8957679 1935 Hilde Weerts 9954 Supervised Classification 8317 sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1) 6893287 categorical_features [] 7644 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 7644 handle_unknown "ignore" 7644 n_values "auto" 7644 sparse true 7644 threshold 0.0 7645 copy true 7646 with_mean false 7646 with_std true 7646 C 29.65270599279296 7650 cache_size 200 7650 class_weight null 7650 coef0 0.49450459302551075 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.014589585179816554 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking true 7650 tol 0.0009506450082535423 7650 verbose false 7650 axis 0 8316 categorical_features [] 8316 copy true 8316 fill_empty 0 8316 missing_values "NaN" 8316 strategy "mean" 8316 strategy_nominal "most_frequent" 8316 verbose 0 8316 memory null 8317 openml-python Sklearn_0.19.1. study_98 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 18830634 description https://api.openml.org/data/download/18830634/description.xml -1 18830635 predictions https://api.openml.org/data/download/18830635/predictions.arff area_under_roc_curve 0.922979797979798 [0.842487,0.96875,1,0.96875,0.96875,0.936553,0.999684,1,0.905934,0.96875,0.967803,0.937184,1,0.875,0.999684,0.96875,1,0.84154,0.745896,0.652462,0.874053,0.96875,0.998737,1,0.937184,0.684343,0.779356,0.936553,0.9375,1,0.999684,1,0.999369,0.715909,0.937184,0.936553,0.748106,0.716856,0.968434,1,0.935606,0.968434,1,0.936869,0.968434,0.96875,0.968434,0.968119,0.873422,0.936553,0.904672,0.905619,0.937184,0.842803,0.874053,0.841225,1,0.968434,0.903409,0.873737,0.968119,0.968434,0.874053,0.999053,0.999369,0.810922,0.71654,1,0.936869,0.873422,0.905303,0.96875,0.90404,0.96875,0.936553,0.96875,0.968434,0.842172,1,1,0.905934,0.936553,0.874684,0.717487,0.905303,1,1,0.935922,0.9375,1,0.937184,0.999684,0.967803,0.936869,0.96875,0.936869,0.905303,0.905303,0.717803,0.937184] average_cost 0 f_measure 0.8473425846298365 [0.709677,0.967742,1,0.967742,0.967742,0.848485,0.969697,1,0.866667,0.967742,0.882353,0.903226,1,0.857143,0.969697,0.967742,1,0.647059,0.432432,0.30303,0.774194,0.967742,0.888889,1,0.903226,0.375,0.580645,0.848485,0.933333,1,0.969697,1,0.941176,0.4375,0.903226,0.848485,0.533333,0.482759,0.9375,1,0.777778,0.9375,1,0.875,0.9375,0.967742,0.9375,0.909091,0.727273,0.848485,0.764706,0.83871,0.903226,0.733333,0.774194,0.628571,1,0.9375,0.684211,0.75,0.909091,0.9375,0.774194,0.914286,0.941176,0.645161,0.466667,1,0.875,0.727273,0.8125,0.967742,0.722222,0.967742,0.848485,0.967742,0.9375,0.6875,1,1,0.866667,0.848485,0.827586,0.518519,0.8125,1,1,0.8,0.933333,1,0.903226,0.969697,0.882353,0.875,0.967742,0.875,0.8125,0.8125,0.538462,0.903226] kappa 0.845959595959596 kb_relative_information_score 1355.4674937408909 mean_absolute_error 0.00304999999999999 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 0.8517535905357114 [0.733333,1,1,1,1,0.823529,0.941176,1,0.928571,1,0.833333,0.933333,1,1,0.941176,1,1,0.611111,0.380952,0.294118,0.8,1,0.8,1,0.933333,0.375,0.6,0.823529,1,1,0.941176,1,0.888889,0.4375,0.933333,0.823529,0.571429,0.538462,0.9375,1,0.7,0.9375,1,0.875,0.9375,1,0.9375,0.882353,0.705882,0.823529,0.722222,0.866667,0.933333,0.785714,0.8,0.578947,1,0.9375,0.590909,0.75,0.882353,0.9375,0.8,0.842105,0.888889,0.666667,0.5,1,0.875,0.705882,0.8125,1,0.65,1,0.823529,1,0.9375,0.6875,1,1,0.928571,0.823529,0.923077,0.636364,0.8125,1,1,0.736842,1,1,0.933333,0.941176,0.833333,0.875,1,0.875,0.8125,0.8125,0.7,0.933333] predictive_accuracy 0.8475 prior_entropy 6.6438561897747395 recall 0.8475 [0.6875,0.9375,1,0.9375,0.9375,0.875,1,1,0.8125,0.9375,0.9375,0.875,1,0.75,1,0.9375,1,0.6875,0.5,0.3125,0.75,0.9375,1,1,0.875,0.375,0.5625,0.875,0.875,1,1,1,1,0.4375,0.875,0.875,0.5,0.4375,0.9375,1,0.875,0.9375,1,0.875,0.9375,0.9375,0.9375,0.9375,0.75,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.6875,1,0.9375,0.8125,0.75,0.9375,0.9375,0.75,1,1,0.625,0.4375,1,0.875,0.75,0.8125,0.9375,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.4375,0.8125,1,1,0.875,0.875,1,0.875,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.4375,0.875] relative_absolute_error 0.15404040404040326 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.05522680508593621 root_relative_squared_error 0.5550502752731563 total_cost 0 area_under_roc_curve 0.9211448133110423 [0.996855,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.990566,0.5,1,0.996855,1,1,0.743671,0.746835,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.996855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.996855,1,1,1,1,1,1,0.75,1,1,1,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.5,1,1,1,1,1,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1] area_under_roc_curve 0.9147559907650663 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.75,0.75,0.487421,1,1,0.996855,1,1,0.75,0.493671,1,1,1,1,1,1,0.990506,0.75,0.5,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.746835,0.996835,0.993671,1,1,0.75,1,0.496855,1,1,0.996855,0.75,1,1,0.75,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,0.996835,0.996855,0.5,0.746835,1,1,0.996835,0.75,1,1,1,1,0.75,1,1,1,1,0.5,0.496855] area_under_roc_curve 0.95269086856142 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,0.996835,1,0.5,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.75,0.996855,1,0.993711,1,1,1,0.746835,0.5,1,1,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,0.993711,0.496835,1,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1] area_under_roc_curve 0.9053220285009151 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,0.5,1,1,1,1,1,1,1,0.746835,1,1,1,0.496855,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.490506,1,1,0.743671,0.5,1,0.990566,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75] area_under_roc_curve 0.9146962821431416 [0.746835,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.746835,0.990566,0.743671,0.75,1,1,1,1,0.990506,0.75,1,1,1,1,1,1,0.496835,1,1,0.746835,0.5,1,1,0.746835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.993671,1,1,1,0.5,1,1,1,1,1,0.75,0.996835,0.996835,1,1,1,0.75,1,0.996835,0.996835,1,1,1,1,1,0.75,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.5,1] area_under_roc_curve 0.9210452989411669 [0.75,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,1,1,1,1,1,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.496835,1,0.746835,0.75,0.743671,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.996855,0.996835,0.993671,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,1,1,0.996835,1,1,1,0.996855,1,0.75,1,1,0.75,1,1,0.996855,0.746835,0.75,0.746835,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,0.5,1] area_under_roc_curve 0.9336836239152932 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.746835,0.75,0.993671,1,1,1,1,0.5,0.496855,0.75,1,1,0.996835,1,1,0.996855,1,1,0.496835,0.746835,0.996835,1,1,1,1,1,0.5,0.75,1,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9273943157391926 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,0.996835,0.993711,1,1,1,1,1,0.496855,0.5,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.5,0.75,0.75,1,1,0.996855,1,1,1,1,0.993671,1,1,0.996835,1,1,0.996835,1] area_under_roc_curve 0.9369078894992438 [0.996855,1,1,0.75,1,0.996855,1,1,0.75,1,1,1,1,1,0.996835,1,1,0.493711,0.75,0.496855,0.996835,1,1,1,1,0.5,0.996855,1,1,1,1,1,1,0.996855,1,1,1,0.5,0.75,1,1,1,1,0.996835,1,1,0.996855,1,0.5,1,0.75,0.996835,1,0.75,0.75,1,1,0.5,0.996835,1,1,1,1,0.996835,1,1,0.743671,1,0.996835,1,0.996855,1,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1] area_under_roc_curve 0.9023166945306901 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.75,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.496855,0.75,0.996835,0.746835,1,1,1,0.996855,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.996835,0.75,0.75,1,0.746835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,1,1] 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 0.8420782502270125 kappa 0.8294040990403981 kappa 0.9052394677616773 kappa 0.810493900272415 kappa 0.8293906243829233 kappa 0.8420595435520809 kappa 0.8673038189644959 kappa 0.8546833043752962 kappa 0.8736326659558504 kappa 0.8042234063548451 kb_relative_information_score 134.94543993246936 kb_relative_information_score 132.94107512706694 kb_relative_information_score 144.96726395948158 kb_relative_information_score 129.93452791896325 kb_relative_information_score 132.94107512706694 kb_relative_information_score 134.94543993246936 kb_relative_information_score 138.95416954327425 kb_relative_information_score 136.9498047378718 kb_relative_information_score 139.95635194597548 kb_relative_information_score 128.93234551626202 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.001875 mean_absolute_error 0.003750000000000001 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.0026250000000000006 mean_absolute_error 0.002875000000000001 mean_absolute_error 0.0025000000000000005 mean_absolute_error 0.0038750000000000013 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 0.84375 predictive_accuracy 0.83125 predictive_accuracy 0.90625 predictive_accuracy 0.8125 predictive_accuracy 0.83125 predictive_accuracy 0.84375 predictive_accuracy 0.86875 predictive_accuracy 0.85625 predictive_accuracy 0.875 predictive_accuracy 0.80625 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 0.84375 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.83125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0] recall 0.90625 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1] recall 0.8125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5] recall 0.83125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,0,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1] recall 0.84375 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.86875 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.85625 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.875 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1] recall 0.80625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0.5,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.1578282828282826 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.09469696969696954 relative_absolute_error 0.18939393939393911 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.1578282828282826 relative_absolute_error 0.13257575757575737 relative_absolute_error 0.14520202020202 relative_absolute_error 0.12626262626262608 relative_absolute_error 0.19570707070707044 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 0.05590169943749475 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.04330127018922193 root_mean_squared_error 0.061237243569579464 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.05590169943749475 root_mean_squared_error 0.051234753829797995 root_mean_squared_error 0.05361902647381805 root_mean_squared_error 0.05 root_mean_squared_error 0.06224949798994367 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.4351941398892443 root_relative_squared_error 0.6154574548966634 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5149286505444369 root_relative_squared_error 0.5388914922357191 root_relative_squared_error 0.5025189076296057 root_relative_squared_error 0.6256309946079566 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 592.9632799999922 usercpu_time_millis 589.9448509999843 usercpu_time_millis 602.4351830000114 usercpu_time_millis 592.2232090000534 usercpu_time_millis 583.6452339999596 usercpu_time_millis 581.947318999994 usercpu_time_millis 561.6817110000056 usercpu_time_millis 557.7118030000179 usercpu_time_millis 567.3782340000457 usercpu_time_millis 562.2651709999786 usercpu_time_millis_testing 53.50260900002013 usercpu_time_millis_testing 53.95288199997594 usercpu_time_millis_testing 54.86113000000614 usercpu_time_millis_testing 53.58676700001297 usercpu_time_millis_testing 50.94488200001024 usercpu_time_millis_testing 51.465183999994224 usercpu_time_millis_testing 51.485689000003276 usercpu_time_millis_testing 51.621695999983785 usercpu_time_millis_testing 50.97127900000942 usercpu_time_millis_testing 51.73477199997478 usercpu_time_millis_training 539.4606709999721 usercpu_time_millis_training 535.9919690000083 usercpu_time_millis_training 547.5740530000053 usercpu_time_millis_training 538.6364420000405 usercpu_time_millis_training 532.7003519999494 usercpu_time_millis_training 530.4821349999997 usercpu_time_millis_training 510.19602200000236 usercpu_time_millis_training 506.0901070000341 usercpu_time_millis_training 516.4069550000363 usercpu_time_millis_training 510.53039900000385