8959040 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) 6894644 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 5.73796979652682 7650 cache_size 200 7650 class_weight null 7650 coef0 0.37602701870407707 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.0033271124361024993 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.000319233217278817 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 18833334 description https://api.openml.org/data/download/18833334/description.xml -1 18833335 predictions https://api.openml.org/data/download/18833335/predictions.arff area_under_roc_curve 0.9179292929292928 [0.904356,0.968434,1,1,0.9375,0.874684,1,1,0.936869,0.96875,0.874684,0.999684,1,0.811869,1,0.90625,1,0.745265,0.716856,0.558712,0.905934,0.96875,0.966856,1,0.968119,0.715278,0.747475,0.967803,0.937184,1,0.999684,1,0.999369,0.810606,0.905619,0.967487,0.903093,0.715593,0.967487,0.999684,0.842487,0.968119,1,0.999053,0.968434,0.96875,0.874684,0.968119,0.904672,0.905934,0.936553,0.905619,0.90625,0.873737,0.811553,0.716856,1,0.968434,0.84154,0.904672,0.999369,0.968434,0.873422,0.999053,0.968119,0.842803,0.653409,1,0.874369,0.842487,0.905934,0.875,0.93529,0.96875,0.905303,0.968434,0.968434,0.81029,0.96875,0.999684,0.9375,0.905619,0.90625,0.873106,0.936869,0.937184,0.96875,0.936237,0.937184,1,0.874369,0.968119,0.968434,0.968119,0.96875,0.936869,0.936553,0.96654,0.686553,0.937184] average_cost 0 f_measure 0.8373317243362379 [0.742857,0.9375,1,1,0.933333,0.827586,1,1,0.875,0.967742,0.827586,0.969697,1,0.714286,1,0.896552,1,0.410256,0.482759,0.133333,0.866667,0.967742,0.810811,1,0.909091,0.411765,0.5,0.882353,0.903226,1,0.969697,1,0.941176,0.625,0.83871,0.857143,0.666667,0.424242,0.857143,0.969697,0.709677,0.909091,1,0.914286,0.9375,0.967742,0.827586,0.909091,0.764706,0.866667,0.848485,0.83871,0.896552,0.75,0.689655,0.482759,1,0.9375,0.647059,0.764706,0.941176,0.9375,0.727273,0.914286,0.909091,0.733333,0.333333,1,0.8,0.709677,0.866667,0.857143,0.756757,0.967742,0.8125,0.9375,0.9375,0.606061,0.967742,0.969697,0.933333,0.83871,0.896552,0.705882,0.875,0.903226,0.967742,0.823529,0.903226,1,0.8,0.909091,0.9375,0.909091,0.967742,0.875,0.848485,0.789474,0.48,0.903226] kappa 0.8358585858585859 kb_relative_information_score 1339.4325752976727 mean_absolute_error 0.0032499999999999855 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 0.8441104606906532 [0.684211,0.9375,1,1,1,0.923077,1,1,0.875,1,0.923077,0.941176,1,0.833333,1,1,1,0.347826,0.538462,0.142857,0.928571,1,0.714286,1,0.882353,0.388889,0.5,0.833333,0.933333,1,0.941176,1,0.888889,0.625,0.866667,0.789474,0.565217,0.411765,0.789474,0.941176,0.733333,0.882353,1,0.842105,0.9375,1,0.923077,0.882353,0.722222,0.928571,0.823529,0.866667,1,0.75,0.769231,0.538462,1,0.9375,0.611111,0.722222,0.888889,0.9375,0.705882,0.842105,0.882353,0.785714,0.357143,1,0.857143,0.733333,0.928571,1,0.666667,1,0.8125,0.9375,0.9375,0.588235,1,0.941176,1,0.866667,1,0.666667,0.875,0.933333,1,0.777778,0.933333,1,0.857143,0.882353,0.9375,0.882353,1,0.875,0.823529,0.681818,0.666667,0.933333] predictive_accuracy 0.8375 prior_entropy 6.6438561897747395 recall 0.8375 [0.8125,0.9375,1,1,0.875,0.75,1,1,0.875,0.9375,0.75,1,1,0.625,1,0.8125,1,0.5,0.4375,0.125,0.8125,0.9375,0.9375,1,0.9375,0.4375,0.5,0.9375,0.875,1,1,1,1,0.625,0.8125,0.9375,0.8125,0.4375,0.9375,1,0.6875,0.9375,1,1,0.9375,0.9375,0.75,0.9375,0.8125,0.8125,0.875,0.8125,0.8125,0.75,0.625,0.4375,1,0.9375,0.6875,0.8125,1,0.9375,0.75,1,0.9375,0.6875,0.3125,1,0.75,0.6875,0.8125,0.75,0.875,0.9375,0.8125,0.9375,0.9375,0.625,0.9375,1,0.875,0.8125,0.8125,0.75,0.875,0.875,0.9375,0.875,0.875,1,0.75,0.9375,0.9375,0.9375,0.9375,0.875,0.875,0.9375,0.375,0.875] relative_absolute_error 0.16414141414141312 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.05700877125495677 root_relative_squared_error 0.5729597091269387 total_cost 0 area_under_roc_curve 0.899072526072765 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[1,1,1,1,1,1,1,1,1,1,0.75,1,1,0.75,1,1,1,0.743671,1,0.490506,1,1,1,1,1,0.743671,1,1,1,1,1,1,1,0.496835,0.996855,0.996855,0.993711,0.5,1,1,0.746835,0.5,1,0.996855,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,0.75,1,1,1,0.746835,1,1,1,0.996855,1,1,0.5,1,0.5,0.75,1,1,0.996855,1,1,1,1,0.746835,0.75,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.996835,0.5,1] area_under_roc_curve 0.9116710452989409 [0.75,1,1,1,0.75,0.75,1,1,0.746835,1,1,1,1,0.75,1,1,1,0.740506,0.493711,0.496835,1,1,0.996835,1,1,0.75,1,1,1,1,1,1,1,0.75,1,0.996855,1,0.493711,0.996855,1,1,0.996855,1,1,1,1,0.75,1,0.996835,1,1,1,1,0.746835,1,0.75,1,1,0.996855,1,1,1,0.996835,1,1,0.746835,0.493671,1,1,0.746835,0.5,0.75,0.990566,1,1,1,1,0.75,1,1,1,1,0.75,0.75,1,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75] area_under_roc_curve 0.9115715309290661 [0.996835,1,1,1,1,0.75,1,1,1,1,1,1,1,0.496855,1,1,1,0.496835,0.996855,0.743671,1,1,1,1,1,0.996835,0.5,1,0.996855,1,1,1,1,0.746835,1,1,0.996835,0.743671,1,1,0.746835,1,1,1,1,1,1,1,1,1,1,0.496855,0.75,1,0.496835,0.5,1,0.996835,0.746835,1,1,1,0.5,1,0.75,1,0.496855,1,0.75,0.746835,1,1,0.996855,1,0.75,1,0.996835,0.746835,1,1,1,1,1,0.743671,0.996855,1,1,1,1,1,1,0.75,1,1,0.75,1,0.996835,0.996855,0.496855,1] area_under_roc_curve 0.9210652018151422 [0.75,0.996855,1,1,1,0.75,1,1,1,0.75,0.75,0.996835,1,1,1,1,1,0.996835,1,0.75,0.75,0.75,0.993671,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.743671,1,1,1,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.996855,0.996835,0.996835,1,1,0.75,0.996855,1,1,0.993711,1,1,0.5,0.996855,1,0.746835,1,1,0.75,1,1,0.75,1,1,1,1,1,1,0.75,0.75,0.996835,1,1,1,0.996855,0.996835,1,0.5,1,1,1,1,1,1,0.996855,0.5,1] area_under_roc_curve 0.9241899530292172 [0.996835,1,1,1,1,0.75,1,1,0.996855,1,1,1,1,1,1,0.75,1,0.996855,0.493671,0.5,0.996835,1,1,1,0.996835,0.5,0.493711,1,1,1,0.996835,1,1,1,1,1,0.743671,0.75,0.990506,1,1,1,1,1,0.5,0.75,0.5,0.996835,0.996855,1,1,1,1,1,0.75,0.75,1,1,0.5,1,0.993671,1,0.996855,0.996835,1,0.5,0.996855,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9149152137568664 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,1,0.75,1,0.993711,0.75,0.5,0.75,1,1,1,0.75,0.5,0.996855,1,0.5,1,1,1,0.996855,1,1,1,0.993671,0.996835,1,0.996855,0.5,1,1,1,1,1,1,0.75,0.996855,0.5,0.496855,0.75,0.75,0.996855,1,0.743671,1,1,1,0.990566,1,0.996835,1,1,1,0.496855,0.496855,1,1,0.746835,1,1,0.996835,1,0.996835,1,1,0.493711,1,1,0.75,1,0.75,1,0.75,0.75,1,0.996855,1,1,0.5,1,1,0.996855,1,1,1,1,0.75,1] area_under_roc_curve 0.930598678449168 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,1,1,1,1,1,1,1,0.496855,0.75,0.496855,1,1,0.5,1,1,0.493711,0.996855,0.996835,1,1,1,1,1,0.996855,0.996835,1,1,0.496835,0.75,1,0.5,1,1,0.996835,1,1,0.996855,1,1,1,0.75,0.996835,0.75,0.75,0.5,0.5,1,0.5,0.993671,1,1,1,1,0.996835,1,1,0.743671,1,0.996835,0.996855,1,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1] area_under_roc_curve 0.9022967916567153 [0.996855,1,1,1,1,1,1,1,1,1,0.996855,1,1,0.75,1,1,1,0.490566,0.5,0.493711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.996855,0.75,1,0.746835,0.75,1,1,0.996855,1,1,1,1,1,1,1,0.996855,0.996855,1,0.75,1,0.746835,0.75,0.996855,1,1,0.993671,0.75,1,0.75,0.496835,1,0.993711,0.996855,0.5,1,0.75,1,1,0.5,0.746835,0.75,0.75,0.75,1,1,1,1,1,0.496855,1,0.496855,1,0.996835,1,0.746835,1,1,0.996835,0.996835,1,0.75,1,1,0.996855,0.75,1,1] 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 f_measure 0.8674999999999997 [1,1,1,1,1,1,1,1,1,1,0.666667,1,1,0.666667,1,1,1,0.5,0.666667,0,1,1,0.666667,1,1,0.5,0,1,1,1,1,1,1,1,0.666667,0.666667,0.666667,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.666667,1,1,0.666667,1,0,1,1,0.666667,0.666667,1,1,1,1,1,1,1,1,1,1,0.8,1,1,1,1,1,1,0.666667,1,1,0.666667,0.666667,1,1,0.5,1,1,0.8,0.666667,1,0.666667,1,1,1,1,1,1,0.8,0.666667,0] kappa 0.7978681405448086 kappa 0.8673195387774444 kappa 0.8610014215763703 kappa 0.8231485867677246 kappa 0.8230927183699257 kappa 0.8420595435520809 kappa 0.8483532106468683 kappa 0.8294512435846823 kappa 0.8609904430929627 kappa 0.8042079501046067 kb_relative_information_score 127.93016311356081 kb_relative_information_score 138.95416954327428 kb_relative_information_score 137.951987140573 kb_relative_information_score 131.9388927243657 kb_relative_information_score 131.9388927243657 kb_relative_information_score 134.94543993246936 kb_relative_information_score 135.94762233517056 kb_relative_information_score 132.94107512706694 kb_relative_information_score 137.951987140573 kb_relative_information_score 128.93234551626205 mean_absolute_error 0.004000000000000002 mean_absolute_error 0.0026250000000000006 mean_absolute_error 0.0027500000000000007 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.003000000000000001 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.0027500000000000007 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] precision 0.9 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0.666667,1,1,1,1,1,1,1,1,1,0.666667,1,0] predictive_accuracy 0.8 predictive_accuracy 0.86875 predictive_accuracy 0.8625 predictive_accuracy 0.825 predictive_accuracy 0.825 predictive_accuracy 0.84375 predictive_accuracy 0.85 predictive_accuracy 0.83125 predictive_accuracy 0.8625 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 0.8 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,0,1,0.5,0.5,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,0,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.86875 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,0] recall 0.8625 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0,1,0,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.825 [0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5] recall 0.825 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,0,1,1,0.5,1,1,1,0,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1] recall 0.84375 [0.5,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1] recall 0.85 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.83125 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1] recall 0.8625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1] recall 0.80625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,0,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,1,0.5,0,1,1,1,0,1,0.5,1,1,0,0.5,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1] relative_absolute_error 0.2020202020202018 relative_absolute_error 0.13257575757575737 relative_absolute_error 0.1388888888888887 relative_absolute_error 0.17676767676767655 relative_absolute_error 0.17676767676767655 relative_absolute_error 0.1578282828282826 relative_absolute_error 0.1515151515151513 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.1388888888888887 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 0.0632455532033676 root_mean_squared_error 0.051234753829797995 root_mean_squared_error 0.052440442408507586 root_mean_squared_error 0.05916079783099617 root_mean_squared_error 0.05916079783099617 root_mean_squared_error 0.05590169943749475 root_mean_squared_error 0.05477225575051662 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.052440442408507586 root_mean_squared_error 0.06224949798994367 root_relative_squared_error 0.6356417261637279 root_relative_squared_error 0.5149286505444369 root_relative_squared_error 0.5270462766947296 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5504818825631801 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5270462766947296 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 439.5810559999518 usercpu_time_millis 444.83544399986386 usercpu_time_millis 437.91201099998034 usercpu_time_millis 454.3736909997733 usercpu_time_millis 453.28515599999264 usercpu_time_millis 457.8738609998254 usercpu_time_millis 437.19166400001086 usercpu_time_millis 445.8092659999693 usercpu_time_millis 430.33586299998206 usercpu_time_millis 442.94973299997764 usercpu_time_millis_testing 57.319350999932794 usercpu_time_millis_testing 56.463076 usercpu_time_millis_testing 53.69332999998733 usercpu_time_millis_testing 55.27115499990032 usercpu_time_millis_testing 55.343799999945986 usercpu_time_millis_testing 53.96093599983942 usercpu_time_millis_testing 59.31044399994789 usercpu_time_millis_testing 53.64065499998105 usercpu_time_millis_testing 55.75676300009036 usercpu_time_millis_testing 53.60855399999309 usercpu_time_millis_training 382.261705000019 usercpu_time_millis_training 388.37236799986385 usercpu_time_millis_training 384.218680999993 usercpu_time_millis_training 399.102535999873 usercpu_time_millis_training 397.94135600004665 usercpu_time_millis_training 403.912924999986 usercpu_time_millis_training 377.88122000006297 usercpu_time_millis_training 392.16861099998823 usercpu_time_millis_training 374.5790999998917 usercpu_time_millis_training 389.34117899998455