8958316 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) 6893923 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 93.21828698117817 7650 cache_size 200 7650 class_weight null 7650 coef0 0.5771270548215587 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.04090120015751121 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.0020347367041112013 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 18831900 description https://api.openml.org/data/download/18831900/description.xml -1 18831901 predictions https://api.openml.org/data/download/18831901/predictions.arff area_under_roc_curve 0.920770202020202 [0.874369,0.96875,1,0.9375,0.937184,0.874053,1,1,0.905934,0.9375,0.968119,0.968434,1,0.90625,0.99779,1,1,0.747159,0.745896,0.588699,0.874369,0.96875,0.967172,1,0.937184,0.746212,0.74779,0.967487,0.937184,1,0.968434,0.96875,0.999369,0.809975,0.905619,0.936869,0.77904,0.685606,0.968119,1,0.935606,0.936869,1,0.936553,0.968434,0.96875,0.937184,0.968119,0.904987,0.905619,0.904672,0.905619,0.937184,0.842803,0.905303,0.748106,1,0.968434,0.873106,0.842172,0.936869,0.96875,0.842487,0.968119,0.968119,0.841856,0.717172,1,0.968119,0.905303,0.874369,0.937184,0.93529,0.96875,0.904987,0.96875,0.968434,0.842172,1,1,0.937184,0.936553,0.90625,0.779672,0.905619,0.968434,1,0.936237,0.937184,1,0.936869,0.999684,0.937184,0.968434,0.96875,0.936869,0.936869,0.936553,0.779672,0.937184] average_cost 0 f_measure 0.844400352374752 [0.8,0.967742,1,0.933333,0.903226,0.774194,1,1,0.866667,0.933333,0.909091,0.9375,1,0.896552,0.820513,1,1,0.484848,0.432432,0.171429,0.8,0.967742,0.833333,1,0.903226,0.444444,0.516129,0.857143,0.903226,1,0.9375,0.967742,0.941176,0.588235,0.83871,0.875,0.5625,0.428571,0.909091,1,0.777778,0.875,1,0.848485,0.9375,0.967742,0.903226,0.909091,0.787879,0.83871,0.764706,0.83871,0.903226,0.733333,0.8125,0.533333,1,0.9375,0.705882,0.6875,0.875,0.967742,0.709677,0.909091,0.909091,0.666667,0.5,1,0.909091,0.8125,0.8,0.903226,0.756757,0.967742,0.787879,0.967742,0.9375,0.6875,1,1,0.903226,0.848485,0.896552,0.6,0.83871,0.9375,1,0.823529,0.903226,1,0.875,0.969697,0.903226,0.9375,0.967742,0.875,0.875,0.848485,0.6,0.903226] kappa 0.8415404040404041 kb_relative_information_score 1348.452216921983 mean_absolute_error 0.003137499999999988 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 0.8497254907302356 [0.857143,1,1,1,0.933333,0.8,1,1,0.928571,1,0.882353,0.9375,1,1,0.695652,1,1,0.470588,0.380952,0.157895,0.857143,1,0.75,1,0.933333,0.4,0.533333,0.789474,0.933333,1,0.9375,1,0.888889,0.555556,0.866667,0.875,0.5625,0.5,0.882353,1,0.7,0.875,1,0.823529,0.9375,1,0.933333,0.882353,0.764706,0.866667,0.722222,0.866667,0.933333,0.785714,0.8125,0.571429,1,0.9375,0.666667,0.6875,0.875,1,0.733333,0.882353,0.882353,0.647059,0.583333,1,0.882353,0.8125,0.857143,0.933333,0.666667,1,0.764706,1,0.9375,0.6875,1,1,0.933333,0.823529,1,0.642857,0.866667,0.9375,1,0.777778,0.933333,1,0.875,0.941176,0.933333,0.9375,1,0.875,0.875,0.823529,0.642857,0.933333] predictive_accuracy 0.843125 prior_entropy 6.6438561897747395 recall 0.843125 [0.75,0.9375,1,0.875,0.875,0.75,1,1,0.8125,0.875,0.9375,0.9375,1,0.8125,1,1,1,0.5,0.5,0.1875,0.75,0.9375,0.9375,1,0.875,0.5,0.5,0.9375,0.875,1,0.9375,0.9375,1,0.625,0.8125,0.875,0.5625,0.375,0.9375,1,0.875,0.875,1,0.875,0.9375,0.9375,0.875,0.9375,0.8125,0.8125,0.8125,0.8125,0.875,0.6875,0.8125,0.5,1,0.9375,0.75,0.6875,0.875,0.9375,0.6875,0.9375,0.9375,0.6875,0.4375,1,0.9375,0.8125,0.75,0.875,0.875,0.9375,0.8125,0.9375,0.9375,0.6875,1,1,0.875,0.875,0.8125,0.5625,0.8125,0.9375,1,0.875,0.875,1,0.875,1,0.875,0.9375,0.9375,0.875,0.875,0.875,0.5625,0.875] relative_absolute_error 0.15845959595959505 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.05601339125602009 root_relative_squared_error 0.5629557637320983 total_cost 0 area_under_roc_curve 0.9148156993869916 [0.996855,0.75,1,1,0.75,1,1,1,1,1,0.75,1,1,1,1,1,1,0.75,0.496835,0.490566,0.5,1,0.996855,1,1,0.743671,0.743671,0.996835,1,1,1,1,0.996835,0.496835,0.75,0.996855,1,0.996855,1,1,0.996855,0.996855,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.496855,1,1,1,1,1,1,0.75,1,1,1,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.5,1,1,1,1,1,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.5,0.993671,0.746835,1] area_under_roc_curve 0.9179205477270915 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,0.75,0.746835,0.487421,1,1,0.996855,1,1,0.746835,0.493671,1,0.996835,1,1,1,1,0.996835,0.75,0.496855,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.746835,0.996835,0.993671,1,1,0.75,1,0.496855,1,1,1,0.5,1,1,0.75,1,1,0.996835,0.75,1,1,1,0.996835,1,1,1,0.996855,1,1,0.993671,1,1,0.75,0.996835,1,1,0.75,1,1,0.996835,0.75,1,0.75,1,0.75,1,1,1,1,1,0.75,0.496855] area_under_roc_curve 0.9368879866252685 [1,1,1,1,1,0.746835,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.743671,1,0.496835,1,1,0.75,1,1,0.746835,1,0.996855,1,1,1,1,1,0.75,0.993711,1,0.993711,0.5,1,1,0.746835,0.5,1,1,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,0.996855,0.496835,1,1,0.75,0.5,1,1,1,1,1,0.75,1,0.996835,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,0.996855,1] area_under_roc_curve 0.9148156993869915 [0.75,1,1,1,0.75,0.75,1,1,0.746835,1,1,1,1,1,1,1,1,0.743671,0.493711,0.746835,1,1,0.993671,1,0.5,1,1,1,1,1,1,1,1,0.75,1,1,1,0.496855,1,1,0.996835,0.996855,1,0.996855,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.743671,1,1,0.996855,1,0.996855,1,1,1,0.75,0.5,0.496835,1,1,0.746835,0.5,1,0.990566,1,1,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,1,1,1,0.996855,0.75,0.996835,0.993711,0.75] area_under_roc_curve 0.9147161850171166 [0.75,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,0.996855,1,1,0.746835,0.990566,0.743671,0.75,1,1,1,1,0.987342,0.5,1,1,1,1,0.5,1,0.496835,1,1,0.746835,0.5,1,1,0.996835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.746835,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,1,1,1,0.75,1,0.996835,1,1,1,1,1,1,0.746835,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.5,1] area_under_roc_curve 0.9178807419791417 [0.75,1,1,0.75,1,0.75,1,1,1,0.75,1,0.996835,1,1,0.993711,1,1,0.996835,1,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.996835,1,0.75,0.75,0.743671,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,1,0.996835,0.996835,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,1,1,0.996835,1,0.75,1,0.996855,1,0.75,1,1,0.746835,1,1,0.996855,0.746835,0.75,0.746835,1,1,1,0.996855,0.996835,1,1,1,1,1,1,1,1,1,0.5,1] area_under_roc_curve 0.9242098559031922 [1,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496835,0.5,0.993671,1,1,1,1,0.5,0.496855,1,1,1,0.746835,1,1,0.996855,1,1,0.493671,0.746835,0.993671,1,1,0.75,1,1,0.5,0.75,0.75,0.996835,1,1,1,0.996835,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,1,0.996855,0.996835,1,0.496855,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.5,1,1,0.996855,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9242297587771677 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496855,0.984177,0.496835,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,0.5,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,0.996835,0.990566,1,1,1,1,1,0.496855,0.5,1,1,0.996835,1,1,0.996835,1,0.996835,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,0.75,1,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1] area_under_roc_curve 0.9369277923732187 [0.996855,1,1,0.75,1,0.996855,1,1,0.75,1,1,1,1,1,0.996835,1,1,0.493711,1,0.496855,1,1,1,1,1,0.496855,0.996855,0.996835,1,1,1,1,1,0.996855,1,1,1,0.5,0.75,1,0.5,1,1,0.996835,1,1,0.996855,1,1,1,0.75,1,1,0.75,0.75,0.5,1,0.5,0.996835,1,0.75,1,0.996835,0.996835,1,0.996855,0.743671,1,0.996835,1,1,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1] area_under_roc_curve 0.9054215428707904 [1,1,1,1,1,0.996855,1,1,0.75,0.5,0.996855,1,1,0.75,0.993671,1,1,0.5,0.5,0.990566,1,1,1,1,1,0.496855,0.5,0.996835,0.75,1,1,1,1,0.993711,0.75,1,0.996835,1,1,1,0.996855,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.746835,1,1,1,1,0.996835,0.75,0.75,1,0.496835,1,0.993711,0.993711,0.5,1,0.75,1,1,0.5,0.746835,0.75,0.75,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,0.996835,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.75,1,1] 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 kappa 0.8294377763739735 kappa 0.8357289527720739 kappa 0.8736476348416646 kappa 0.8294445102451735 kappa 0.829397361977727 kappa 0.8357419252941641 kappa 0.8483532106468683 kappa 0.8483532106468683 kappa 0.8736326659558504 kappa 0.8105088626584027 kb_relative_information_score 132.94107512706694 kb_relative_information_score 133.94325752976818 kb_relative_information_score 139.95635194597548 kb_relative_information_score 132.94107512706694 kb_relative_information_score 132.94107512706694 kb_relative_information_score 133.94325752976815 kb_relative_information_score 135.9476223351706 kb_relative_information_score 135.9476223351706 kb_relative_information_score 139.95635194597548 kb_relative_information_score 129.93452791896325 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.0032500000000000007 mean_absolute_error 0.0025000000000000005 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.0032500000000000007 mean_absolute_error 0.003000000000000001 mean_absolute_error 0.003000000000000001 mean_absolute_error 0.0025000000000000005 mean_absolute_error 0.003750000000000001 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 0.83125 predictive_accuracy 0.8375 predictive_accuracy 0.875 predictive_accuracy 0.83125 predictive_accuracy 0.83125 predictive_accuracy 0.8375 predictive_accuracy 0.85 predictive_accuracy 0.85 predictive_accuracy 0.875 predictive_accuracy 0.8125 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 0.83125 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,0] recall 0.875 [1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1] recall 0.83125 [0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5] recall 0.83125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1] recall 0.8375 [0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,0.5,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.85 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.875 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1] recall 0.8125 [1,1,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0.5,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1] relative_absolute_error 0.17045454545454522 relative_absolute_error 0.1641414141414139 relative_absolute_error 0.12626262626262608 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.1641414141414139 relative_absolute_error 0.1515151515151513 relative_absolute_error 0.1515151515151513 relative_absolute_error 0.12626262626262608 relative_absolute_error 0.18939393939393911 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 0.058094750193111264 root_mean_squared_error 0.0570087712549569 root_mean_squared_error 0.05 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.0570087712549569 root_mean_squared_error 0.05477225575051662 root_mean_squared_error 0.05477225575051662 root_mean_squared_error 0.05 root_mean_squared_error 0.061237243569579464 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5729597091269403 root_relative_squared_error 0.5025189076296057 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5729597091269403 root_relative_squared_error 0.5504818825631801 root_relative_squared_error 0.5504818825631801 root_relative_squared_error 0.5025189076296057 root_relative_squared_error 0.6154574548966634 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 638.456731000133 usercpu_time_millis 651.5611680000575 usercpu_time_millis 634.927016000006 usercpu_time_millis 642.9227910000463 usercpu_time_millis 660.475910999935 usercpu_time_millis 659.1885289999482 usercpu_time_millis 645.3607160000274 usercpu_time_millis 665.58395200002 usercpu_time_millis 649.9334110000063 usercpu_time_millis 644.3683219999912 usercpu_time_millis_testing 53.784304000032535 usercpu_time_millis_testing 57.93827499996951 usercpu_time_millis_testing 53.06515400002354 usercpu_time_millis_testing 55.38878000004388 usercpu_time_millis_testing 55.78324399994017 usercpu_time_millis_testing 55.75922299999547 usercpu_time_millis_testing 54.635092000012264 usercpu_time_millis_testing 56.01129599995147 usercpu_time_millis_testing 55.62622900004044 usercpu_time_millis_testing 55.120883999961734 usercpu_time_millis_training 584.6724270001005 usercpu_time_millis_training 593.622893000088 usercpu_time_millis_training 581.8618619999825 usercpu_time_millis_training 587.5340110000025 usercpu_time_millis_training 604.6926669999948 usercpu_time_millis_training 603.4293059999527 usercpu_time_millis_training 590.7256240000152 usercpu_time_millis_training 609.5726560000685 usercpu_time_millis_training 594.3071819999659 usercpu_time_millis_training 589.2474380000294