8959021 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) 6894625 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 15.226343639972196 7650 cache_size 200 7650 class_weight null 7650 coef0 0.4464248819216967 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.008007945520279747 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.0006105194828685501 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 18833298 description https://api.openml.org/data/download/18833298/description.xml -1 18833299 predictions https://api.openml.org/data/download/18833299/predictions.arff area_under_roc_curve 0.9217171717171717 [0.842803,0.96875,1,1,0.96875,0.874369,0.999684,1,0.936553,0.96875,0.967803,0.937184,1,0.843434,1,0.96875,1,0.809659,0.714331,0.590909,0.842803,0.96875,0.998737,1,0.937184,0.746843,0.715909,0.936553,0.9375,1,0.999684,1,0.999369,0.809975,0.937184,0.968119,0.716225,0.71654,0.999369,1,0.904356,0.968434,1,0.936869,0.968434,0.96875,0.9375,0.968119,0.904672,0.936553,0.904672,0.905619,0.937184,0.842487,0.874053,0.81029,1,0.968434,0.87279,0.873737,0.968119,0.968434,0.874053,0.967803,0.999369,0.810606,0.716225,1,0.905619,0.873422,0.905303,0.9375,0.904672,0.96875,0.936869,0.96875,0.968434,0.84154,1,1,0.905934,0.937184,0.874684,0.841856,0.905303,1,1,0.935922,0.9375,1,0.937184,0.999369,0.968119,0.936869,0.96875,0.936869,0.905303,0.905303,0.717487,0.937184] average_cost 0 f_measure 0.8451829695386914 [0.733333,0.967742,1,1,0.967742,0.8,0.969697,1,0.848485,0.967742,0.882353,0.903226,1,0.785714,1,0.967742,1,0.571429,0.378378,0.214286,0.733333,0.967742,0.888889,1,0.903226,0.470588,0.4375,0.848485,0.933333,1,0.969697,1,0.941176,0.588235,0.903226,0.909091,0.451613,0.466667,0.941176,1,0.742857,0.9375,1,0.875,0.9375,0.967742,0.933333,0.909091,0.764706,0.848485,0.764706,0.83871,0.903226,0.709677,0.774194,0.606061,1,0.9375,0.685714,0.75,0.909091,0.9375,0.774194,0.882353,0.941176,0.625,0.451613,1,0.83871,0.727273,0.8125,0.933333,0.764706,0.967742,0.875,0.967742,0.9375,0.647059,1,1,0.866667,0.903226,0.827586,0.666667,0.8125,1,1,0.8,0.933333,1,0.903226,0.941176,0.909091,0.875,0.967742,0.875,0.8125,0.8125,0.518519,0.903226] kappa 0.8434343434343434 kb_relative_information_score 1351.4587641300861 mean_absolute_error 0.003099999999999989 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 0.8490239353010248 [0.785714,1,1,1,1,0.857143,0.941176,1,0.823529,1,0.833333,0.933333,1,0.916667,1,1,1,0.526316,0.333333,0.25,0.785714,1,0.8,1,0.933333,0.444444,0.4375,0.823529,1,1,0.941176,1,0.888889,0.555556,0.933333,0.882353,0.466667,0.5,0.888889,1,0.684211,0.9375,1,0.875,0.9375,1,1,0.882353,0.722222,0.823529,0.722222,0.866667,0.933333,0.733333,0.8,0.588235,1,0.9375,0.631579,0.75,0.882353,0.9375,0.8,0.833333,0.888889,0.625,0.466667,1,0.866667,0.705882,0.8125,1,0.722222,1,0.875,1,0.9375,0.611111,1,1,0.928571,0.933333,0.923077,0.647059,0.8125,1,1,0.736842,1,1,0.933333,0.888889,0.882353,0.875,1,0.875,0.8125,0.8125,0.636364,0.933333] predictive_accuracy 0.845 prior_entropy 6.6438561897747395 recall 0.845 [0.6875,0.9375,1,1,0.9375,0.75,1,1,0.875,0.9375,0.9375,0.875,1,0.6875,1,0.9375,1,0.625,0.4375,0.1875,0.6875,0.9375,1,1,0.875,0.5,0.4375,0.875,0.875,1,1,1,1,0.625,0.875,0.9375,0.4375,0.4375,1,1,0.8125,0.9375,1,0.875,0.9375,0.9375,0.875,0.9375,0.8125,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.625,1,0.9375,0.75,0.75,0.9375,0.9375,0.75,0.9375,1,0.625,0.4375,1,0.8125,0.75,0.8125,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.6875,0.8125,1,1,0.875,0.875,1,0.875,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.4375,0.875] relative_absolute_error 0.15656565656565571 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.05567764362830012 root_relative_squared_error 0.5595813731096768 total_cost 0 area_under_roc_curve 0.9116113366770163 [1,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.493711,0.5,1,0.996855,1,1,0.743671,0.743671,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.496855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.996855,1,1,1,1,1,1,0.75,1,1,0.996835,0.496835,1,1,0.5,0.75,1,1,1,1,1,0.75,0.493671,1,1,1,1,0.5,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1] area_under_roc_curve 0.9241899530292172 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.746835,0.75,0.493711,1,1,0.996855,1,1,0.746835,0.490506,1,1,1,1,1,1,0.993671,0.75,1,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996835,0.996835,0.996835,1,1,0.75,1,0.496855,1,1,1,0.75,1,1,1,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,1,0.996855,1,0.746835,1,1,0.996835,0.75,1,0.75,1,1,0.75,1,1,1,1,0.5,0.496855] area_under_roc_curve 0.9432171005493191 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,0.75,1,1,1,0.996835,1,0.5,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.5,0.996855,0.996855,0.993711,1,1,1,0.743671,0.5,1,1,0.996835,1,0.75,1,0.75,1,0.996835,1,1,1,1,1,1,1,0.993711,0.496835,1,1,1,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996855,1,1,0.996835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.75,1,1] area_under_roc_curve 0.9147957965130162 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,1,1,1,1,1,1,1,1,0.75,1,1,0.996855,0.5,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.493671,1,1,0.743671,0.5,1,0.993711,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,1,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75] area_under_roc_curve 0.9115715309290661 [0.746835,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.496835,0.987421,0.746835,0.75,1,1,1,1,0.993671,0.5,1,1,1,1,1,1,0.746835,1,1,0.496835,0.746835,1,1,0.746835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.75,1,1,1,0.5,1,1,1,1,1,0.75,0.996835,0.996835,1,1,1,0.75,1,0.996835,0.996835,1,1,1,1,1,0.993671,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.496855,1] area_under_roc_curve 0.921085104689117 [0.75,1,1,1,1,0.75,1,1,0.996855,0.75,1,0.996835,1,1,1,1,1,0.996835,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.746835,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.490506,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.993711,0.996835,0.996835,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,0.996855,1,0.746835,1,1,1,1,1,0.75,1,1,0.75,1,1,0.996855,0.75,0.75,0.996835,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,0.5,1] area_under_roc_curve 0.9179205477270918 [1,1,1,1,1,0.75,1,1,0.996855,1,1,1,1,1,1,1,1,1,0.496835,0.5,0.743671,1,1,1,1,0.5,0.493711,0.75,1,1,0.996835,1,1,0.993711,1,1,0.493671,0.746835,0.993671,1,1,1,1,1,0.5,0.75,0.75,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9337234296632435 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,1,0.993711,1,1,1,1,1,0.496855,0.5,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,1,0.75,1,1,0.996855,1,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1] area_under_roc_curve 0.9369078894992438 [0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.493711,0.75,0.493711,0.996835,1,1,1,1,0.496855,0.496855,1,1,1,1,1,1,0.996855,1,1,1,0.5,1,1,1,1,1,0.996835,1,1,1,1,0.5,1,0.75,0.996835,1,0.75,0.75,0.5,1,0.5,0.993671,1,1,1,1,0.996835,1,1,0.743671,1,0.996835,1,0.996855,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1] area_under_roc_curve 0.9022967916567153 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.746835,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.996855,0.75,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.993671,0.75,0.75,1,0.496835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,1,1] 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 0.8230927183699257 kappa 0.8483532106468683 kappa 0.8862873613140126 kappa 0.8294377763739735 kappa 0.8230857323381905 kappa 0.8420720151610865 kappa 0.8357289527720739 kappa 0.8673195387774444 kappa 0.8736176935229067 kappa 0.8042234063548451 kb_relative_information_score 131.9388927243657 kb_relative_information_score 135.9476223351706 kb_relative_information_score 141.9607167513779 kb_relative_information_score 132.94107512706694 kb_relative_information_score 131.9388927243657 kb_relative_information_score 134.94543993246936 kb_relative_information_score 133.94325752976815 kb_relative_information_score 138.95416954327425 kb_relative_information_score 139.95635194597548 kb_relative_information_score 128.93234551626202 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.003000000000000001 mean_absolute_error 0.0022500000000000003 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.0032500000000000007 mean_absolute_error 0.0026250000000000006 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 0.825 predictive_accuracy 0.85 predictive_accuracy 0.8875 predictive_accuracy 0.83125 predictive_accuracy 0.825 predictive_accuracy 0.84375 predictive_accuracy 0.8375 predictive_accuracy 0.86875 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 0.825 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,1,0,0] recall 0.8875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1] recall 0.83125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5] recall 0.825 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,0.5,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1] recall 0.84375 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.8375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.86875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.875 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1] recall 0.80625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.17676767676767655 relative_absolute_error 0.1515151515151513 relative_absolute_error 0.11363636363636348 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.17676767676767655 relative_absolute_error 0.1578282828282826 relative_absolute_error 0.1641414141414139 relative_absolute_error 0.13257575757575737 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 0.05916079783099617 root_mean_squared_error 0.05477225575051662 root_mean_squared_error 0.047434164902525694 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.05916079783099617 root_mean_squared_error 0.05590169943749475 root_mean_squared_error 0.0570087712549569 root_mean_squared_error 0.051234753829797995 root_mean_squared_error 0.05 root_mean_squared_error 0.06224949798994367 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.5504818825631801 root_relative_squared_error 0.4767312946227959 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5729597091269403 root_relative_squared_error 0.5149286505444369 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 469.77259699997376 usercpu_time_millis 477.58256399993115 usercpu_time_millis 474.81244499999775 usercpu_time_millis 480.7856989998527 usercpu_time_millis 488.32102999995186 usercpu_time_millis 472.2232780002287 usercpu_time_millis 484.3912750002346 usercpu_time_millis 478.10306099995614 usercpu_time_millis 489.6718110001075 usercpu_time_millis 488.24846000002253 usercpu_time_millis_testing 53.98987900002794 usercpu_time_millis_testing 56.38235999981589 usercpu_time_millis_testing 53.24294599995483 usercpu_time_millis_testing 55.39799799998946 usercpu_time_millis_testing 57.822310000119614 usercpu_time_millis_testing 53.951894000192624 usercpu_time_millis_testing 55.81965300007141 usercpu_time_millis_testing 54.81100299994068 usercpu_time_millis_testing 55.73941400007243 usercpu_time_millis_testing 55.7208239999909 usercpu_time_millis_training 415.7827179999458 usercpu_time_millis_training 421.20020400011526 usercpu_time_millis_training 421.5694990000429 usercpu_time_millis_training 425.3877009998632 usercpu_time_millis_training 430.49871999983225 usercpu_time_millis_training 418.27138400003605 usercpu_time_millis_training 428.5716220001632 usercpu_time_millis_training 423.29205800001546 usercpu_time_millis_training 433.93239700003505 usercpu_time_millis_training 432.52763600003163