8958687 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) 6894291 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 13.685410278618933 7650 cache_size 200 7650 class_weight null 7650 coef0 0.43872833905918407 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.007274733449149372 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.0005687394533659914 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 18832636 description https://api.openml.org/data/download/18832636/description.xml -1 18832637 predictions https://api.openml.org/data/download/18832637/predictions.arff area_under_roc_curve 0.9204545454545456 [0.842803,0.96875,1,1,0.96875,0.874369,0.999684,1,0.936553,0.96875,0.967803,0.937184,1,0.843434,1,0.96875,1,0.809343,0.714331,0.590593,0.842803,0.96875,0.998737,1,0.937184,0.715278,0.715909,0.936553,0.9375,1,0.999684,1,0.999369,0.81029,0.937184,0.967803,0.71654,0.715909,0.999369,1,0.904356,0.968434,1,0.968119,0.968434,0.96875,0.9375,0.968119,0.904672,0.936869,0.904672,0.905619,0.937184,0.842487,0.874053,0.778725,1,0.968434,0.873106,0.873737,0.968119,0.968434,0.874053,0.967803,0.999369,0.810606,0.684975,1,0.905619,0.873422,0.905303,0.9375,0.904356,0.96875,0.936869,0.96875,0.968434,0.84154,1,1,0.905934,0.937184,0.874684,0.873106,0.905303,1,1,0.935922,0.9375,1,0.874684,0.999369,0.968119,0.936869,0.96875,0.936869,0.905303,0.905303,0.686237,0.937184] average_cost 0 f_measure 0.8426648814107015 [0.733333,0.967742,1,1,0.967742,0.8,0.969697,1,0.848485,0.967742,0.882353,0.903226,1,0.785714,1,0.967742,1,0.555556,0.378378,0.206897,0.733333,0.967742,0.888889,1,0.903226,0.411765,0.4375,0.848485,0.933333,1,0.969697,1,0.941176,0.606061,0.903226,0.882353,0.466667,0.4375,0.941176,1,0.742857,0.9375,1,0.909091,0.9375,0.967742,0.933333,0.909091,0.764706,0.875,0.764706,0.83871,0.903226,0.709677,0.774194,0.545455,1,0.9375,0.705882,0.75,0.909091,0.9375,0.774194,0.882353,0.941176,0.625,0.4,1,0.83871,0.727273,0.8125,0.933333,0.742857,0.967742,0.875,0.967742,0.9375,0.647059,1,1,0.866667,0.903226,0.827586,0.705882,0.8125,1,1,0.8,0.933333,1,0.827586,0.941176,0.909091,0.875,0.967742,0.875,0.8125,0.8125,0.461538,0.903226] kappa 0.8409090909090909 kb_relative_information_score 1347.4500345192819 mean_absolute_error 0.003149999999999988 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 0.8468775346170857 [0.785714,1,1,1,1,0.857143,0.941176,1,0.823529,1,0.833333,0.933333,1,0.916667,1,1,1,0.5,0.333333,0.230769,0.785714,1,0.8,1,0.933333,0.388889,0.4375,0.823529,1,1,0.941176,1,0.888889,0.588235,0.933333,0.833333,0.5,0.4375,0.888889,1,0.684211,0.9375,1,0.882353,0.9375,1,1,0.882353,0.722222,0.875,0.722222,0.866667,0.933333,0.733333,0.8,0.529412,1,0.9375,0.666667,0.75,0.882353,0.9375,0.8,0.833333,0.888889,0.625,0.428571,1,0.866667,0.705882,0.8125,1,0.684211,1,0.875,1,0.9375,0.611111,1,1,0.928571,0.933333,0.923077,0.666667,0.8125,1,1,0.736842,1,1,0.923077,0.888889,0.882353,0.875,1,0.875,0.8125,0.8125,0.6,0.933333] predictive_accuracy 0.8425 prior_entropy 6.6438561897747395 recall 0.8425 [0.6875,0.9375,1,1,0.9375,0.75,1,1,0.875,0.9375,0.9375,0.875,1,0.6875,1,0.9375,1,0.625,0.4375,0.1875,0.6875,0.9375,1,1,0.875,0.4375,0.4375,0.875,0.875,1,1,1,1,0.625,0.875,0.9375,0.4375,0.4375,1,1,0.8125,0.9375,1,0.9375,0.9375,0.9375,0.875,0.9375,0.8125,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.5625,1,0.9375,0.75,0.75,0.9375,0.9375,0.75,0.9375,1,0.625,0.375,1,0.8125,0.75,0.8125,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.75,0.8125,1,1,0.875,0.875,1,0.75,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.375,0.875] relative_absolute_error 0.15909090909090817 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.056124860801609014 root_relative_squared_error 0.5640760748177647 total_cost 0 area_under_roc_curve 0.9084666825889659 [1,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.490566,0.5,1,0.996855,1,1,0.740506,0.743671,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.496855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.496855,1,1,1,1,1,1,0.75,1,1,0.996835,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.493671,1,1,1,1,0.5,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1] area_under_roc_curve 0.9273744128652176 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.746835,0.746835,0.496855,1,1,0.996855,1,1,0.746835,0.490506,1,1,1,1,1,1,1,0.75,0.996855,0.496855,0.496855,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.496855,1,1,1,0.75,1,1,1,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,1,0.996855,1,0.746835,1,1,0.996835,0.75,1,0.75,1,1,0.75,1,1,1,1,0.5,0.496855] area_under_roc_curve 0.9368680837512935 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,0.75,1,1,1,0.993671,1,0.496835,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.496835,0.996855,0.996855,0.993711,1,1,1,0.743671,0.5,1,1,0.996835,1,0.75,1,0.75,1,0.996835,1,1,1,1,0.75,1,1,0.996855,0.496835,1,1,1,0.5,1,1,0.75,1,1,0.75,1,1,1,1,0.996855,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.75,0.5,1] area_under_roc_curve 0.9084865854629406 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,0.75,1,1,1,1,1,1,1,0.75,1,1,1,0.496855,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.990506,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.493671,1,1,0.743671,0.5,1,0.990566,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75] area_under_roc_curve 0.9115715309290661 [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 0.9179205477270918 [0.75,1,1,1,1,0.75,1,1,0.996855,0.75,1,0.996835,1,1,1,1,1,0.996835,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.490506,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.993711,0.996835,0.996835,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,0.996855,1,0.746835,1,1,1,1,1,0.75,1,1,0.75,1,1,0.996855,0.75,0.75,0.996835,1,1,1,0.996855,1,1,0.5,1,1,1,1,1,1,1,0.5,1] area_under_roc_curve 0.9210851046891172 [1,1,1,1,1,0.75,1,1,0.996855,1,1,1,1,1,1,1,1,1,0.5,0.5,0.743671,1,1,1,1,0.5,0.493711,0.75,1,1,0.996835,1,1,0.993711,1,1,0.493671,0.746835,0.993671,1,1,1,1,1,0.5,0.75,0.75,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,1,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9337433325372183 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,1,0.993711,1,1,1,1,1,0.496855,0.496855,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,1,0.75,1,1,0.996855,1,1,1,1,0.996835,1,1,0.996835,1,1,1,1] 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 0.9022768887827401 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.746835,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.496855,0.5,0.996835,0.75,1,1,1,1,0.996855,0.75,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.993671,0.75,0.75,1,0.496835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,0.996835,1] 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 0.8167746011688517 kappa 0.8546775658492279 kappa 0.8736426456071076 kappa 0.8168107702633345 kappa 0.8230857323381905 kappa 0.8357484107869073 kappa 0.842047069973148 kappa 0.867324777887463 kappa 0.8736176935229067 kappa 0.8042156785347754 kb_relative_information_score 130.93671032166446 kb_relative_information_score 136.94980473787183 kb_relative_information_score 139.95635194597548 kb_relative_information_score 130.93671032166446 kb_relative_information_score 131.9388927243657 kb_relative_information_score 133.94325752976815 kb_relative_information_score 134.94543993246936 kb_relative_information_score 138.95416954327425 kb_relative_information_score 139.95635194597548 kb_relative_information_score 128.93234551626202 mean_absolute_error 0.003625000000000001 mean_absolute_error 0.002875000000000001 mean_absolute_error 0.0025000000000000005 mean_absolute_error 0.003625000000000001 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.0032500000000000007 mean_absolute_error 0.0031250000000000006 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 0.81875 predictive_accuracy 0.85625 predictive_accuracy 0.875 predictive_accuracy 0.81875 predictive_accuracy 0.825 predictive_accuracy 0.8375 predictive_accuracy 0.84375 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 0.81875 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.85625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,1,0,0] recall 0.875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1] recall 0.81875 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5] recall 0.825 [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 0.8375 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1] recall 0.84375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] 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 0.18308080808080782 relative_absolute_error 0.14520202020202 relative_absolute_error 0.12626262626262608 relative_absolute_error 0.18308080808080782 relative_absolute_error 0.17676767676767655 relative_absolute_error 0.1641414141414139 relative_absolute_error 0.1578282828282826 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 0.06020797289396149 root_mean_squared_error 0.05361902647381805 root_mean_squared_error 0.05 root_mean_squared_error 0.06020797289396149 root_mean_squared_error 0.05916079783099617 root_mean_squared_error 0.0570087712549569 root_mean_squared_error 0.05590169943749475 root_mean_squared_error 0.051234753829797995 root_mean_squared_error 0.05 root_mean_squared_error 0.06224949798994367 root_relative_squared_error 0.6051128953853288 root_relative_squared_error 0.5388914922357191 root_relative_squared_error 0.5025189076296057 root_relative_squared_error 0.6051128953853288 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.5729597091269403 root_relative_squared_error 0.5618332187193681 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 475.69599799999196 usercpu_time_millis 470.06035699996573 usercpu_time_millis 466.9689079998989 usercpu_time_millis 460.68772600006014 usercpu_time_millis 460.0077299999157 usercpu_time_millis 459.6392930000093 usercpu_time_millis 475.2056239997273 usercpu_time_millis 469.63239199999407 usercpu_time_millis 458.00123899994105 usercpu_time_millis 459.868734000338 usercpu_time_millis_testing 54.90942799997356 usercpu_time_millis_testing 54.05771400000958 usercpu_time_millis_testing 51.46094799988532 usercpu_time_millis_testing 53.085619000057704 usercpu_time_millis_testing 53.84754700003214 usercpu_time_millis_testing 54.851635999966675 usercpu_time_millis_testing 52.47810599985314 usercpu_time_millis_testing 52.58580099985011 usercpu_time_millis_testing 54.04402099998151 usercpu_time_millis_testing 52.35412800016093 usercpu_time_millis_training 420.7865700000184 usercpu_time_millis_training 416.00264299995615 usercpu_time_millis_training 415.50796000001355 usercpu_time_millis_training 407.60210700000243 usercpu_time_millis_training 406.16018299988355 usercpu_time_millis_training 404.7876570000426 usercpu_time_millis_training 422.7275179998742 usercpu_time_millis_training 417.04659100014396 usercpu_time_millis_training 403.95721799995954 usercpu_time_millis_training 407.5146060001771