8958286 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) 6893893 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 1.4748151400207605 7650 cache_size 200 7650 class_weight null 7650 coef0 0.2780267065952804 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.0009796002202444975 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking true 7650 tol 0.0001294514222799584 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 18831840 description https://api.openml.org/data/download/18831840/description.xml -1 18831841 predictions https://api.openml.org/data/download/18831841/predictions.arff area_under_roc_curve 0.6900252525252525 [0.554293,0.651199,0.999684,1,0.748106,0.716225,0.874684,0.998737,0.685606,0.96875,0.779672,0.716856,0.619949,0.624369,0.96875,0.655303,0.65625,0.585543,0.612374,0.557134,0.560922,0.905934,0.589015,1,0.592803,0.528725,0.525253,0.684659,0.68529,0.778409,0.623422,0.999053,0.623106,0.619634,0.618056,0.714646,0.620896,0.586174,0.872159,0.874053,0.589015,0.684028,0.842803,0.715593,0.78125,0.621528,0.809975,0.62279,0.650253,0.587753,0.652462,0.590278,0.621843,0.62279,0.651515,0.525568,1,0.653725,0.651199,0.621528,0.651831,0.592172,0.618056,0.715909,0.621843,0.589015,0.584912,1,0.623106,0.589015,0.623422,0.654356,0.620265,0.71875,0.559659,0.685606,0.74779,0.589331,0.873737,0.873737,0.529672,0.623422,0.683396,0.653725,0.653725,0.621843,0.9375,0.556503,0.623737,0.589646,0.589962,0.967487,0.684975,0.619318,0.619949,0.654987,0.614583,0.71654,0.49779,0.559659] average_cost 0 f_measure 0.39521540213535117 [0.090909,0.27027,0.969697,1,0.533333,0.451613,0.827586,0.888889,0.428571,0.967742,0.6,0.482759,0.222222,0.363636,0.967742,0.416667,0.47619,0.133333,0.133333,0.114286,0.173913,0.866667,0.176471,1,0.272727,0.08,0.055556,0.387097,0.413793,0.529412,0.32,0.914286,0.307692,0.216216,0.190476,0.388889,0.242424,0.139535,0.648649,0.774194,0.176471,0.363636,0.733333,0.424242,0.72,0.258065,0.588235,0.296296,0.25,0.157895,0.30303,0.2,0.266667,0.296296,0.277778,0.057143,1,0.344828,0.27027,0.258065,0.285714,0.25,0.190476,0.4375,0.266667,0.176471,0.12766,1,0.307692,0.176471,0.32,0.37037,0.228571,0.608696,0.148148,0.428571,0.516129,0.181818,0.75,0.75,0.090909,0.32,0.342857,0.344828,0.344828,0.266667,0.933333,0.108108,0.333333,0.1875,0.193548,0.857143,0.4,0.210526,0.222222,0.4,0.150943,0.466667,0,0.148148] kappa 0.380050505050505 kb_relative_information_score 615.8568805474029 mean_absolute_error 0.012274999999999793 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 0.4284058444336376 [0.071429,0.238095,0.941176,1,0.571429,0.466667,0.923077,0.8,0.5,1,0.642857,0.538462,0.2,0.666667,1,0.625,1,0.103448,0.090909,0.105263,0.285714,0.928571,0.166667,1,0.5,0.111111,0.05,0.4,0.461538,0.5,0.444444,0.842105,0.4,0.190476,0.153846,0.35,0.235294,0.111111,0.571429,0.8,0.166667,0.352941,0.785714,0.411765,1,0.266667,0.555556,0.363636,0.208333,0.136364,0.294118,0.214286,0.285714,0.363636,0.25,0.052632,1,0.384615,0.238095,0.266667,0.263158,0.375,0.153846,0.4375,0.285714,0.166667,0.096774,1,0.4,0.166667,0.444444,0.454545,0.210526,1,0.181818,0.5,0.533333,0.176471,0.75,0.75,0.166667,0.444444,0.315789,0.384615,0.384615,0.285714,1,0.095238,0.5,0.1875,0.2,0.789474,0.428571,0.181818,0.2,0.555556,0.108108,0.5,0,0.181818] predictive_accuracy 0.38625 prior_entropy 6.6438561897747395 recall 0.38625 [0.125,0.3125,1,1,0.5,0.4375,0.75,1,0.375,0.9375,0.5625,0.4375,0.25,0.25,0.9375,0.3125,0.3125,0.1875,0.25,0.125,0.125,0.8125,0.1875,1,0.1875,0.0625,0.0625,0.375,0.375,0.5625,0.25,1,0.25,0.25,0.25,0.4375,0.25,0.1875,0.75,0.75,0.1875,0.375,0.6875,0.4375,0.5625,0.25,0.625,0.25,0.3125,0.1875,0.3125,0.1875,0.25,0.25,0.3125,0.0625,1,0.3125,0.3125,0.25,0.3125,0.1875,0.25,0.4375,0.25,0.1875,0.1875,1,0.25,0.1875,0.25,0.3125,0.25,0.4375,0.125,0.375,0.5,0.1875,0.75,0.75,0.0625,0.25,0.375,0.3125,0.3125,0.25,0.875,0.125,0.25,0.1875,0.1875,0.9375,0.375,0.25,0.25,0.3125,0.25,0.4375,0,0.125] relative_absolute_error 0.6199494949494834 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.11079259903080076 root_relative_squared_error 1.113507516768058 total_cost 0 area_under_roc_curve 0.6854947854470183 [0.471698,0.5,1,1,0.75,0.993711,1,0.996855,0.5,1,0.75,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.974843,0.496855,1,0.977987,1,0.496855,0.5,0.5,0.75,0.5,0.490566,0.5,1,0.5,0.5,0.5,0.987421,0.996855,0.987421,1,0.75,0.984277,0.990566,1,0.996835,0.75,0.5,0.996855,0.996855,0.75,0.5,0.75,0.5,0.993711,0.5,0.993711,0.484277,1,0.996855,0.996855,0.5,0.996855,0.990566,0.5,0.5,0.990566,0.5,0.5,1,0.990566,0.487421,0.5,0.993711,0.5,0.75,0.487421,0.5,0.5,0.5,1,1,0.5,0.5,0.993711,0.996855,0.5,0.5,0.75,0.5,0.5,0.987421,0.5,1,0.5,0.5,0.5,0.5,0.977987,0.746835,0.5,0.993711] area_under_roc_curve 0.7011981530132947 [0.977987,0.5,1,1,0.75,0.993711,0.75,0.996855,0.5,1,0.5,0.75,0.5,0.5,1,0.996855,0.75,0.5,0.5,0.977987,1,0.5,0.987421,1,0.996855,0.5,0.5,0.75,1,0.993711,0.5,0.996835,0.5,0.5,0.5,0.990566,0.996855,0.984277,0.996855,0.75,0.984277,0.990566,1,0.5,0.75,0.5,0.996855,0.990566,0.5,0.5,1,0.496835,0.981132,0.5,0.996855,0.481132,1,0.981132,0.987421,0.5,0.990566,0.996855,0.5,0.75,0.993711,0.5,0.5,1,0.5,0.990566,0.5,1,0.5,0.75,0.496855,0.496835,0.5,0.5,1,1,0.5,0.5,0.993711,1,0.75,0.5,1,0.5,0.5,0.993711,0.5,1,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.490566] area_under_roc_curve 0.6917243850011939 [0.5,0.5,0.996835,1,0.5,1,1,1,1,1,0.75,0.5,0.981132,0.75,0.75,0.5,0.5,0.5,0.993711,0.5,0.996855,0.5,0.5,1,1,0.5,0.5,0.990566,0.5,0.75,1,1,0.5,0.5,0.984277,0.993711,0.974843,0.981132,0.990566,0.75,0.5,0.996855,1,0.984277,0.75,0.984277,0.5,0.993711,0.5,0.5,0.5,0.996855,1,0.5,0.977987,0.5,1,0.5,0.987421,0.5,0.990566,0.496855,0.5,0.487421,0.496835,0.5,0.5,1,0.993711,0.496835,0.5,0.996835,0.971698,0.75,0.993711,0.5,0.5,0.5,0.75,0.996835,0.496855,0.75,0.5,0.5,0.993711,0.987421,1,0.5,0.5,0.490566,0.5,1,0.996855,0.5,0.5,1,0.5,0.75,0.5,0.5] area_under_roc_curve 0.6886195366610937 [0.5,0.5,1,1,0.75,0.5,1,1,0.743671,1,1,0.5,0.984277,0.5,1,0.5,0.5,0.5,0.987421,0.5,0.490566,0.996855,0.5,1,0.496855,0.5,0.5,0.990566,0.5,0.75,0.996855,0.996835,0.5,0.5,0.984277,0.987421,0.990566,0.471698,0.993711,0.75,0.5,0.987421,0.993711,0.993711,1,0.990566,0.5,0.996855,0.5,0.5,0.5,0.993711,0.993711,0.5,0.987421,0.5,1,0.5,0.977987,0.5,0.981132,1,0.5,0.996855,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.75,0.990566,0.5,0.993711,0.5,0.5,0.5,1,1,0.996855,0.5,0.5,0.5,0.987421,0.993711,1,0.5,0.5,0.987421,0.5,1,0.996855,0.5,0.5,0.996855,0.5,0.5,0.493711,0.5] area_under_roc_curve 0.6979937903033192 [0.5,0.990566,1,1,0.993711,0.5,1,0.996835,0.496855,1,0.75,1,0.993711,0.496855,1,0.5,0.5,0.5,0.943396,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.996855,0.996855,0.5,0.993711,1,0.5,0.5,0.990566,1,0.5,0.5,1,0.996835,0.5,0.5,1,0.996855,1,0.996855,1,0.5,0.5,0.5,0.496855,0.490566,0.5,0.996855,0.75,0.5,1,0.5,0.5,0.993711,0.75,0.5,0.977987,0.996855,0.5,0.5,0.468553,1,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,1,0.993671,0.5,0.5,0.993711,0.493711,0.5,0.5,0.75,0.996855,0.990566,1,0.984277,0.75,0.5,0.993711,0.746835,0.987421,0.996855,0.496835,0.993711,0.5,0.993711,0.493711,0.5] area_under_roc_curve 0.70121805588727 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[0.5,0.981132,1,1,0.996855,0.5,0.5,1,0.993711,1,0.996855,0.993711,0.5,1,1,1,1,0.974843,0.5,0.5,0.5,1,0.5,1,0.5,0.496855,0.481132,0.5,0.993711,1,0.5,1,0.996855,0.981132,0.5,0.5,0.5,0.5,0.990506,0.996855,0.5,0.75,1,0.5,0.5,0.5,0.5,0.5,0.987421,0.993711,0.484277,0.5,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.987421,0.496835,0.5,0.987421,0.5,0.5,0.990566,0.990566,1,0.5,0.5,0.996855,0.5,0.5,1,0.5,0.993711,0.993711,0.990566,1,1,0.5,0.996855,0.996835,0.496835,0.5,0.5,1,0.484277,0.496855,0.5,0.990566,1,0.496835,0.984277,0.990566,0.5,0.5,1,0.5,0.5] area_under_roc_curve 0.682330228484993 [0.5,0.981132,1,1,0.996855,0.75,0.75,1,0.996855,1,1,0.996855,0.5,0.5,1,0.5,1,0.977987,0.5,0.5,0.5,1,0.5,1,0.5,0.990566,0.484277,0.5,0.490566,0.75,0.5,1,0.996855,0.987421,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.496835,0.5,0.5,0.5,0.996835,0.5,0.990566,0.481132,0.481132,0.5,0.5,0.993711,0.5,0.5,1,0.5,0.75,0.987421,0.5,0.5,0.987421,0.75,0.5,0.474843,0.984277,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.993711,0.996855,0.481132,1,1,0.5,0.996855,0.5,0.5,0.5,0.5,1,0.481132,1,0.5,0.496855,0.996835,1,0.977987,0.990566,0.75,0.5,1,0.5,0.5] area_under_roc_curve 0.6886394395350685 [0.468553,0.75,1,1,0.5,0.993711,0.996835,1,0.5,1,0.993711,0.990566,0.5,0.75,1,1,1,0.987421,0.5,0.496855,0.5,1,0.493711,1,0.75,0.490566,0.984277,0.5,0.75,0.996855,0.5,1,0.990566,0.987421,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.996855,0.5,0.977987,0.974843,0.5,0.5,0.5,0.5,0.5,0.493711,1,0.996855,0.5,0.5,0.5,0.5,0.5,0.75,1,0.993711,0.5,1,0.75,0.993711,0.993711,0.493711,0.5,0.75,0.5,0.75,1,0.990566,0.993711,0.5,0.5,1,0.990566,0.990566,0.5,0.5,1,0.5,0.993711,0.5,0.5,1,0.5,0.5,0.977987,0.5,0.971698,0.746835,0.5,0.496855] area_under_roc_curve 0.6791855743969426 [1,0.5,1,1,0.75,0.993711,1,0.996855,0.5,1,0.993711,1,0.5,0.5,1,0.993711,1,0.477987,0.5,0.496855,0.5,1,0.993711,1,0.5,0.496855,0.490566,0.5,0.5,0.990566,0.5,0.996835,0.996855,0.990566,0.5,0.5,0.5,0.5,0.5,1,0.984277,0.75,0.75,0.75,0.5,0.5,0.987421,0.5,0.984277,0.990566,0.75,0.5,0.5,0.5,0.5,0.984277,1,1,0.5,0.5,0.5,0.5,0.5,0.75,0.987421,0.993711,0.5,1,0.5,0.984277,0.993711,0.496855,0.5,0.75,0.5,0.746835,0.993711,0.993711,0.993711,0.5,0.5,0.490566,0.984277,0.490566,0.5,0.5,0.75,0.5,0.996855,0.5,0.5,0.996835,0.5,0.5,0.993711,0.5,0.962264,0.5,0.5,0.990566] 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 0.37032664305391577 kappa 0.40173967804148464 kappa 0.38284724682174204 kappa 0.37667243821816465 kappa 0.39532320289740963 kappa 0.4018338514816418 kappa 0.3890725869941742 kappa 0.36395481560199944 kappa 0.37659884292967055 kappa 0.3577837242247757 kb_relative_information_score 59.78175972987758 kb_relative_information_score 64.79267174338369 kb_relative_information_score 61.78612453528003 kb_relative_information_score 60.783942132578815 kb_relative_information_score 63.79048934068249 kb_relative_information_score 64.79267174338369 kb_relative_information_score 62.78830693798123 kb_relative_information_score 58.77957732717637 kb_relative_information_score 60.78394213257882 kb_relative_information_score 57.77739492447517 mean_absolute_error 0.012500000000000008 mean_absolute_error 0.011875000000000007 mean_absolute_error 0.012250000000000007 mean_absolute_error 0.012375000000000008 mean_absolute_error 0.012000000000000007 mean_absolute_error 0.011875000000000007 mean_absolute_error 0.012125000000000007 mean_absolute_error 0.012625000000000008 mean_absolute_error 0.012375000000000008 mean_absolute_error 0.012750000000000008 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 0.375 predictive_accuracy 0.40625 predictive_accuracy 0.3875 predictive_accuracy 0.38125 predictive_accuracy 0.4 predictive_accuracy 0.40625 predictive_accuracy 0.39375 predictive_accuracy 0.36875 predictive_accuracy 0.38125 predictive_accuracy 0.3625 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 0.375 [0,0,1,1,0.5,1,1,1,0,1,0.5,0,0,0,1,0,0,0,0,1,0,1,1,1,0,0,0,0.5,0,0,0,1,0,0,0,1,1,1,1,0.5,1,1,1,1,0.5,0,1,1,0.5,0,0.5,0,1,0,1,0,1,1,1,0,1,1,0,0,1,0,0,1,1,0,0,1,0,0.5,0,0,0,0,1,1,0,0,1,1,0,0,0.5,0,0,1,0,1,0,0,0,0,1,0.5,0,1] recall 0.40625 [1,0,1,1,0.5,1,0.5,1,0,1,0,0.5,0,0,1,1,0.5,0,0,1,1,0,1,1,1,0,0,0.5,1,1,0,1,0,0,0,1,1,1,1,0.5,1,1,1,0,0.5,0,1,1,0,0,1,0,1,0,1,0,1,1,1,0,1,1,0,0.5,1,0,0,1,0,1,0,1,0,0.5,0,0,0,0,1,1,0,0,1,1,0.5,0,1,0,0,1,0,1,0,0,0,0,1,0,0,0] recall 0.3875 [0,0,1,1,0,1,1,1,1,1,0.5,0,1,0.5,0.5,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0.5,1,1,0,0,1,1,1,1,1,0.5,0,1,1,1,0.5,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,0,0,0,0,0,0,1,1,0,0,1,1,0.5,1,0,0,0,0.5,1,0,0.5,0,0,1,1,1,0,0,0,0,1,1,0,0,1,0,0.5,0,0] recall 0.38125 [0,0,1,1,0.5,0,1,1,0.5,1,1,0,1,0,1,0,0,0,1,0,0,1,0,1,0,0,0,1,0,0.5,1,1,0,0,1,1,1,0,1,0.5,0,1,1,1,1,1,0,1,0,0,0,1,1,0,1,0,1,0,1,0,1,1,0,1,0,0,0,1,1,0,0,0.5,1,0,1,0,0,0,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,0,0,1,0,0,0,0] recall 0.4 [0,1,1,1,1,0,1,1,0,1,0.5,1,1,0,1,0,0,0,1,0,0,1,0,1,0,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0.5,0,1,0,0,1,0.5,0,1,1,0,0,0,1,0,0,0,0,1,0,0,1,1,0,0,1,0,0,0,0.5,1,1,1,1,0.5,0,1,0.5,1,1,0,1,0,1,0,0] recall 0.40625 [0,1,1,1,1,0,1,1,1,0.5,0,0,1,1,1,0,0,0,1,0,0,0.5,0,1,0,0,0,1,1,0.5,1,1,0,0,1,0.5,0,0,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,1,0,0,1,0.5,0,1,0,0,1,1,0,0,1,1,0,0,0,0,1,1,0,1,1,0,0.5,1,0,0,0,0.5,1,1,1,1,0,0,1,1,1,1,0,1,0,1,0,0] recall 0.39375 [0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,0,1,0,0,0,0,1,1,0,1,1,1,0,0,0,0,1,1,0,0.5,1,0,0,0,0,0,1,1,0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,1,1,1,0,0,1,0,0,1,0,1,1,1,1,1,0,1,1,0,0,0,1,0,0,0,1,1,0,1,1,0,0,1,0,0] recall 0.36875 [0,1,1,1,1,0.5,0.5,1,1,1,1,1,0,0,1,0,1,1,0,0,0,1,0,1,0,1,0,0,0,0.5,0,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,1,0,0.5,1,0,0,1,0.5,0,0,1,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,0,0,0,0,1,0,1,0,0,1,1,1,1,0.5,0,1,0,0] recall 0.38125 [0,0.5,1,1,0,1,1,1,0,1,1,1,0,0.5,1,1,1,1,0,0,0,1,0,1,0.5,0,1,0,0.5,1,0,1,1,1,0,0,0,0,0,1,0,0,0,0,1,0,1,0,1,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0.5,1,1,0,1,0.5,1,1,0,0,0.5,0,0.5,1,1,1,0,0,1,1,1,0,0,1,0,1,0,0,1,0,0,1,0,1,0.5,0,0] recall 0.3625 [1,0,1,1,0.5,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0,1,1,1,0,0,0,0,0,1,0,1,1,1,0,0,0,0,0,1,1,0.5,0.5,0.5,0,0,1,0,1,1,0.5,0,0,0,0,1,1,1,0,0,0,0,0,0.5,1,1,0,1,0,1,1,0,0,0.5,0,0.5,1,1,1,0,0,0,1,0,0,0,0.5,0,1,0,0,1,0,0,1,0,1,0,0,1] relative_absolute_error 0.6313131313131306 relative_absolute_error 0.5997474747474741 relative_absolute_error 0.6186868686868681 relative_absolute_error 0.6249999999999993 relative_absolute_error 0.6060606060606054 relative_absolute_error 0.5997474747474741 relative_absolute_error 0.6123737373737367 relative_absolute_error 0.637626262626262 relative_absolute_error 0.6249999999999993 relative_absolute_error 0.6439393939393934 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 0.11180339887498952 root_mean_squared_error 0.10897247358851687 root_mean_squared_error 0.1106797181058933 root_mean_squared_error 0.11124297730643498 root_mean_squared_error 0.10954451150103325 root_mean_squared_error 0.10897247358851687 root_mean_squared_error 0.11011357772772623 root_mean_squared_error 0.11236102527122119 root_mean_squared_error 0.11124297730643498 root_mean_squared_error 0.11291589790636218 root_relative_squared_error 1.1236664374387366 root_relative_squared_error 1.0952145677879512 root_relative_squared_error 1.1123730207865241 root_relative_squared_error 1.1180339887498945 root_relative_squared_error 1.1009637651263602 root_relative_squared_error 1.0952145677879512 root_relative_squared_error 1.1066830958984932 root_relative_squared_error 1.1292707935887318 root_relative_squared_error 1.1180339887498945 root_relative_squared_error 1.1348474733984242 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 562.9320860000462 usercpu_time_millis 566.3684270000431 usercpu_time_millis 547.3009209999873 usercpu_time_millis 544.1168229999676 usercpu_time_millis 538.1429800000888 usercpu_time_millis 545.2989430000343 usercpu_time_millis 578.5534479999797 usercpu_time_millis 536.7996530000028 usercpu_time_millis 555.7079780001004 usercpu_time_millis 538.2634999999709 usercpu_time_millis_testing 54.9021269999912 usercpu_time_millis_testing 54.18412899996383 usercpu_time_millis_testing 54.88668899999993 usercpu_time_millis_testing 51.33668899998156 usercpu_time_millis_testing 54.24116100004994 usercpu_time_millis_testing 53.68098600001758 usercpu_time_millis_testing 56.83312899998327 usercpu_time_millis_testing 50.733239000010144 usercpu_time_millis_testing 53.64914800009046 usercpu_time_millis_testing 51.13504099995225 usercpu_time_millis_training 508.029959000055 usercpu_time_millis_training 512.1842980000793 usercpu_time_millis_training 492.41423199998735 usercpu_time_millis_training 492.780133999986 usercpu_time_millis_training 483.9018190000388 usercpu_time_millis_training 491.61795700001676 usercpu_time_millis_training 521.7203189999964 usercpu_time_millis_training 486.0664139999926 usercpu_time_millis_training 502.05883000000995 usercpu_time_millis_training 487.12845900001867