8958515 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) 6894121 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 23.775330431771728 7650 cache_size 200 7650 class_weight null 7650 coef0 0.4785696743411747 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.011959112487787894 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking true 7650 tol 0.0008208781528809752 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 18832294 description https://api.openml.org/data/download/18832294/description.xml -1 18832295 predictions https://api.openml.org/data/download/18832295/predictions.arff area_under_roc_curve 0.9226641414141414 [0.842487,0.96875,1,1,0.96875,0.936553,0.999684,1,0.905934,0.96875,0.967803,0.937184,1,0.874684,1,0.96875,1,0.84154,0.744949,0.621528,0.874053,0.96875,0.998737,1,0.937184,0.684343,0.810606,0.936553,0.9375,1,0.999684,1,0.999369,0.747475,0.937184,0.936869,0.716856,0.716856,0.968119,1,0.935922,0.968434,1,0.936869,0.968434,0.96875,0.937184,0.968119,0.873422,0.936553,0.904672,0.905619,0.937184,0.842487,0.874053,0.841225,1,0.968434,0.903093,0.904987,0.968119,0.968434,0.874053,0.999053,0.999369,0.810922,0.71654,1,0.905619,0.873422,0.905303,0.9375,0.90404,0.96875,0.936869,0.96875,0.968434,0.842172,1,1,0.905934,0.936553,0.874684,0.717487,0.905303,1,1,0.935922,0.9375,1,0.937184,0.999684,0.967803,0.936869,0.96875,0.936869,0.905303,0.905303,0.717803,0.937184] average_cost 0 f_measure 0.8468469414460382 [0.709677,0.967742,1,1,0.967742,0.848485,0.969697,1,0.866667,0.967742,0.882353,0.903226,1,0.827586,1,0.967742,1,0.647059,0.4,0.258065,0.774194,0.967742,0.888889,1,0.903226,0.375,0.625,0.848485,0.933333,1,0.969697,1,0.941176,0.5,0.903226,0.875,0.482759,0.482759,0.909091,1,0.8,0.9375,1,0.875,0.9375,0.967742,0.903226,0.909091,0.727273,0.848485,0.764706,0.83871,0.903226,0.709677,0.774194,0.628571,1,0.9375,0.666667,0.787879,0.909091,0.9375,0.774194,0.914286,0.941176,0.645161,0.466667,1,0.83871,0.727273,0.8125,0.933333,0.722222,0.967742,0.875,0.967742,0.9375,0.6875,1,1,0.866667,0.848485,0.827586,0.518519,0.8125,1,1,0.8,0.933333,1,0.903226,0.969697,0.882353,0.875,0.967742,0.875,0.8125,0.8125,0.538462,0.903226] kappa 0.8453282828282829 kb_relative_information_score 1354.4653113381896 mean_absolute_error 0.0030624999999999897 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 0.8514549189835904 [0.733333,1,1,1,1,0.823529,0.941176,1,0.928571,1,0.833333,0.933333,1,0.923077,1,1,1,0.611111,0.333333,0.266667,0.8,1,0.8,1,0.933333,0.375,0.625,0.823529,1,1,0.941176,1,0.888889,0.5,0.933333,0.875,0.538462,0.538462,0.882353,1,0.736842,0.9375,1,0.875,0.9375,1,0.933333,0.882353,0.705882,0.823529,0.722222,0.866667,0.933333,0.733333,0.8,0.578947,1,0.9375,0.565217,0.764706,0.882353,0.9375,0.8,0.842105,0.888889,0.666667,0.5,1,0.866667,0.705882,0.8125,1,0.65,1,0.875,1,0.9375,0.6875,1,1,0.928571,0.823529,0.923077,0.636364,0.8125,1,1,0.736842,1,1,0.933333,0.941176,0.833333,0.875,1,0.875,0.8125,0.8125,0.7,0.933333] predictive_accuracy 0.846875 prior_entropy 6.6438561897747395 recall 0.846875 [0.6875,0.9375,1,1,0.9375,0.875,1,1,0.8125,0.9375,0.9375,0.875,1,0.75,1,0.9375,1,0.6875,0.5,0.25,0.75,0.9375,1,1,0.875,0.375,0.625,0.875,0.875,1,1,1,1,0.5,0.875,0.875,0.4375,0.4375,0.9375,1,0.875,0.9375,1,0.875,0.9375,0.9375,0.875,0.9375,0.75,0.875,0.8125,0.8125,0.875,0.6875,0.75,0.6875,1,0.9375,0.8125,0.8125,0.9375,0.9375,0.75,1,1,0.625,0.4375,1,0.8125,0.75,0.8125,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.8125,0.875,0.75,0.4375,0.8125,1,1,0.875,0.875,1,0.875,1,0.9375,0.875,0.9375,0.875,0.8125,0.8125,0.4375,0.875] relative_absolute_error 0.15467171717171635 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.05533985905294655 root_relative_squared_error 0.5561865103932607 total_cost 0 area_under_roc_curve 0.9211448133110423 [0.996855,0.75,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.5,1,0.75,0.496835,0.990566,0.5,1,0.996855,1,1,0.743671,0.746835,0.996835,1,1,1,1,0.996835,0.5,1,0.996855,1,0.996855,1,1,0.996855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,1,0.996855,0.996855,1,1,1,1,1,1,0.75,1,1,1,0.5,1,1,0.5,0.75,1,1,1,1,1,0.75,0.5,1,1,1,1,1,0.996855,1,1,1,0.996835,0.75,1,0.996835,1,1,0.996835,1,0.75,0.496855,0.993671,0.496835,1] area_under_roc_curve 0.9147559907650663 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.75,0.746835,0.487421,1,1,0.996855,1,1,0.75,0.493671,1,1,1,1,1,1,0.993671,0.75,0.5,0.496855,0.5,1,1,1,1,1,0.75,1,1,1,1,0.746835,0.996835,0.993671,1,1,0.75,1,0.496855,1,1,0.996855,0.75,1,1,0.75,0.996835,1,0.75,0.75,1,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.75,0.996835,0.996855,0.5,0.746835,1,1,0.996835,0.75,1,1,1,1,0.75,1,1,1,1,0.5,0.496855] area_under_roc_curve 0.9558355226494705 [1,1,1,1,1,0.996835,1,1,1,1,1,0.75,1,1,1,1,1,0.996835,1,0.5,1,1,1,1,1,0.746835,1,0.996855,1,1,1,1,1,0.75,0.996855,1,0.993711,1,1,1,0.746835,0.5,1,1,0.996835,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,0.993711,0.746835,1,1,1,1,1,1,1,1,1,0.75,1,1,1,1,0.996855,1,1,0.996835,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1] area_under_roc_curve 0.9053220285009151 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,0.75,1,0.75,1,1,1,0.743671,0.493711,0.75,1,1,0.996835,1,0.5,0.5,1,1,1,1,1,1,1,0.746835,1,1,1,0.496855,1,1,0.996835,0.996855,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.75,1,0.993671,1,1,0.996855,1,0.996855,1,1,1,1,0.496835,0.490506,1,1,0.743671,0.5,1,0.990566,1,0.996855,1,1,0.75,1,1,1,1,0.75,0.75,0.5,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.996855,0.75] area_under_roc_curve 0.9147161850171164 [0.746835,1,1,1,1,0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.746835,0.987421,0.746835,0.75,1,1,1,1,0.990506,1,1,1,1,1,1,1,0.496835,1,1,0.496835,0.5,1,1,0.746835,1,1,0.5,1,1,1,1,1,1,0.496855,0.496855,0.75,0.996855,0.496835,0.5,1,0.996835,0.993671,1,1,1,0.5,1,1,1,1,1,0.75,0.996835,0.996835,1,1,1,0.75,1,0.996835,0.996835,1,1,1,1,1,0.75,0.996855,1,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,0.5,1] area_under_roc_curve 0.921065201815142 [0.75,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,1,1,1,1,1,0.996855,0.5,0.75,0.75,0.996835,1,0.996835,0.743671,0.746835,0.5,1,1,1,1,1,0.746835,1,0.75,0.75,0.743671,1,1,0.996835,1,1,0.996855,1,1,1,1,0.75,0.75,1,1,1,0.993711,0.996835,0.993671,1,1,0.75,0.996855,1,0.75,0.996855,1,1,0.75,1,1,0.746835,1,1,1,0.996855,1,0.75,1,1,0.75,1,1,0.996855,0.746835,0.75,0.746835,1,1,1,0.996855,1,1,1,1,1,1,1,1,1,1,0.5,1] area_under_roc_curve 0.9273545099912427 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.743671,0.5,0.993671,1,1,1,1,0.5,0.496855,0.75,1,1,0.996835,1,1,0.996855,1,1,0.496835,0.746835,0.993671,1,1,1,1,1,0.5,0.75,0.75,0.996835,0.996855,0.996855,1,1,0.996835,0.5,1,0.75,1,1,0.5,1,0.996835,0.996835,0.996855,0.996835,1,0.496855,0.996855,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9273943157391926 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.984177,0.5,0.75,1,1,1,0.75,0.5,1,1,0.5,1,1,1,0.996855,1,1,1,0.5,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,1,0.746835,1,1,0.996835,0.993711,1,1,1,1,1,0.496855,0.5,1,1,0.746835,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.5,0.75,0.75,1,1,0.996855,1,1,1,1,0.993671,1,1,0.996835,1,1,0.996835,1] area_under_roc_curve 0.9369078894992438 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,1,1,1,1,1,1,1,0.493711,0.75,0.496855,0.996835,1,1,1,1,0.5,0.996855,1,1,1,1,1,1,0.996855,1,1,1,0.5,0.75,1,1,1,1,0.996835,1,1,0.996855,1,0.5,1,0.75,0.996835,1,0.75,0.75,1,1,0.5,0.993671,1,1,1,1,0.996835,1,1,0.743671,1,0.996835,1,0.996855,0.5,0.75,1,1,1,1,0.996855,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1] area_under_roc_curve 0.9022967916567153 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,0.993711,1,1,0.746835,1,1,1,1,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.496855,0.75,0.996835,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,0.75,0.996855,1,1,0.996835,0.75,0.75,1,0.746835,1,0.993711,0.993711,0.496835,1,0.75,0.996855,1,0.5,0.496835,0.75,1,0.75,1,1,1,1,1,0.496855,1,0.496855,0.996835,1,1,0.746835,1,1,1,0.996835,1,0.75,1,1,0.996855,0.5,1,1] 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 0.8420782502270125 kappa 0.8294040990403981 kappa 0.9115533443891652 kappa 0.810493900272415 kappa 0.829397361977727 kappa 0.8420657796027955 kappa 0.854666087437305 kappa 0.8546833043752962 kappa 0.873627675539057 kappa 0.8042156785347754 kb_relative_information_score 134.94543993246936 kb_relative_information_score 132.94107512706694 kb_relative_information_score 145.9694463621828 kb_relative_information_score 129.93452791896325 kb_relative_information_score 132.94107512706694 kb_relative_information_score 134.94543993246936 kb_relative_information_score 136.9498047378718 kb_relative_information_score 136.9498047378718 kb_relative_information_score 139.95635194597548 kb_relative_information_score 128.93234551626202 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.0017499999999999998 mean_absolute_error 0.003750000000000001 mean_absolute_error 0.003375000000000001 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.002875000000000001 mean_absolute_error 0.002875000000000001 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 0.84375 predictive_accuracy 0.83125 predictive_accuracy 0.9125 predictive_accuracy 0.8125 predictive_accuracy 0.83125 predictive_accuracy 0.84375 predictive_accuracy 0.85625 predictive_accuracy 0.85625 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 0.84375 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.83125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0] recall 0.9125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1] recall 0.8125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5] recall 0.83125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1] recall 0.84375 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.85625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.85625 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1] recall 0.80625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0.5,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.1578282828282826 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.08838383838383823 relative_absolute_error 0.18939393939393911 relative_absolute_error 0.17045454545454522 relative_absolute_error 0.1578282828282826 relative_absolute_error 0.14520202020202 relative_absolute_error 0.14520202020202 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 0.05590169943749475 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.04183300132670378 root_mean_squared_error 0.061237243569579464 root_mean_squared_error 0.058094750193111264 root_mean_squared_error 0.05590169943749475 root_mean_squared_error 0.05361902647381805 root_mean_squared_error 0.05361902647381805 root_mean_squared_error 0.05 root_mean_squared_error 0.06224949798994367 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.4204374825912606 root_relative_squared_error 0.6154574548966634 root_relative_squared_error 0.5838742081211419 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5388914922357191 root_relative_squared_error 0.5388914922357191 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 586.4865089999967 usercpu_time_millis 583.559169000182 usercpu_time_millis 575.6807370000843 usercpu_time_millis 582.2157919999427 usercpu_time_millis 588.3162549998815 usercpu_time_millis 613.1356100001994 usercpu_time_millis 580.2620610002123 usercpu_time_millis 569.6479150001323 usercpu_time_millis 575.3605959998822 usercpu_time_millis 569.4337940001333 usercpu_time_millis_testing 58.12841500005561 usercpu_time_millis_testing 55.81786700008706 usercpu_time_millis_testing 56.394404000002396 usercpu_time_millis_testing 55.816458999970564 usercpu_time_millis_testing 55.850974999884784 usercpu_time_millis_testing 54.38182400007463 usercpu_time_millis_testing 54.76869200015244 usercpu_time_millis_testing 55.00793100009105 usercpu_time_millis_testing 55.16264199991383 usercpu_time_millis_testing 54.600353000068935 usercpu_time_millis_training 528.358093999941 usercpu_time_millis_training 527.741302000095 usercpu_time_millis_training 519.2863330000819 usercpu_time_millis_training 526.3993329999721 usercpu_time_millis_training 532.4652799999967 usercpu_time_millis_training 558.7537860001248 usercpu_time_millis_training 525.4933690000598 usercpu_time_millis_training 514.6399840000413 usercpu_time_millis_training 520.1979539999684 usercpu_time_millis_training 514.8334410000643