10095193 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) 8020321 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 7 8783 min_samples_split 10 8783 min_weight_fraction_leaf 0.0 8783 presort false 8783 random_state 43500 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 21110923 description https://api.openml.org/data/download/21110923/description.xml -1 21110924 predictions https://api.openml.org/data/download/21110924/predictions.arff area_under_roc_curve 0.808621764520202 [0.740057,0.870522,0.843355,0.903192,0.903942,0.802083,0.774167,0.870443,0.774858,0.841521,0.869003,0.869456,0.838088,0.738518,0.871863,0.737216,0.905106,0.735697,0.761857,0.703224,0.807252,0.869673,0.804885,0.999605,0.806226,0.697029,0.77109,0.806246,0.838798,0.873047,0.871626,0.935882,0.807765,0.671954,0.837693,0.871942,0.768288,0.738419,0.997021,0.934245,0.772688,0.835819,0.841343,0.835957,0.871725,0.771721,0.93458,0.776515,0.705966,0.80883,0.896918,0.704111,0.836608,0.694129,0.806029,0.6337,0.999369,0.900765,0.799321,0.798769,0.714765,0.770103,0.839094,0.647885,0.838522,0.773497,0.669863,0.935172,0.573587,0.671638,0.73329,0.87137,0.773714,0.868608,0.56686,0.933554,0.840475,0.665384,0.904179,0.870837,0.804569,0.677991,0.771563,0.771307,0.829447,0.840791,0.831459,0.765625,0.739721,0.774996,0.966422,0.965278,0.829052,0.795553,0.839291,0.837674,0.834714,0.739583,0.694149,0.802872] average_cost 0 f_measure 0.44636935357678453 [0.363636,0.628571,0.785714,0.692308,0.684211,0.272727,0.457143,0.666667,0.421053,0.666667,0.545455,0.62069,0.5,0.222222,0.705882,0.133333,0.764706,0.137931,0.25641,0.387097,0.457143,0.606061,0.378378,0.914286,0.428571,0.210526,0.230769,0.551724,0.642857,0.666667,0.545455,0.742857,0.6,0.210526,0.47619,0.666667,0.384615,0.25,0.8,0.727273,0.4375,0.434783,0.666667,0.424242,0.6875,0.375,0.642857,0.5,0.181818,0.645161,0.512821,0.25,0.37037,0.129032,0.466667,0.052632,0.882353,0.514286,0.117647,0.285714,0.434783,0.387097,0.571429,0.32,0.5625,0.363636,0.125,0.666667,0.142857,0.230769,0.114286,0.625,0.451613,0.6,0.086957,0.647059,0.516129,0.129032,0.72,0.529412,0.484848,0.148148,0.411765,0.277778,0.304348,0.571429,0.24,0.181818,0.230769,0.45,0.705882,0.588235,0.4,0.1875,0.551724,0.484848,0.424242,0.285714,0.086957,0.416667] kappa 0.4438131313131313 kb_relative_information_score 853.7929969970668 mean_absolute_error 0.012295829136141518 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 0.4607360140196323 [0.352941,0.578947,0.916667,0.9,0.590909,0.5,0.421053,0.647059,0.363636,0.647059,0.529412,0.692308,0.5,0.2,0.666667,0.142857,0.722222,0.153846,0.217391,0.4,0.421053,0.588235,0.333333,0.842105,0.5,0.181818,0.3,0.615385,0.75,0.6,0.529412,0.684211,0.642857,0.181818,0.384615,0.818182,0.5,0.25,0.736842,0.705882,0.4375,0.333333,0.714286,0.411765,0.6875,0.375,0.75,0.5,0.176471,0.666667,0.434783,0.25,0.454545,0.133333,0.5,0.045455,0.833333,0.473684,0.111111,0.263158,0.714286,0.4,0.526316,0.444444,0.5625,0.352941,0.125,0.647059,0.166667,0.3,0.105263,0.625,0.466667,0.642857,0.142857,0.611111,0.533333,0.133333,1,0.5,0.470588,0.181818,0.388889,0.25,0.233333,0.666667,0.333333,0.176471,0.3,0.375,0.666667,0.555556,0.428571,0.1875,0.615385,0.470588,0.411765,0.333333,0.142857,0.625] predictive_accuracy 0.449375 prior_entropy 6.6438561897747395 recall 0.449375 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[0.481132,0.995253,1,1,1,0.996855,0.740506,0.487421,0.735759,1,0.496855,0.996855,0.996835,0.746835,0.996835,0.487421,0.993711,0.981132,1,1,0.996835,1,0.993711,1,0.75,0.45283,0.471698,0.743671,0.742089,1,0.996835,1,0.481132,0.987421,0.988924,1,0.740506,0.735759,1,0.5,0.490566,0.743671,0.75,0.727848,0.493671,0.748418,0.996855,0.738924,0.490566,1,0.743671,0.740506,0.745253,0.723101,0.742089,0.484277,1,0.990566,0.487342,0.734177,0.746835,0.996835,0.995253,0.742089,1,1,0.97943,0.5,0.732595,0.993711,0.984277,0.5,0.745253,1,0.474684,0.740506,0.996855,0.484277,1,1,1,0.987421,0.487421,0.993711,0.987342,1,0.952532,0.732595,0.484277,0.745253,1,0.746835,1,0.72943,1,0.734177,0.477987,0.740506,0.732595,1] area_under_roc_curve 0.8270109366292487 [0.474843,0.487342,0.5,0.996835,1,0.987421,0.740506,0.487421,0.738924,1,0.996855,1,0.996835,0.738924,0.996835,1,1,0.993711,0.984177,1,1,0.995253,0.496855,1,1,0.468553,1,0.746835,0.493671,0.987421,0.496835,0.75,1,0.977987,0.745253,0.742089,0.726266,0.740506,0.996835,1,0.971698,0.988924,0.748418,0.743671,1,0.740506,0.993711,0.490506,0.996855,0.493711,0.995253,0.743671,0.996835,0.708861,0.745253,0.468553,1,0.993711,0.493671,1,1,0.72943,0.487342,0.745253,0.993711,0.5,0.481013,0.996855,0.471519,0.481132,0.477987,0.987421,0.742089,0.996835,0.742089,0.993671,1,0.487421,0.496855,0.996835,0.746835,0.490566,1,0.493711,0.988924,1,0.742089,0.985759,0.471698,0.998418,1,0.996835,0.996835,0.990506,1,1,1,0.742089,0.995253,0.996855] 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 0.4503889130177281 kappa 0.44451019844557543 kappa 0.425232906995105 kappa 0.41923774954627946 kappa 0.41893972289109066 kappa 0.41273975846554584 kappa 0.4318854302284294 kappa 0.4000631512472371 kappa 0.5009475679090335 kappa 0.5325885278907267 kb_relative_information_score 87.56954001097156 kb_relative_information_score 85.69149844067975 kb_relative_information_score 83.98401454437571 kb_relative_information_score 81.74281190053672 kb_relative_information_score 78.41749602351905 kb_relative_information_score 84.17641760422903 kb_relative_information_score 88.3723912059569 kb_relative_information_score 80.86522973372652 kb_relative_information_score 89.6293159027603 kb_relative_information_score 93.34428163032057 mean_absolute_error 0.011926018426018427 mean_absolute_error 0.01197917776667777 mean_absolute_error 0.012310061813186815 mean_absolute_error 0.012814200729825725 mean_absolute_error 0.01261101884226885 mean_absolute_error 0.012830724136974139 mean_absolute_error 0.01251280212842713 mean_absolute_error 0.01295080266955267 mean_absolute_error 0.011896791749916752 mean_absolute_error 0.011126693098568102 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 0.45625 predictive_accuracy 0.45 predictive_accuracy 0.43125 predictive_accuracy 0.425 predictive_accuracy 0.425 predictive_accuracy 0.41875 predictive_accuracy 0.4375 predictive_accuracy 0.40625 predictive_accuracy 0.50625 predictive_accuracy 0.5375 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 0.45625 [1,0.5,1,0,1,1,0.5,1,0.5,1,1,0.5,0,0,1,0,1,0,0,0,1,0,0,1,0,0,0.5,0,0.5,0,1,1,0.5,0,1,0,0,0,1,1,1,0,0.5,1,1,0.5,1,1,0,0.5,0.5,0.5,0,0,1,0,1,1,0,0.5,0,1,0.5,0,1,0.5,0,1,0,0,0,1,0.5,0.5,0,1,0.5,0.5,0.5,0.5,1,0,1,1,0.5,0.5,0,0,0,0,0.5,0,1,0,0,0,0,0,0,1] recall 0.45 [1,1,0.5,1,1,1,0,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,0,0.5,1,1,0,0,1,1,0,0,0,0.5,1,0.5,1,0.5,0.5,0.5,1,0,1,1,1,0,1,1,0.5,0.5,0,0,0,0,1,0,0,1,0.5,1,0,1,0,0,0,1,1,0.5,0,1,0,0.5,0,0,0,0,1,0.5,0.5,0,1,0,0.5,0.5,0.5,0.5,0,0,0,0.5,0,0.5,0,0,0,0.5,1,0.5,0,0.5,0.5,1,0,0,0] recall 0.43125 [0,0.5,0,1,0.5,0,0,1,1,0.5,0.5,0.5,1,0.5,0,0,1,0,0,0,1,0,0,1,0,1,0,1,1,1,1,1,1,0.5,0,0,1,0,1,1,0,1,1,1,0,0,0.5,1,0.5,0.5,1,1,0,0,1,0.5,1,0.5,0,0,0,0,1,1,0.5,0,0,1,0,0,0,1,0,0.5,0,0,1,0,0,1,0,0,0.5,0.5,0,0,1,0.5,0.5,1,0.5,1,0,0,0,0,0,0,0,0.5] recall 0.425 [0.5,1,1,1,0.5,0,1,0.5,0,0.5,0,0.5,0,0,1,0,0.5,0,0,0,0,1,0.5,1,0,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0,1,0,0,0,1,1,0.5,1,1,0,1,1,0.5,1,0,1,1,0,0,0,1,0,1,1,0,0,0,0,0.5,0,0.5,1,0,1,0,0.5,0,0,1,0.5,0,0.5,0,0,1,0.5,0,0,1,0,1,0,0,0,0,1,1,0,0,0,1,0,0,1,0,0] recall 0.425 [0.5,1,0.5,1,0,0,0,0.5,0,0.5,1,0.5,1,0,1,0,0.5,0,1,1,0,0.5,1,1,0.5,0,0,1,1,0.5,0,1,0,0,1,1,0.5,0,0.5,1,1,0.5,0,1,1,0,0.5,0,0.5,0.5,0,0,0,0,0,0,1,0,1,0,0.5,0.5,1,0,0.5,0,0,0.5,0,0,0,0.5,1,0,0,1,0.5,0,0.5,0,0,0.5,0,0.5,0,1,0,1,1,0.5,1,1,0,1,0.5,1,0.5,0,0,0] recall 0.41875 [0,1,1,0,1,0,1,0.5,1,0.5,0.5,1,0,1,1,0,1,0.5,0,0,0.5,0.5,0.5,1,0,0.5,0,1,1,1,1,1,0.5,0,0,0,0,0.5,1,0,0.5,0.5,1,1,1,0,1,0.5,0,0.5,1,0,0,0,0,0,1,1,0,1,0.5,0,0,0,0.5,0.5,0,0.5,0.5,0.5,0,1,0,1,0,0,0.5,0,0.5,0,1,0,0,0,0,1,0,0,0,1,1,0,0,1,1,0,0.5,0,0,0.5] recall 0.4375 [0.5,0,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0,0,0,0,0,0,0.5,0.5,1,0.5,1,0,0,0,0.5,0,1,0.5,0,1,1,1,0.5,1,0.5,1,0,0,1,0.5,0,1,0.5,0,0.5,0,1,1,0,0.5,0,0.5,0,0.5,0.5,0,0,0,0,1,0,0,1,0,1,0,0,1,1,0,0,0,1,1,0,1,1,0.5,0,0.5,0,0.5,0.5,0,0,0,0,1,1,0.5,0,0,0.5,1,0,0.5,0.5] recall 0.40625 [0.5,1,1,0,1,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0.5,0.5,1,0.5,0,0,0.5,1,0.5,0,1,1,1,0.5,1,0,0,0.5,1,1,0.5,1,0,1,0.5,1,1,0,0,0,0,0,1,0.5,0,1,0.5,0,1,0,0.5,1,0.5,0.5,0,0,0.5,0,0,0,0.5,1,0,0,1,0,0,1,0,0,0,0.5,1,0,0.5,0.5,0,0,0.5,0,1,0,0,0,1,0.5,0,0,0] recall 0.50625 [0,1,1,1,1,1,0.5,0,0.5,1,0,0,1,0.5,1,0,1,0,1,1,0.5,1,1,1,0.5,0,0,0.5,0.5,1,1,1,0,0,0.5,1,0.5,0,1,0,0,0.5,0,0,0,0.5,1,0.5,0,1,0.5,0.5,0.5,0,0,0,1,0,0,0,0,1,1,0.5,1,1,0.5,0,0.5,1,1,0,0.5,1,0,0.5,1,0,1,0.5,1,1,0,0,0.5,1,0,0,0,0.5,1,0,0,0,1,0.5,0,0.5,0,1] recall 0.5375 [0,0,0,0.5,1,0,0,0,0.5,1,1,1,1,0,1,1,1,1,0.5,1,1,1,0,1,1,0,1,0.5,0,1,0,0.5,1,0,0.5,0.5,0,0.5,1,1,0,0.5,0.5,0.5,1,0.5,0,0,1,0,1,0.5,1,0,0.5,0,1,1,0,1,1,0,0,0.5,1,0,0,1,0,0,0,0,0,1,0.5,1,1,0,0,1,0.5,0,1,0,1,0.5,0,0.5,0,1,1,1,1,0.5,1,1,1,0.5,0,0] relative_absolute_error 0.6023241629302226 relative_absolute_error 0.605008978115038 relative_absolute_error 0.6217202935952926 relative_absolute_error 0.6471818550417022 relative_absolute_error 0.6369201435489308 relative_absolute_error 0.6480163705542483 relative_absolute_error 0.6319597034559146 relative_absolute_error 0.6540809429066994 relative_absolute_error 0.6008480681776127 relative_absolute_error 0.5619541968973779 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 0.0897678274993853 root_mean_squared_error 0.0889440612573376 root_mean_squared_error 0.09232434575200137 root_mean_squared_error 0.09094116956478102 root_mean_squared_error 0.09260394593438483 root_mean_squared_error 0.09190075425017251 root_mean_squared_error 0.09032188182963481 root_mean_squared_error 0.0925583437749283 root_mean_squared_error 0.08764211295384126 root_mean_squared_error 0.08564932672981034 root_relative_squared_error 0.9022006123054797 root_relative_squared_error 0.8939214500635605 root_relative_squared_error 0.927894587498275 root_relative_squared_error 0.91399314376505 root_relative_squared_error 0.9307046750627626 root_relative_squared_error 0.9236373327226706 root_relative_squared_error 0.9077690678415684 root_relative_squared_error 0.9302463561156498 root_relative_squared_error 0.8808363772782966 root_relative_squared_error 0.8608081221495095 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 234.02769799577072 usercpu_time_millis 230.09217299841112 usercpu_time_millis 183.09209500148427 usercpu_time_millis 186.21933500253363 usercpu_time_millis 187.90746000377112 usercpu_time_millis 185.99043400172377 usercpu_time_millis 190.25465600498137 usercpu_time_millis 185.94350599960308 usercpu_time_millis 188.9881949973642 usercpu_time_millis 185.4880469982163 usercpu_time_millis_testing 1.7363119986839592 usercpu_time_millis_testing 1.7134949994215276 usercpu_time_millis_testing 1.3744159987254534 usercpu_time_millis_testing 1.3843930028087925 usercpu_time_millis_testing 1.5252400007739197 usercpu_time_millis_testing 1.4967780007282272 usercpu_time_millis_testing 1.4234020018193405 usercpu_time_millis_testing 1.4106740018178243 usercpu_time_millis_testing 1.4324309995572548 usercpu_time_millis_testing 1.3787269999738783 usercpu_time_millis_training 232.29138599708676 usercpu_time_millis_training 228.3786779989896 usercpu_time_millis_training 181.7176790027588 usercpu_time_millis_training 184.83494199972483 usercpu_time_millis_training 186.3822200029972 usercpu_time_millis_training 184.49365600099554 usercpu_time_millis_training 188.83125400316203 usercpu_time_millis_training 184.53283199778525 usercpu_time_millis_training 187.55576399780693 usercpu_time_millis_training 184.10931999824243