6209410 1 Jan van Rijn 9954 Supervised Classification 6952 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1) 4242739 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "median" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse true 6948 threshold 0.0 6949 C 155.10707988971012 6953 cache_size 200 6953 class_weight null 6953 coef0 0.0 6953 decision_function_shape null 6953 degree 3 6953 gamma 0.3865265019550319 6953 kernel "rbf" 6953 max_iter -1 6953 probability true 6953 random_state 48091 6953 shrinking false 6953 tol 0.0001989722680253024 6953 verbose false 6953 openml-pimp openml-python Sklearn_0.18.1. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 13349291 description https://api.openml.org/data/download/13349291/description.xml -1 13349292 predictions https://api.openml.org/data/download/13349292/predictions.arff area_under_roc_curve 0.9961560921717171 [0.993568,1,1,1,0.999527,0.997041,0.999645,1,0.996686,0.999882,0.999092,1,0.999803,0.984848,0.999645,1,1,0.987019,0.981613,0.971117,0.997159,0.999763,0.995462,1,0.996804,0.976365,0.978851,0.998698,0.998935,1,0.999842,1,0.999645,0.988755,0.999803,0.999053,0.990096,0.980429,0.999921,1,0.99925,0.999803,1,0.998777,0.999408,0.999527,0.999803,0.99783,0.998146,0.997238,0.996646,0.998501,0.999014,0.988045,0.997869,0.981021,1,0.999763,0.994239,0.994989,0.99929,0.99925,0.995226,0.998816,0.999408,0.993726,0.988163,0.999921,0.994318,0.994081,0.994792,0.997909,0.993371,0.999961,0.987295,0.999684,0.999882,0.993174,1,0.999605,0.993568,0.997199,0.999171,0.996094,0.998816,0.999882,1,0.999645,0.999448,1,0.995028,0.999487,0.998856,0.998974,0.999487,0.997869,0.998737,0.998106,0.972143,0.996291] average_cost 0 f_measure 0.8062979849386354 [0.722222,0.9375,1,1,0.9375,0.740741,0.9375,0.967742,0.848485,0.896552,0.903226,0.941176,0.967742,0.666667,1,0.9375,1,0.428571,0.424242,0.181818,0.75,0.967742,0.685714,1,0.848485,0.363636,0.368421,0.8125,0.903226,0.896552,0.969697,1,0.875,0.4375,0.941176,0.689655,0.470588,0.4375,0.909091,1,0.742857,0.909091,0.933333,0.8125,0.967742,0.903226,0.933333,0.9375,0.736842,0.83871,0.8,0.785714,0.903226,0.8,0.787879,0.322581,1,0.9375,0.685714,0.742857,0.8,0.9375,0.727273,0.882353,0.903226,0.606061,0.411765,1,0.727273,0.705882,0.714286,0.758621,0.545455,0.967742,0.764706,0.969697,0.933333,0.5625,1,0.9375,0.774194,0.903226,0.866667,0.625,0.83871,0.903226,0.967742,0.866667,0.9375,1,0.740741,0.827586,0.848485,0.83871,0.9375,0.823529,0.857143,0.810811,0.333333,0.827586] kappa 0.8017676767676767 kb_relative_information_score 981.4783252397167 mean_absolute_error 0.01618822338337978 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 0.8151037942535614 [0.65,0.9375,1,1,0.9375,0.909091,0.9375,1,0.823529,1,0.933333,0.888889,1,0.714286,1,0.9375,1,0.5,0.411765,0.176471,0.75,1,0.631579,1,0.823529,0.352941,0.318182,0.8125,0.933333,1,0.941176,1,0.875,0.4375,0.888889,0.769231,0.444444,0.4375,0.882353,1,0.684211,0.882353,1,0.8125,1,0.933333,1,0.9375,0.636364,0.866667,0.736842,0.916667,0.933333,0.857143,0.764706,0.333333,1,0.9375,0.631579,0.684211,0.857143,0.9375,0.705882,0.833333,0.933333,0.588235,0.388889,1,0.705882,0.666667,0.833333,0.846154,0.529412,1,0.722222,0.941176,1,0.5625,1,0.9375,0.8,0.933333,0.928571,0.625,0.866667,0.933333,1,0.928571,0.9375,1,0.909091,0.923077,0.823529,0.866667,0.9375,0.777778,0.789474,0.714286,0.3,0.923077] predictive_accuracy 0.80375 prior_entropy 6.6438561897747395 recall 0.80375 [0.8125,0.9375,1,1,0.9375,0.625,0.9375,0.9375,0.875,0.8125,0.875,1,0.9375,0.625,1,0.9375,1,0.375,0.4375,0.1875,0.75,0.9375,0.75,1,0.875,0.375,0.4375,0.8125,0.875,0.8125,1,1,0.875,0.4375,1,0.625,0.5,0.4375,0.9375,1,0.8125,0.9375,0.875,0.8125,0.9375,0.875,0.875,0.9375,0.875,0.8125,0.875,0.6875,0.875,0.75,0.8125,0.3125,1,0.9375,0.75,0.8125,0.75,0.9375,0.75,0.9375,0.875,0.625,0.4375,1,0.75,0.75,0.625,0.6875,0.5625,0.9375,0.8125,1,0.875,0.5625,1,0.9375,0.75,0.875,0.8125,0.625,0.8125,0.875,0.9375,0.8125,0.9375,1,0.625,0.75,0.875,0.8125,0.9375,0.875,0.9375,0.9375,0.375,0.75] relative_absolute_error 0.817587039564634 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08308285337528497 root_relative_squared_error 0.8350140944179779 total_cost 0 area_under_roc_curve 0.9958908028819362 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,0.996835,0.968354,0.981132,0.993711,1,1,1,1,0.990506,1,1,1,1,1,1,0.993671,0.974684,0.996835,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.930818,0.990506,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,0.996835,1,1,1,0.996835,1,0.993671,1,1,1,1,0.987342,1,0.987342,0.911392,1] area_under_roc_curve 0.9965242118461907 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.933544,1,1,1,0.981013,0.993671,0.993711,1,1,1,1,1,0.981013,0.984177,1,1,1,1,1,1,1,1,0.993711,0.993711,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,0.996835,1,0.955975,1,0.993671,1,1,1,1,1,1,0.993671,1,0.993671,0.981013,1,0.993711,0.993711,0.996835,1,1,1,1,1,0.990506,1,1,0.993671,0.996835,1,1,0.993671,0.996835,0.981132] area_under_roc_curve 0.9957756149988055 [1,1,1,1,1,1,0.993711,1,0.993671,1,1,1,1,0.996835,0.996835,1,1,0.968354,0.993711,0.946203,0.993711,1,0.981013,1,1,0.974684,0.990506,0.993711,1,1,1,1,1,0.987342,1,1,0.993711,0.937107,1,1,0.993671,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.974843,0.984177,1,1,1,0.968553,1,1,0.993671,1,0.987421,0.993671,0.990506,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.962264,1] area_under_roc_curve 0.9956188798662529 [1,1,1,1,1,0.993671,1,1,0.993671,1,1,1,1,1,1,1,1,1,0.930818,0.962025,1,1,1,1,0.981132,0.981013,0.984177,1,1,1,1,1,1,0.990506,1,1,1,0.937107,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,0.977848,1,1,0.993711,1,1,1,1,1,1,1,0.971519,1,1,0.993671,0.974684,0.993671,0.974843,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,0.943396,0.981013] area_under_roc_curve 0.9959306086298861 [1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.949686,1,1,1,0.993671,1,0.984177,1,1,1,1,0.990506,0.996835,0.974684,1,1,1,1,1,1,0.974684,1,1,0.993671,0.971519,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.981132,1,0.993711,0.990506,0.984177,1,0.996835,1,1,1,1,1,1,1,1,0.981132,1,0.993671,1,1,1,1,1,0.933544,1,0.996835,0.984177,1,1,1,1,1,0.990506,0.987421,1,1,1,1,1,1,0.996835,1,1,0.996835,0.993711,1,1,1,1] area_under_roc_curve 0.9958885638086139 [0.955696,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.993711,0.943038,1,1,0.993671,1,0.993671,0.987342,0.977848,1,1,1,1,1,1,0.993671,1,0.996835,0.993671,0.984177,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.974684,1,1,0.996835,1,0.993671,1,0.987421,1,1,0.990506,1,1,1,1,1,0.987342,1,1,0.987342,1,1,0.990506,1,1,0.987421,0.990506,1,0.993671,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,0.981132,0.993671] area_under_roc_curve 0.9957397898256506 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.987342,0.968354,0.996835,1,1,1,1,0.855346,0.90566,0.996835,1,1,0.996835,1,1,0.993711,1,1,0.96519,0.987342,1,1,1,0.996835,1,1,0.987421,0.996835,1,1,1,1,0.993711,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,0.996835,1,0.974843,1,1,0.996835,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,1,0.971519,1] area_under_roc_curve 0.9972762916965209 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.987421,0.974684,0.993671,0.993671,1,0.996835,1,0.993671,0.981132,0.993711,1,0.993711,1,1,1,1,1,1,1,0.984177,0.993671,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.974843,0.996835,1,1,1,0.971519,1,1,0.993671,1,1,1,1,1,1,0.981132,0.949686,1,0.996835,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1] area_under_roc_curve 0.9968406675423932 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,0.987421,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,0.993711,1,1,0.990506,0.971519,1,1,1,1,1,0.990506,1,0.990506,1,0.996835,0.993711,1,0.993671,1,1,0.936709,0.996835,0.949686,1,1,0.996835,1,0.996835,1,1,1,1,1,0.996835,1,0.993671,1,1,0.987421,0.968354,1,1,1,1,0.993711,1,0.996835,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1] area_under_roc_curve 0.9975536880025475 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.962264,0.974684,0.974843,0.996835,1,1,1,1,0.987421,0.993711,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,0.993711,1,1,0.993671,0.990506,1,1,0.984177,1,0.993711,0.993711,0.987342,1,1,0.993711,1,1,0.987342,1,0.996835,0.993671,1,1,1,1,1,0.974843,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1] 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 0.8041924914136829 kappa 0.8167890705204138 kappa 0.8357354392892399 kappa 0.7789444597955236 kappa 0.7662204320183233 kappa 0.7725387987205308 kappa 0.8041461006910168 kappa 0.8167601295316326 kappa 0.8104714522624971 kappa 0.810501381760758 kb_relative_information_score 98.86875849602791 kb_relative_information_score 97.46089679835808 kb_relative_information_score 98.20769399301449 kb_relative_information_score 97.2240126985506 kb_relative_information_score 97.2792383178784 kb_relative_information_score 96.11070833767552 kb_relative_information_score 100.10298764788894 kb_relative_information_score 98.46246328339294 kb_relative_information_score 99.10459737813534 kb_relative_information_score 98.65696828879338 mean_absolute_error 0.016077159813129738 mean_absolute_error 0.016276570057601858 mean_absolute_error 0.01618702289649725 mean_absolute_error 0.016269352045485217 mean_absolute_error 0.016311394424904823 mean_absolute_error 0.016427722047338132 mean_absolute_error 0.015936669585311338 mean_absolute_error 0.01618058588186205 mean_absolute_error 0.016076945695416244 mean_absolute_error 0.016138811386251197 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 0.80625 predictive_accuracy 0.81875 predictive_accuracy 0.8375 predictive_accuracy 0.78125 predictive_accuracy 0.76875 predictive_accuracy 0.775 predictive_accuracy 0.80625 predictive_accuracy 0.81875 predictive_accuracy 0.8125 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 0.80625 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0,1] recall 0.81875 [1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,0.5,1,0.5,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,0] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1] recall 0.78125 [1,1,1,1,0.5,0,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,0,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0.5,0,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5] recall 0.76875 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0,1,0.5,1,1,0,1,1,1,0,1,1,0.5,1,1,0.5,0,1,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,0,0,0.5,1,0.5,0,1,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1] recall 0.775 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,1,1,0,1,0,1,0.5,1,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,0.5,1,1,1,1,1,0,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0] recall 0.80625 [1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,0,1] recall 0.81875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,0,1,1,0,1,1,1,1,1,1,1,1,1] recall 0.8125 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0,0.5,1,0,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1] recall 0.8125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0.5,0,0.5,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,0,0,0,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1] relative_absolute_error 0.8119777683398844 relative_absolute_error 0.8220489928081733 relative_absolute_error 0.8175264089140012 relative_absolute_error 0.8216844467416763 relative_absolute_error 0.8238077992376159 relative_absolute_error 0.8296829316837426 relative_absolute_error 0.8048823022884501 relative_absolute_error 0.8172013071647486 relative_absolute_error 0.8119669543139504 relative_absolute_error 0.8150914841540995 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 0.08262138235556568 root_mean_squared_error 0.08334258228037993 root_mean_squared_error 0.08305408372971168 root_mean_squared_error 0.08352998717271498 root_mean_squared_error 0.0836440114378643 root_mean_squared_error 0.08434016987941088 root_mean_squared_error 0.08194380101971507 root_mean_squared_error 0.08294328132313965 root_mean_squared_error 0.08251802419342216 root_mean_squared_error 0.08286677960032483 root_relative_squared_error 0.830376136163337 root_relative_squared_error 0.8376244681313411 root_relative_squared_error 0.8347249486006505 root_relative_squared_error 0.8395079581669543 root_relative_squared_error 0.8406539451502764 root_relative_squared_error 0.8476506007419387 root_relative_squared_error 0.8235661875088998 root_relative_squared_error 0.8336113425143843 root_relative_squared_error 0.8293373475486376 root_relative_squared_error 0.8328424712707705 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 1706.9395089999944 usercpu_time_millis 1581.5613540000015 usercpu_time_millis 1594.6333989999957 usercpu_time_millis 1580.672761999999 usercpu_time_millis 1593.0368409999999 usercpu_time_millis 1580.2663370000046 usercpu_time_millis 1591.1264969999977 usercpu_time_millis 1590.205300000001 usercpu_time_millis 1590.5536559999973 usercpu_time_millis 1589.4287109999896 usercpu_time_millis_testing 158.3774269999978 usercpu_time_millis_testing 158.79840699999903 usercpu_time_millis_testing 157.68878000000086 usercpu_time_millis_testing 159.02230100000025 usercpu_time_millis_testing 162.47511899999978 usercpu_time_millis_testing 158.86027300000194 usercpu_time_millis_testing 157.87137899999948 usercpu_time_millis_testing 157.84556199999855 usercpu_time_millis_testing 157.95049500000147 usercpu_time_millis_testing 157.92118399999566 usercpu_time_millis_training 1548.5620819999965 usercpu_time_millis_training 1422.7629470000024 usercpu_time_millis_training 1436.9446189999949 usercpu_time_millis_training 1421.6504609999988 usercpu_time_millis_training 1430.5617220000001 usercpu_time_millis_training 1421.4060640000027 usercpu_time_millis_training 1433.2551179999982 usercpu_time_millis_training 1432.3597380000024 usercpu_time_millis_training 1432.603160999996 usercpu_time_millis_training 1431.5075269999938