506,0.430818,0.493711,1,1,0.474843,0.947785,0.955696,0.984177,0.474684,0.481013,0.996835,0.987342,0.446541,0.993711,1,0.496855,0.732595,0.987342,1,1,0.984277,0.743671,0.998418,0.474684,0.723101,0.737342,0.996855,0.731013,1,0.993671,0.707278,0.481132,0.981013,1,0.981013,0.477987,0.981132,0.977987,0.735759,0.977848,0.993711,0.974684,0.718354,1,0.996835,0.735759,0.443396,0.734177,0.993671,0.987421,0.740506,0.996835,0.996855,0.971698,0.732595,0.716772,0.718354,0.449686,0.996835,0.977848,0.987421,0.471519,1,0.996855,0.446541,0.996855,0.996855,0.724684,0.477987,0.973101,0.981013,0.920886,0.734177,0.990506,0.487421,0.996855,0.996835,0.487421,0.974684,0.996835,0.465409,0.474843,0.743671,0.96519,0.474843,0.458861,0.990506] area_under_roc_curve 0.833669069938699 [0.987421,0.996835,1,0.742089,0.484177,0.987421,0.484177,0.993711,0.996835,1,0.987421,1,0.740506,0.981013,0.987342,0.465409,1,1,0.481013,0.487421,1,0.995253,0.95283,0.75,0.742089,0.471698,0.443396,0.734177,0.996835,0.996855,0.988924,0.996835,0.981132,0.981132,0.992089,0.984177,0.988924,0.468354,0.996835,0.493711,1,0.738924,0.745253,0.97943,0.735759,0.742089,0.996855,1,0.962264,0.993711,0.995253,0.742089,0.731013,0.734177,0.723101,0.95283,1,0.487421,0.996835,0.72943,0.740506,0.75,0.993671,0.738924,0.490566,0.996855,0.723101,0.993711,0.705696,0.996855,0.949686,0.490566,0.988924,0.484177,0.72943,0.474684,0.996855,0.45283,1,0.745253,0.977848,1,0.477987,0.484277,0.993671,0.982595,0.996835,0.740506,0.481132,0.996835,1,0.996835,1,0.723101,0.959119,0.993671,0.465409,0.984177,0.938291,0.487421] area_under_roc_curve 0.8495904983679641 [0.468553,0.734177,0.468553,0.745253,1,0.962264,1,0.977987,1,1,0.996855,0.996855,0.987342,0.726266,0.996835,0.968553,0.996855,0.977987,0.971519,1,0.732595,0.71519,0.465409,1,0.487342,0.974843,0.481132,0.712025,0.971519,1,0.745253,1,0.990566,0.984277,0.737342,0.996835,0.743671,0.719937,0.481013,0.996855,0.481132,0.732595,0.740506,0.96519,0.740506,0.737342,0.996855,0.743671,0.996855,0.487421,0.716772,0.993671,0.992089,0.984177,1,0.977987,1,0.490566,0.988924,0.993671,1,1,0.493671,0.734177,0.987421,0.968553,0.969937,0.968553,0.977848,0.95283,0.968553,1,0.737342,0.71519,0.678797,0.97943,1,0.455975,0.996855,0.72943,0.721519,0.993711,0.981132,0.484277,0.993671,0.982595,0.723101,0.968354,1,0.731013,1,0.996835,0.958861,0.716772,0.996855,0.996835,0.459119,0.984177,0.468354,1] 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 0.4002288600402478 kappa 0.46963418965313125 kappa 0.38138635735984533 kappa 0.4004890747022167 kappa 0.40630797773654914 kappa 0.37465455981050133 kappa 0.4820371101460718 kappa 0.3996366221660479 kappa 0.41905438471860446 kappa 0.3749013417521705 kb_relative_information_score 84.29011501339028 kb_relative_information_score 89.11938824464919 kb_relative_information_score 83.72467041779471 kb_relative_information_score 80.18480930345413 kb_relative_information_score 89.31036392112406 kb_relative_information_score 87.68773910890961 kb_relative_information_score 93.57605214353764 kb_relative_information_score 83.41795608289665 kb_relative_information_score 85.25046599021404 kb_relative_information_score 84.00017936486273 mean_absolute_error 0.013860073462511377 mean_absolute_error 0.012931806656110864 mean_absolute_error 0.0139954002738159 mean_absolute_error 0.013706568533725996 mean_absolute_error 0.013345970106469377 mean_absolute_error 0.013918011503236297 mean_absolute_error 0.012926935875484083 mean_absolute_error 0.0137640236353372 mean_absolute_error 0.013388570175094936 mean_absolute_error 0.013871986516259089 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 0.40625 predictive_accuracy 0.475 predictive_accuracy 0.3875 predictive_accuracy 0.40625 predictive_accuracy 0.4125 predictive_accuracy 0.38125 predictive_accuracy 0.4875 predictive_accuracy 0.40625 predictive_accuracy 0.425 predictive_accuracy 0.38125 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 0.40625 [1,0.5,0.5,1,0,0,1,1,0,1,0,0,0,0,0.5,0,0,0,0,0,0,0,0,1,0,0,0,0,0.5,0,0.5,0.5,0.5,0,0.5,0,1,1,1,0.5,0,1,1,0,0,1,1,1,1,0.5,0,0.5,0,0,1,1,1,1,0,1,1,1,0,0.5,1,0,1,0,0,0,0.5,1,0,1,0,1,0.5,0,1,0,0,1,0,1,0,0,0,1,0.5,0,0.5,1,0.5,0.5,0,0.5,1,0,0,1] recall 0.475 [0,1,0.5,1,0,0,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0,0,1,0,0,1,0,0,0,0,1,1,0.5,1,0.5,0.5,0,0,0,1,0,1,1,1,1,0.5,0,1,0,1,0.5,1,1,0.5,1,0,0,0,1,1,1,0,1,0,0.5,0.5,1,0,0,0,0,0,0,1,0.5,0.5,0,0.5,0.5,0.5,1,0,0,0.5,0,1,0.5,0.5,1,0.5,1,1,0.5,1,0,1,0.5,0,0,0,0,1] recall 0.3875 [0,0,0.5,0,1,0.5,0,0.5,0.5,1,0.5,0.5,1,0.5,0.5,1,1,0,0,0,0,0,0,1,0,0,0,0,0.5,1,1,0,0,0.5,1,1,1,0,0,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,0.5,1,0,0,0,0,1,1,0,0,0,1,0.5,0,0,0,0.5,0.5,1,0,0,1,1,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0.5,0,1,1,1,0,0,0.5,1,0,0.5,0,0] recall 0.40625 [0,1,1,1,1,0.5,1,0.5,0,1,0.5,0,0,0,1,0.5,0.5,0.5,0,0,0,1,1,0,0,0,0,1,0.5,1,1,0,1,0,0,1,1,0,0,1,0.5,1,1,1,0,0,0,1,1,0,0,0,0,0,1,0.5,1,0,1,0,1,0,0.5,0,1,1,0,0,0,0,0,0.5,1,0.5,0,0,0,0,1,0.5,0,0.5,0,0.5,0,0,1,0.5,0,1,1,1,1,0,0,1,0,0,0,0] recall 0.4125 [0.5,0,0.5,0.5,1,0,0,0,0,1,0.5,0,0,0,0,0,1,0.5,0,0,1,1,0.5,1,0.5,0,0,0,1,0.5,1,0,1,0,1,0.5,0.5,0,0.5,0.5,1,1,1,0,0,1,1,0.5,0,0,0,0,0.5,0,0.5,0,1,0,1,0,0,1,1,1,0.5,1,0,0,0,0,0,0.5,1,0,0.5,0,0.5,0,1,0,0,1,0,0.5,0,0,1,1,1,0.5,1,0,0,0,0,0,0.5,0,0,0.5] recall 0.38125 [0,1,0.5,1,1,0,1,0,0,0.5,0.5,1,0,0,0,0.5,1,0.5,0,0,0.5,0.5,0.5,1,0.5,0,0,0,1,0.5,0,1,0.5,0.5,1,0.5,0,0,0,0,0,1,0,0,0,1,0.5,0,1,0.5,0,0,0.5,1,0,0,1,0.5,0.5,1,0.5,0,0,1,1,0,0,0,0,0,0,0,1,1,0.5,0,0.5,0,0.5,0,0,0.5,1,0.5,0,0,1,0,0,1,1,0,0,1,0.5,1,0,0,0,0.5] recall 0.4875 [0.5,0,0,0.5,1,0,0.5,0.5,1,1,1,1,0,1,1,0,1,0,0.5,0,1,0,0,1,0.5,0,0,0.5,0,1,0.5,0,1,0,1,1,0,1,0,1,0,0,1,1,0,1,0.5,0.5,1,1,0,1,0.5,0,0.5,0,0.5,1,0,0,0,1,1,0,0.5,1,1,0.5,1,0,0,1,0,1,0.5,0,1,0,1,0,0,1,0.5,0.5,0.5,0.5,1,0,0,0.5,1,1,0,0,0,0,1,0,0,1] recall 0.40625 [1,1,1,0.5,1,0.5,1,1,0,1,0,1,0.5,0,0,1,1,0,0,0,0.5,0,0,1,1,0,0,0.5,0,0.5,0,1,1,0,0.5,0.5,0,0,0.5,1,0,1,1,0,0,0,1,0,0,0,0,0.5,0.5,0,0,0,1,0,0,0,0,1,0,0.5,1,0,0,0,0,0.5,0,1,0.5,0,0,1,1,0,0,1,0,0,0.5,0,0,0.5,1,0,1,1,0,0.5,1,0,0,0.5,0,0,0,0.5] recall 0.425 [0,1,1,0.5,0,0,0,1,1,1,0,1,0.5,0,0.5,0,1,1,0,0,1,0,0,0.5,0.5,0,0,0.5,1,1,1,1,0,0,0.5,0,0.5,0,1,0,1,0.5,0.5,0,0,0.5,1,1,0,1,0.5,0.5,0.5,0.5,0,0,1,0,0,0,0,0.5,0,0.5,0,1,0,0,0,1,0,0,0.5,0,0,0,1,0,1,0.5,0,1,0,0,1,0.5,1,0.5,0,1,1,1,1,0,0,1,0,0,0,0] recall 0.38125 [0,0,0,0.5,1,0,0.5,0,1,1,1,1,1,0,0,0,1,0,0,0,0.5,0.5,0,1,0,0,0,0,0,1,0.5,1,1,0,0.5,1,0.5,0,0,0,0,0.5,0.5,0,0,0,1,0.5,1,0,0,0.5,0.5,0,1,0,1,0,0.5,0.5,1,1,0,0.5,1,0,0,0,0.5,0,0,1,0.5,0,0,0,1,0,1,0,0,0,0,0,1,0.5,0,0,1,0,1,1,0,0,0,1,0,0.5,0,1] relative_absolute_error 0.7000037102278462 relative_absolute_error 0.6531215482884264 relative_absolute_error 0.7068383976674686 relative_absolute_error 0.6922509360467664 relative_absolute_error 0.6740388942661291 relative_absolute_error 0.7029298739008221 relative_absolute_error 0.6528755492668717 relative_absolute_error 0.695152708855413 relative_absolute_error 0.6761904128835815 relative_absolute_error 0.7006053796090437 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 0.09147312709326831 root_mean_squared_error 0.08718754360581198 root_mean_squared_error 0.09090786528453441 root_mean_squared_error 0.09113065022974898 root_mean_squared_error 0.0878469436634081 root_mean_squared_error 0.09067067345987893 root_mean_squared_error 0.08588642511035548 root_mean_squared_error 0.09017910322843249 root_mean_squared_error 0.0904754490016438 root_mean_squared_error 0.09188916670446359 root_relative_squared_error 0.9193395180874657 root_relative_squared_error 0.8762677834340249 root_relative_squared_error 0.9136584231544717 root_relative_squared_error 0.9158974961005826 root_relative_squared_error 0.8828950033667071 root_relative_squared_error 0.9112745556219809 root_relative_squared_error 0.8631910505333554 root_relative_squared_error 0.906334088907387 root_relative_squared_error 0.9093124759920828 root_relative_squared_error 0.9235208735064355 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 135.14236599985452 usercpu_time_millis 120.83008800073003 usercpu_time_millis 123.80645600023854 usercpu_time_millis 94.17053899960592 usercpu_time_millis 93.7218330000178 usercpu_time_millis 91.52808699946036 usercpu_time_millis 92.41838900197763 usercpu_time_millis 93.02429799936363 usercpu_time_millis 91.42164699915156 usercpu_time_millis 91.95027799796662 usercpu_time_millis_testing 1.715956001135055 usercpu_time_millis_testing 1.6929869998421054 usercpu_time_millis_testing 1.6786520009191008 usercpu_time_millis_testing 1.306274998569279 usercpu_time_millis_testing 1.3397639995673671 usercpu_time_millis_testing 1.2454019997676369 usercpu_time_millis_testing 1.3136020006641047 usercpu_time_millis_testing 1.3540630006900756 usercpu_time_millis_testing 1.2410899998940295 usercpu_time_millis_testing 1.288603998546023 usercpu_time_millis_training 133.42640999871946 usercpu_time_millis_training 119.13710100088792 usercpu_time_millis_training 122.12780399931944 usercpu_time_millis_training 92.86426400103664 usercpu_time_millis_training 92.38206900045043 usercpu_time_millis_training 90.28268499969272 usercpu_time_millis_training 91.10478700131353 usercpu_time_millis_training 91.67023499867355 usercpu_time_millis_training 90.18055699925753 usercpu_time_millis_training 90.6616739994206