8958780 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) 6894384 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 2.5343496481925443 7650 cache_size 200 7650 class_weight null 7650 coef0 0.31708077888603037 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.0015946483356092196 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.000185491116598834 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 18832822 description https://api.openml.org/data/download/18832822/description.xml -1 18832823 predictions https://api.openml.org/data/download/18832823/predictions.arff area_under_roc_curve 0.8686868686868686 [0.747159,0.937184,1,1,0.9375,0.718434,0.999684,1,0.93529,0.96875,0.874684,0.998737,0.778725,0.780619,1,0.96875,1,0.587121,0.618687,0.559659,0.780619,0.96875,0.746528,1,0.843119,0.683712,0.590593,0.998422,0.968434,0.999053,0.999053,1,0.936237,0.713384,0.780934,0.715278,0.620581,0.588068,0.967487,0.999684,0.873422,0.968119,1,0.998422,0.905934,0.968119,0.874053,0.905303,0.968119,0.842803,0.780619,0.904987,0.874684,0.874053,0.873106,0.589331,1,0.968434,0.685922,0.748422,0.935606,0.936869,0.873106,0.968119,0.936869,0.716856,0.587753,1,0.936869,0.748737,0.779356,0.843434,0.809028,0.9375,0.780619,0.968434,0.968434,0.684343,0.96875,0.999684,0.75,0.936869,0.904987,0.839962,0.966856,0.937184,0.96875,0.905934,0.843119,0.999684,0.686553,0.968434,0.936553,0.937184,0.96875,0.905303,0.684343,0.997475,0.561869,0.873737] average_cost 0 f_measure 0.7408910064271739 [0.484848,0.903226,1,1,0.933333,0.583333,0.969697,1,0.756757,0.967742,0.827586,0.888889,0.545455,0.666667,1,0.967742,1,0.15,0.2,0.148148,0.666667,0.967742,0.457143,1,0.758621,0.352941,0.206897,0.864865,0.9375,0.914286,0.914286,1,0.823529,0.35,0.692308,0.411765,0.235294,0.162162,0.857143,0.969697,0.727273,0.909091,1,0.864865,0.866667,0.909091,0.774194,0.8125,0.909091,0.733333,0.666667,0.787879,0.827586,0.774194,0.705882,0.181818,1,0.9375,0.444444,0.551724,0.777778,0.875,0.705882,0.909091,0.875,0.482759,0.157895,1,0.875,0.571429,0.580645,0.785714,0.540541,0.933333,0.666667,0.9375,0.9375,0.375,0.967742,0.969697,0.666667,0.875,0.787879,0.564103,0.810811,0.903226,0.967742,0.866667,0.758621,0.969697,0.48,0.9375,0.848485,0.903226,0.967742,0.8125,0.375,0.8,0.2,0.75] kappa 0.7373737373737373 kb_relative_information_score 1183.0921204762903 mean_absolute_error 0.005199999999999944 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 0.7577157225803914 [0.470588,0.933333,1,1,1,0.875,0.941176,1,0.666667,1,0.923077,0.8,0.529412,0.818182,1,1,1,0.125,0.166667,0.181818,0.818182,1,0.421053,1,0.846154,0.333333,0.230769,0.761905,0.9375,0.842105,0.842105,1,0.777778,0.291667,0.9,0.388889,0.222222,0.142857,0.789474,0.941176,0.705882,0.882353,1,0.761905,0.928571,0.882353,0.8,0.8125,0.882353,0.785714,0.818182,0.764706,0.923077,0.8,0.666667,0.176471,1,0.9375,0.545455,0.615385,0.7,0.875,0.666667,0.882353,0.875,0.538462,0.136364,1,0.875,0.666667,0.6,0.916667,0.47619,1,0.818182,0.9375,0.9375,0.375,1,0.941176,1,0.875,0.764706,0.478261,0.714286,0.933333,1,0.928571,0.846154,0.941176,0.666667,0.9375,0.823529,0.933333,1,0.8125,0.375,0.666667,0.5,0.75] predictive_accuracy 0.74 prior_entropy 6.6438561897747395 recall 0.74 [0.5,0.875,1,1,0.875,0.4375,1,1,0.875,0.9375,0.75,1,0.5625,0.5625,1,0.9375,1,0.1875,0.25,0.125,0.5625,0.9375,0.5,1,0.6875,0.375,0.1875,1,0.9375,1,1,1,0.875,0.4375,0.5625,0.4375,0.25,0.1875,0.9375,1,0.75,0.9375,1,1,0.8125,0.9375,0.75,0.8125,0.9375,0.6875,0.5625,0.8125,0.75,0.75,0.75,0.1875,1,0.9375,0.375,0.5,0.875,0.875,0.75,0.9375,0.875,0.4375,0.1875,1,0.875,0.5,0.5625,0.6875,0.625,0.875,0.5625,0.9375,0.9375,0.375,0.9375,1,0.5,0.875,0.8125,0.6875,0.9375,0.875,0.9375,0.8125,0.6875,1,0.375,0.9375,0.875,0.875,0.9375,0.8125,0.375,1,0.125,0.75] relative_absolute_error 0.2626262626262594 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.0721110255092794 root_relative_squared_error 0.7247430753394742 total_cost 0 area_under_roc_curve 0.8488177692858849 [0.490566,0.75,1,1,0.75,1,1,1,1,1,0.75,0.996835,0.75,0.5,1,0.5,1,0.5,0.5,0.984277,0.496855,1,0.987421,1,0.5,0.5,0.5,0.996835,1,0.996855,1,1,0.496835,0.5,0.75,0.990566,0.996855,0.990566,1,1,0.996855,0.996855,1,1,1,0.996835,1,0.993711,1,0.75,1,1,1,1,0.996855,0.484277,1,1,0.5,1,1,0.996855,0.75,1,1,0.5,0.5,1,1,0.5,0.746835,1,1,0.75,0.496855,0.996835,0.75,0.5,1,1,0.75,0.996835,1,0.996855,1,0.75,0.75,1,0.5,1,0.75,1,1,0.996835,1,0.746835,0.493711,0.993671,0.496835,1] area_under_roc_curve 0.8929026351405144 [1,1,1,1,1,1,0.996835,1,1,1,0.75,1,0.5,0.75,1,1,1,0.5,0.5,0.990566,1,1,0.993711,1,1,0.5,0.496835,1,1,0.996855,1,1,1,0.5,0.75,0.990566,0.996855,0.990566,1,1,1,1,1,0.996835,0.75,1,0.996855,1,1,1,1,0.75,0.996855,1,1,0.487421,1,1,1,0.75,0.996855,0.996855,1,1,1,0.5,0.5,1,1,1,0.743671,1,1,1,1,1,1,0.990506,1,1,0.5,1,0.993711,1,1,1,1,1,0.5,1,0.75,1,0.75,0.75,1,1,0.993711,0.996835,0.5,0.5] area_under_roc_curve 0.8771395589523125 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[0.746835,1,1,1,1,0.5,1,1,0.996855,1,1,1,0.993711,0.496855,1,1,1,0.5,0.968553,0.5,0.5,1,0.75,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,0.996835,0.746835,1,1,0.496835,0.5,1,1,0.996835,1,1,1,1,0.996855,1,1,1,0.5,0.5,0.496855,0.75,0.996855,0.743671,0.5,1,0.996835,0.5,0.993711,1,1,0.996855,1,0.75,1,0.481132,1,0.75,0.75,0.75,0.75,0.996855,1,0.75,1,0.996835,0.5,1,1,0.5,1,0.75,0.993671,0.996855,1,1,1,1,1,1,0.75,0.996855,1,0.75,1,0.5,0.996855,0.5,1] area_under_roc_curve 0.8770400445824376 [0.75,0.996855,1,1,1,0.5,1,1,0.996855,0.75,0.75,0.996835,0.993711,0.996855,1,1,1,0.5,0.984277,0.5,0.5,0.75,0.75,1,0.746835,0.990506,0.75,1,1,1,1,1,0.996835,0.996835,1,0.75,0.5,0.5,1,1,0.996835,1,1,0.996855,1,1,1,0.75,1,0.75,1,0.996855,0.75,1,0.993671,1,1,1,0.5,1,0.993671,1,0.993711,1,1,0.5,0.984277,1,1,0.75,0.75,0.75,0.996855,1,0.75,1,1,0.496835,1,1,0.5,0.75,1,0.993671,1,1,1,1,0.996835,1,0.493711,1,1,1,1,1,0.5,0.996855,0.5,1] area_under_roc_curve 0.8738754876204124 [0.996835,1,1,1,1,0.5,1,1,0.993711,1,0.996855,0.996855,1,1,1,1,1,0.987421,0.5,0.5,0.996835,1,0.496835,1,0.75,0.496855,0.490566,1,1,1,0.996835,1,1,0.987421,0.75,0.5,0.493671,0.5,0.990506,1,1,0.75,1,1,0.5,0.75,0.5,0.746835,1,1,1,0.996835,1,1,0.746835,0.5,1,1,0.5,1,0.996835,1,0.996855,0.996835,1,0.996855,0.990566,1,1,0.75,0.996855,1,0.75,1,0.75,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,0.5,1,0.996855,1,0.746835,1,1,0.75,1,1,0.5,0.746835] area_under_roc_curve 0.8646206512220364 [0.75,1,1,1,1,0.75,1,1,0.996855,1,1,1,0.996835,1,1,1,1,0.977987,0.5,0.5,0.75,1,0.75,1,0.75,0.990566,0.493711,0.996835,0.5,0.996835,1,1,1,0.987421,0.75,0.5,0.5,0.5,1,0.996855,0.5,1,1,1,0.5,1,0.996835,1,0.993711,0.5,0.496855,0.75,0.75,0.996855,1,0.5,1,1,1,0.993711,1,1,1,1,1,0.493711,0.984277,1,1,0.746835,1,1,0.5,1,0.746835,1,1,0.490566,1,1,0.5,1,0.75,1,0.746835,0.75,1,0.496855,1,1,0.5,1,1,1,1,1,0.75,1,0.496835,1] area_under_roc_curve 0.8677852081840618 [0.496855,1,1,1,1,0.996855,1,1,0.75,1,1,0.996855,0.5,0.75,1,1,1,0.987421,0.5,0.496855,1,1,0.493711,1,1,0.490566,0.987421,0.996835,1,1,1,1,0.996855,0.987421,1,0.5,0.5,0.5,0.75,1,0.5,1,1,0.996835,1,1,0.996855,0.75,1,0.993711,0.75,0.996835,0.75,0.75,0.5,0.5,1,0.5,0.5,0.5,0.75,0.75,1,0.996835,1,1,0.5,1,0.996835,0.996855,1,0.5,0.75,1,0.75,1,1,0.993711,1,1,1,1,1,0.990566,1,1,1,1,0.996855,1,0.5,1,1,1,1,0.746835,0.990566,0.996835,0.75,0.5] area_under_roc_curve 0.8677454024361116 [1,1,1,1,1,0.5,1,1,0.996835,1,1,1,0.5,0.75,1,1,1,0.481132,0.5,0.5,1,1,1,1,1,0.496855,0.5,1,1,1,1,1,1,0.990566,0.5,0.5,0.5,0.5,1,1,0.993711,1,1,1,1,1,1,1,1,0.996855,0.75,1,1,0.746835,1,0.984277,1,1,0.746835,0.5,0.75,0.75,0.496835,1,0.993711,0.993711,0.5,1,0.75,0.996855,0.996855,0.5,0.493671,0.75,0.75,0.75,1,1,1,1,1,0.496855,1,0.490566,0.996835,0.996835,1,0.75,1,1,0.75,0.996835,1,0.75,1,1,0.990566,1,0.75,0.993711] 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 0.6970055627884957 kappa 0.785345065698615 kappa 0.7538073068728793 kappa 0.7159763313609467 kappa 0.722244141087351 kappa 0.7537490134175217 kappa 0.7474149498776541 kappa 0.7285567742444566 kappa 0.7348694074015625 kappa 0.7348589465377787 kb_relative_information_score 111.8952446703412 kb_relative_information_score 125.92579830815838 kb_relative_information_score 120.91488629465225 kb_relative_information_score 114.90179187844495 kb_relative_information_score 115.90397428114613 kb_relative_information_score 120.91488629465222 kb_relative_information_score 119.91270389195101 kb_relative_information_score 116.90615668384734 kb_relative_information_score 117.90833908654861 kb_relative_information_score 117.90833908654857 mean_absolute_error 0.006000000000000004 mean_absolute_error 0.004250000000000002 mean_absolute_error 0.004875000000000003 mean_absolute_error 0.005625000000000003 mean_absolute_error 0.005500000000000003 mean_absolute_error 0.004875000000000003 mean_absolute_error 0.005000000000000003 mean_absolute_error 0.005375000000000003 mean_absolute_error 0.005250000000000003 mean_absolute_error 0.005250000000000003 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 0.7 predictive_accuracy 0.7875 predictive_accuracy 0.75625 predictive_accuracy 0.71875 predictive_accuracy 0.725 predictive_accuracy 0.75625 predictive_accuracy 0.75 predictive_accuracy 0.73125 predictive_accuracy 0.7375 predictive_accuracy 0.7375 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 0.7 [0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0,1,0,1,0,0,1,0,1,1,1,0,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,0,1,1,1,0.5,1,1,0,0,1,1,0,0.5,1,1,0.5,0,1,0.5,0,1,1,0.5,1,1,1,1,0.5,0.5,1,0,1,0.5,1,1,1,1,0.5,0,1,0,1] recall 0.7875 [1,1,1,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0,0,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,0,0] recall 0.75625 [0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,0,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0.5,1,0,1,1,1,0,1,1,0.5,0,1,1,0,1,1,0,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1] recall 0.71875 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,0.5,0,0,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0,0.5] recall 0.725 [0.5,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,0.5,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0.5,1,0.5,0,1,1,0,1,1,1,1,1,0.5,1,0,1,0.5,0.5,0.5,0.5,1,1,0.5,1,1,0,1,1,0,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0,1,0,1] recall 0.75625 [0.5,1,1,1,1,0,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,0,0,0.5,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0.5,0.5,0.5,1,1,0.5,1,1,0,1,1,0,0.5,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1] recall 0.75 [1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0.5,0,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,0.5,1,1,0,0.5,0,0.5,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,1,1,0.5,1,1,0.5,1,1,0,0.5] recall 0.73125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5,1,0.5,1,0.5,1,0,1,0,1,1,1,1,1,0.5,0,0,0,1,1,0,1,1,1,0,1,1,1,1,0,0,0.5,0.5,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,0,1,0.5,1,1,0,1,1,0,1,0.5,1,0.5,0.5,1,0,1,1,0,1,1,1,1,1,0.5,1,0,1] recall 0.7375 [0,1,1,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0.5,1,0,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,0.5,0,0,1,0,0,0,0.5,0.5,1,1,1,1,0,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,0] recall 0.7375 [1,1,1,1,1,0,1,1,1,1,1,1,0,0.5,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,0,0.5,0.5,0,1,1,1,0,1,0.5,1,1,0,0,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1] relative_absolute_error 0.3030303030303027 relative_absolute_error 0.2146464646464644 relative_absolute_error 0.24621212121212094 relative_absolute_error 0.2840909090909088 relative_absolute_error 0.27777777777777746 relative_absolute_error 0.24621212121212094 relative_absolute_error 0.2525252525252522 relative_absolute_error 0.2714646464646462 relative_absolute_error 0.26515151515151486 relative_absolute_error 0.26515151515151486 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 0.07745966692414837 root_mean_squared_error 0.06519202405202651 root_mean_squared_error 0.06982120021884472 root_mean_squared_error 0.07500000000000002 root_mean_squared_error 0.07416198487095665 root_mean_squared_error 0.06982120021884472 root_mean_squared_error 0.07071067811865477 root_mean_squared_error 0.07331439149307592 root_mean_squared_error 0.07245688373094722 root_mean_squared_error 0.07245688373094722 root_relative_squared_error 0.7784989441615228 root_relative_squared_error 0.6552044942557468 root_relative_squared_error 0.7017294652672368 root_relative_squared_error 0.7537783614444089 root_relative_squared_error 0.7453559924999297 root_relative_squared_error 0.7017294652672368 root_relative_squared_error 0.7106690545187011 root_relative_squared_error 0.7368373585325954 root_relative_squared_error 0.7282190812544189 root_relative_squared_error 0.7282190812544189 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 473.27386300003127 usercpu_time_millis 471.35919700008344 usercpu_time_millis 477.7904570000828 usercpu_time_millis 474.5512619999772 usercpu_time_millis 485.5129610000404 usercpu_time_millis 469.55574100002195 usercpu_time_millis 486.3180659999671 usercpu_time_millis 475.9406589998889 usercpu_time_millis 468.8606529998651 usercpu_time_millis 462.1308240000417 usercpu_time_millis_testing 55.43266299991956 usercpu_time_millis_testing 55.865190000076836 usercpu_time_millis_testing 55.642792000071495 usercpu_time_millis_testing 55.984289999969405 usercpu_time_millis_testing 55.245560000003024 usercpu_time_millis_testing 54.88343000001805 usercpu_time_millis_testing 53.58770099996946 usercpu_time_millis_testing 54.15766799978883 usercpu_time_millis_testing 54.59023699995669 usercpu_time_millis_testing 54.41973100005271 usercpu_time_millis_training 417.8412000001117 usercpu_time_millis_training 415.4940070000066 usercpu_time_millis_training 422.14766500001133 usercpu_time_millis_training 418.5669720000078 usercpu_time_millis_training 430.26740100003735 usercpu_time_millis_training 414.6723110000039 usercpu_time_millis_training 432.7303649999976 usercpu_time_millis_training 421.7829910001001 usercpu_time_millis_training 414.27041599990844 usercpu_time_millis_training 407.711092999989