10093027 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) 8018138 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 "entropy" 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 11 8783 min_samples_split 19 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 28112 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 21106591 description https://api.openml.org/data/download/21106591/description.xml -1 21106592 predictions https://api.openml.org/data/download/21106592/predictions.arff area_under_roc_curve 0.8399479166666665 [0.829072,0.869792,0.904928,0.928267,0.901377,0.861328,0.801018,0.897293,0.867089,0.837851,0.931897,0.898497,0.833491,0.762251,0.837358,0.822838,0.905086,0.791075,0.794448,0.727884,0.898122,0.833866,0.833787,0.999901,0.801215,0.754814,0.82631,0.835148,0.835208,0.872317,0.987966,0.935705,0.834793,0.818478,0.900331,0.870561,0.794725,0.760614,0.965633,0.96514,0.735322,0.861683,0.871015,0.862926,0.867878,0.764481,0.935507,0.806483,0.727865,0.834635,0.95492,0.824732,0.929194,0.74785,0.76959,0.687441,0.998777,0.929885,0.82852,0.790443,0.774996,0.766927,0.926353,0.640428,0.835977,0.862216,0.788569,0.933495,0.662701,0.724925,0.749388,0.933318,0.80236,0.864623,0.649089,0.931305,0.900844,0.719993,0.901653,0.93026,0.928859,0.767598,0.766907,0.796914,0.857067,0.836194,0.857382,0.854344,0.735006,0.834537,0.96583,0.96437,0.824298,0.786794,0.86482,0.865136,0.861012,0.799025,0.679214,0.793442] average_cost 0 f_measure 0.4064506658766277 [0.333333,0.628571,0.785714,0.296296,0.516129,0.275862,0.3125,0.571429,0.258065,0.428571,0.514286,0.540541,0.457143,0.066667,0.611111,0.214286,0.702703,0.186047,0.4,0.230769,0.5,0.516129,0.35,0.941176,0.424242,0.2,0.258065,0.5,0.592593,0.666667,0.375,0.8,0.470588,0.210526,0.571429,0.727273,0.296296,0.216216,0.714286,0.648649,0.285714,0.333333,0.666667,0.484848,0.645161,0.142857,0.705882,0.484848,0.206897,0.47619,0.465116,0.25,0.424242,0.16,0.333333,0,0.888889,0.5,0.1875,0.26087,0.4,0.342857,0.461538,0.258065,0.466667,0.324324,0.068966,0.5625,0.216216,0.111111,0.064516,0.685714,0.378378,0.451613,0.083333,0.571429,0.592593,0.076923,0.740741,0.580645,0.645161,0.32,0.4,0.133333,0.341463,0.5625,0.24,0.086957,0.2,0.388889,0.702703,0.611111,0.444444,0.173913,0.375,0.428571,0.424242,0.16,0,0.357143] kappa 0.4116161616161616 kb_relative_information_score 868.8852424268293 mean_absolute_error 0.013352925465487305 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 0.41264246344483246 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[0.996835,0.993711,1,0.477848,1,0.716772,0.993671,0.996835,0.493711,0.996835,0.993711,0.487421,0.732595,0.974843,0.481132,0.46519,1,0.465409,0.971519,0.481013,0.977848,0.737342,0.732595,1,0.990506,0.440252,0.45283,0.738924,1,0.742089,0.981013,0.996855,1,1,0.740506,1,0.737342,0.984177,0.993671,0.996855,0.735759,0.737342,0.993671,0.490506,1,0.735759,1,1,0.962264,0.496855,0.974843,0.723101,0.737342,1,0.746835,0.723101,1,0.995253,0.481013,0.996855,0.493671,0.737342,0.984277,0.738924,0.746835,0.984277,0.993711,0.743671,0.481013,0.732595,0.465409,1,0.996835,0.468553,0.721519,1,0.974843,0.940252,1,0.962264,0.968354,1,0.732595,0.990506,0.468354,0.740506,0.990506,0.481132,1,0.737342,1,0.996835,0.734177,0.965409,0.474843,0.987342,0.984177,0.990566,0.697785,0.727848] area_under_roc_curve 0.8679455507125233 [0.471698,0.995253,1,1,0.996835,0.990566,0.731013,0.955975,0.974684,1,0.490566,0.996855,0.996835,0.745253,0.996835,0.968553,0.993711,0.993711,1,0.949686,0.993671,1,0.987421,1,0.748418,0.981132,0.465409,0.990506,0.742089,0.996855,0.990506,1,0.949686,0.937107,0.996835,1,0.740506,0.721519,0.993671,0.996855,0.487421,0.727848,0.746835,0.735759,0.487342,0.490506,0.990566,0.97943,0.465409,0.996855,0.987342,0.982595,0.993671,0.705696,0.740506,0.471698,1,0.981132,0.742089,0.710443,0.745253,0.993671,0.988924,0.732595,0.996855,0.987421,0.97943,0.5,0.732595,0.987421,0.990566,0.984277,0.742089,0.993671,0.455696,0.732595,0.996855,0.996855,1,1,1,0.990566,0.477987,0.987421,0.976266,1,0.958861,0.977848,0.474843,0.987342,1,0.746835,0.996835,0.707278,0.993711,0.726266,0.955975,0.727848,0.731013,0.996855] area_under_roc_curve 0.8696803349653688 [0.962264,0.484177,0.496855,0.96519,1,0.987421,0.737342,0.484277,0.735759,0.993711,1,0.993711,0.993671,0.987342,0.742089,1,1,1,0.993671,0.996855,1,0.996835,1,1,1,0.459119,0.996855,0.743671,0.484177,0.996855,0.985759,0.75,1,0.946541,0.992089,0.732595,0.726266,0.996835,1,1,0.959119,0.981013,0.998418,0.743671,1,0.738924,1,0.471519,0.993711,0.490566,0.995253,0.737342,0.996835,0.955696,0.738924,0.45283,1,0.987421,0.471519,1,0.993671,0.731013,0.993671,0.724684,0.990566,0.5,0.94462,0.993711,0.985759,0.468553,0.471698,0.490566,0.737342,0.996835,0.734177,0.996835,1,0.474843,0.477987,0.996835,1,0.493711,0.996855,0.484277,0.987342,1,0.969937,0.969937,0.455975,0.990506,1,0.996835,0.996835,0.737342,1,1,1,0.996835,0.976266,0.984277] 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 0.44418127269856306 kappa 0.43161634103019536 kappa 0.4063548450759818 kappa 0.40630797773654914 kappa 0.4125310908444866 kappa 0.4002998500749625 kappa 0.34951647917900136 kappa 0.35595895816890294 kappa 0.40015785319652725 kappa 0.5073230429118472 kb_relative_information_score 89.33733168165067 kb_relative_information_score 89.88028966400262 kb_relative_information_score 83.40694591748748 kb_relative_information_score 87.17423133328909 kb_relative_information_score 80.314682299163 kb_relative_information_score 86.09231858690346 kb_relative_information_score 83.63042271075261 kb_relative_information_score 80.48646041002516 kb_relative_information_score 91.47159388702352 kb_relative_information_score 97.09096593653983 mean_absolute_error 0.012883218010167513 mean_absolute_error 0.013040672032753105 mean_absolute_error 0.013335414966118337 mean_absolute_error 0.013493395985249703 mean_absolute_error 0.013698917174908861 mean_absolute_error 0.01345262408246638 mean_absolute_error 0.01406975499775423 mean_absolute_error 0.01378558708716894 mean_absolute_error 0.01340924810215154 mean_absolute_error 0.01236042221613526 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 0.45 predictive_accuracy 0.4375 predictive_accuracy 0.4125 predictive_accuracy 0.4125 predictive_accuracy 0.41875 predictive_accuracy 0.40625 predictive_accuracy 0.35625 predictive_accuracy 0.3625 predictive_accuracy 0.40625 predictive_accuracy 0.5125 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 0.45 [0,0.5,1,0,0.5,1,0.5,1,0,0,1,0.5,0,0,1,1,1,0,0,0,1,0,1,1,0,0.5,0.5,0.5,0.5,0,1,1,0.5,0,1,0,0,0,1,1,1,0,0.5,1,1,0.5,1,1,0,0.5,0.5,0.5,0,0,1,0,1,1,0,0,0,1,0,0,1,0.5,0,1,0,0,0,1,0.5,0.5,0,0.5,0.5,0,0.5,0.5,1,0,0,1,0.5,0.5,0,0,0,0,1,1,1,0,0.5,0.5,0,0,0,1] recall 0.4375 [1,1,0.5,1,0,1,0.5,1,0.5,1,0.5,0.5,0.5,0.5,1,0,1,0,0.5,1,1,0,0,1,1,0,0,0,0.5,1,0.5,1,0.5,0.5,0,1,0,0,0,1,0,1,1,0.5,0.5,0,0,0,0,1,0,0.5,1,0.5,1,0,1,1,0,0,1,1,1,0,1,1,0.5,0,0,0,0,1,0.5,0.5,0,1,0,0.5,0.5,0.5,0.5,0,0,0,0.5,0,0,0,0,0,0.5,1,0,0,0.5,0.5,1,0,0,0] recall 0.4125 [0,0.5,0,1,0.5,0,0,1,0.5,0,0.5,0.5,1,0,0,0,1,0,0,0,1,0,0,1,0,1,0,1,1,1,0,1,1,0,0,1,0,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,1,1,0,0,1,0,1,0.5,0,0,0,0,0.5,1,0.5,0.5,0,1,0,0,0,1,0,0.5,0,0,1,0,0.5,1,0,0,1,0,1,0,0,0,0,1,0.5,1,0,0.5,0.5,1,0,0.5,0,0.5] recall 0.4125 [0.5,1,1,0,0.5,0,1,0.5,0,0,1,0.5,0,0,1,0,0.5,0.5,0,0,0,1,0.5,1,0,0,0.5,0,0,0.5,1,1,0.5,0.5,1,0,1,0,1,1,0,0,1,0,0.5,1,0.5,1,0,1,1,1,0,0,1,0,1,1,0,0,1,0,1,0,0.5,0.5,0,1,0,0.5,0,0,1,0.5,0,0.5,0,0,1,0.5,0,0.5,1,0,0,0,1,0,0,0,1,0,0,0,0.5,0,0.5,0,0,0] recall 0.41875 [0.5,1,0.5,1,0,0.5,0,0,0,0.5,0,0.5,0,0,1,0.5,0.5,0.5,1,1,0,0,1,1,0.5,0,0,1,1,0,1,1,0,0,1,1,0.5,0,0.5,1,1,0.5,0,1,1,0,1,0,0.5,0.5,0,0,0,0,0.5,0,1,0,0.5,0,0.5,0.5,0,0,0.5,0,0,0,0,0,0,1,1,0,0,1,0.5,0,0.5,0,1,1,0,0.5,0,1,0,1,1,0.5,1,1,0,0,0.5,0,0.5,1,0,0] recall 0.40625 [0,1,1,0,1,0,0,0.5,1,0.5,0.5,1,1,0,1,0,1,0.5,0,0,1,0.5,0,1,0.5,0,0.5,1,1,1,0,1,0,0,0,1,0,0.5,1,0,0.5,0.5,1,1,1,0,1,0.5,0,0.5,1,0,0,0,0,0,1,1,1,0,0.5,0,0,1,0,0.5,0,1,0.5,0.5,0,1,0,1,0,0,0.5,0,0.5,0,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0.5,0,0,0.5] recall 0.35625 [0.5,0,1,0,1,0,0,1,0,0,1,1,0.5,0,0,0,0,0,0,0,0.5,0.5,0.5,1,0,0,0,0.5,0,1,0.5,0,1,1,1,0.5,0,0.5,0.5,0,0,0,0.5,0,1,0,0.5,0.5,0,1,1,0,0.5,0,0,0,1,0.5,0,0,0,0,1,0,0,0,0,0.5,0.5,0,0,1,0,0,0,1,1,0,1,1,0.5,0,0.5,0,1,1,0,0,0,0.5,1,1,0.5,0,0,0.5,0.5,0,0,0.5] recall 0.3625 [0.5,1,1,0,1,0,0.5,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0.5,0,1,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0.5,0,0.5,1,0,0.5,1,0,1,0,1,1,0,0,0,0,0.5,1,0,0,1,0.5,0,1,0,0.5,0,0.5,0.5,0,0,0,0,0,0,1,1,0,0,1,0,0,1,0,0,0,0,0,0,0.5,1,0,0,0.5,0,1,0,0,0,1,0.5,0,0,0] recall 0.40625 [0,1,1,0,0,1,0.5,0,0,1,0,1,1,0,1,0,1,0,1,0,0.5,1,1,1,0.5,0,0,0.5,0.5,1,0,1,0,0,1,1,0.5,0,0,0,0,0.5,0,0.5,0,0,1,0.5,0,1,0.5,0.5,1,0,0,0,1,0,0,0,0,1,0.5,0.5,0,0,0,0,0.5,0,1,0,0.5,0,0,0.5,1,0,1,0.5,1,1,0,0,0.5,1,0,0,0,0,1,0,0.5,0,1,0.5,0,0,0,1] recall 0.5125 [0,0,0,0,1,0,0,0,0.5,0,1,1,1,0,0.5,1,1,1,1,0,1,1,1,1,1,0,1,0.5,0,1,0,0.5,1,0,0.5,0.5,0,1,1,1,0,0.5,0.5,0.5,1,0,1,0,1,0,1,0,1,0,0,0,1,1,0,1,1,0,1,0,1,0,0,1,0.5,0,0,0,0,1,0.5,1,1,0,0,1,1,0,1,0,0.5,1,0,0,0,0.5,1,1,1,0.5,0,1,1,0,0,0] relative_absolute_error 0.6506675762710854 relative_absolute_error 0.6586197996339941 relative_absolute_error 0.6735058063696119 relative_absolute_error 0.6814846457196809 relative_absolute_error 0.6918645037832748 relative_absolute_error 0.6794254587104221 relative_absolute_error 0.7105936867552629 relative_absolute_error 0.6962417720792382 relative_absolute_error 0.677234752633915 relative_absolute_error 0.6242637482896586 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 0.08746847186111488 root_mean_squared_error 0.08698234656337585 root_mean_squared_error 0.09137582735737691 root_mean_squared_error 0.08918535712034124 root_mean_squared_error 0.0914318580366923 root_mean_squared_error 0.08990751006324724 root_mean_squared_error 0.09217295604963562 root_mean_squared_error 0.09110798422146887 root_mean_squared_error 0.08834876857842745 root_mean_squared_error 0.0834843608101919 root_relative_squared_error 0.8790912186335672 root_relative_squared_error 0.8742054755617484 root_relative_squared_error 0.9183616189476098 root_relative_squared_error 0.8963465647334032 root_relative_squared_error 0.9189247484628761 root_relative_squared_error 0.9036044748936156 root_relative_squared_error 0.926373063741091 root_relative_squared_error 0.9156696941461578 root_relative_squared_error 0.8879385335290441 root_relative_squared_error 0.8390493959698699 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 222.27354499955254 usercpu_time_millis 204.006751999259 usercpu_time_millis 181.71193699981814 usercpu_time_millis 146.11291499932122 usercpu_time_millis 146.61534999959258 usercpu_time_millis 145.03117999993265 usercpu_time_millis 146.48745500016958 usercpu_time_millis 147.07077400089474 usercpu_time_millis 147.51718099887512 usercpu_time_millis 151.6315979997671 usercpu_time_millis_testing 1.731983999889053 usercpu_time_millis_testing 1.7128639992733952 usercpu_time_millis_testing 1.241897999534558 usercpu_time_millis_testing 1.2415089995556627 usercpu_time_millis_testing 1.2369659998512361 usercpu_time_millis_testing 1.2591650001922972 usercpu_time_millis_testing 1.2384450001263758 usercpu_time_millis_testing 1.2555700004668324 usercpu_time_millis_testing 1.4077159994485555 usercpu_time_millis_testing 1.2398150001899921 usercpu_time_millis_training 220.5415609996635 usercpu_time_millis_training 202.2938879999856 usercpu_time_millis_training 180.47003900028358 usercpu_time_millis_training 144.87140599976556 usercpu_time_millis_training 145.37838399974135 usercpu_time_millis_training 143.77201499974035 usercpu_time_millis_training 145.2490100000432 usercpu_time_millis_training 145.8152040004279 usercpu_time_millis_training 146.10946499942656 usercpu_time_millis_training 150.39178299957712