5952979 1 Jan van Rijn 9954 Supervised Classification 6970 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier))(1) 3987720 class_weight null 6941 criterion "gini" 6941 max_depth 9 6941 max_features null 6941 max_leaf_nodes null 6941 min_impurity_split 1e-07 6941 min_samples_leaf 1 6941 min_samples_split 2 6941 min_weight_fraction_leaf 0.0 6941 presort false 6941 random_state 19825 6941 splitter "best" 6941 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "most_frequent" 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 false 6948 threshold 0.0 6949 algorithm "SAMME.R" 6971 learning_rate 0.05129720397177312 6971 n_estimators 89 6971 random_state 38695 6971 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12829426 description https://api.openml.org/data/download/12829426/description.xml -1 12829425 predictions https://api.openml.org/data/download/12829425/predictions.arff area_under_roc_curve 0.9954498106060602 [0.995423,0.997199,1,1,0.999053,0.993213,0.999961,0.999961,0.998224,0.999882,0.997475,0.999921,0.995857,0.995778,1,0.999921,0.999842,0.979482,0.983744,0.985322,0.999448,0.999921,0.995186,1,0.999527,0.942235,0.990412,0.998501,0.997988,1,0.999329,1,1,0.98836,0.999803,0.996765,0.989702,0.986269,0.996173,0.999842,0.999487,0.999842,1,0.999842,0.999684,1,0.998501,0.999842,0.995975,0.993134,0.998895,0.996843,0.997988,0.964686,0.998658,0.969302,1,0.999684,0.995186,0.993529,0.999921,0.999014,0.994949,0.99925,0.999171,0.995541,0.990017,1,0.99566,0.996765,0.999605,0.99783,0.991319,0.999763,0.989781,0.999605,0.999961,0.987058,1,1,0.987058,0.996883,0.998343,0.993213,0.99708,0.998737,1,0.980548,0.999171,1,0.999487,0.998619,0.998106,0.999132,0.998777,0.999921,0.999211,0.997435,0.967961,0.99929] average_cost 0 f_measure 0.8132663756011743 [0.666667,0.875,0.969697,1,0.9375,0.689655,0.9375,0.9375,0.8,0.967742,0.742857,0.969697,0.848485,0.733333,0.969697,0.967742,0.875,0.594595,0.545455,0.428571,0.857143,0.9375,0.75,1,0.882353,0.357143,0.514286,0.875,0.933333,0.969697,0.903226,1,1,0.451613,0.909091,0.8125,0.529412,0.37037,0.823529,0.969697,0.848485,0.933333,1,0.842105,0.909091,0.967742,0.774194,0.9375,0.75,0.903226,0.875,0.666667,0.774194,0.571429,0.787879,0.444444,1,0.9375,0.625,0.75,0.967742,0.8125,0.625,0.882353,0.875,0.65,0.363636,0.941176,0.62069,0.6,0.814815,0.83871,0.647059,0.9375,0.75,0.903226,0.969697,0.785714,1,1,0.774194,0.774194,0.848485,0.727273,0.774194,0.875,1,0.777778,0.909091,0.967742,0.875,0.848485,0.83871,0.896552,0.9375,0.967742,0.941176,0.666667,0.466667,0.875] kappa 0.8125 kb_relative_information_score 1372.9838404394186 mean_absolute_error 0.004044616286898861 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 0.8180372480976191 [0.818182,0.875,0.941176,1,0.9375,0.769231,0.9375,0.9375,0.857143,1,0.684211,0.941176,0.823529,0.785714,0.941176,1,0.875,0.52381,0.529412,0.5,0.789474,0.9375,0.75,1,0.833333,0.416667,0.473684,0.875,1,0.941176,0.933333,1,1,0.466667,0.882353,0.8125,0.5,0.454545,0.777778,0.941176,0.823529,1,1,0.727273,0.882353,1,0.8,0.9375,0.75,0.933333,0.875,0.647059,0.8,0.666667,0.764706,0.4,1,0.9375,0.625,0.75,1,0.8125,0.625,0.833333,0.875,0.541667,0.352941,0.888889,0.692308,0.642857,1,0.866667,0.611111,0.9375,0.75,0.933333,0.941176,0.916667,1,1,0.8,0.8,0.823529,0.705882,0.8,0.875,1,0.7,0.882353,1,0.875,0.823529,0.866667,1,0.9375,1,0.888889,0.647059,0.5,0.875] predictive_accuracy 0.814375 prior_entropy 6.6438561897747395 recall 0.814375 [0.5625,0.875,1,1,0.9375,0.625,0.9375,0.9375,0.75,0.9375,0.8125,1,0.875,0.6875,1,0.9375,0.875,0.6875,0.5625,0.375,0.9375,0.9375,0.75,1,0.9375,0.3125,0.5625,0.875,0.875,1,0.875,1,1,0.4375,0.9375,0.8125,0.5625,0.3125,0.875,1,0.875,0.875,1,1,0.9375,0.9375,0.75,0.9375,0.75,0.875,0.875,0.6875,0.75,0.5,0.8125,0.5,1,0.9375,0.625,0.75,0.9375,0.8125,0.625,0.9375,0.875,0.8125,0.375,1,0.5625,0.5625,0.6875,0.8125,0.6875,0.9375,0.75,0.875,1,0.6875,1,1,0.75,0.75,0.875,0.75,0.75,0.875,1,0.875,0.9375,0.9375,0.875,0.875,0.8125,0.8125,0.9375,0.9375,1,0.6875,0.4375,0.875] relative_absolute_error 0.20427354984337642 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.05466908710110289 root_relative_squared_error 0.5494449986230797 total_cost 0 area_under_roc_curve 0.9957693953506886 [1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,1,1,1,1,0.911392,0.974684,1,1,1,0.974843,1,1,1,0.993671,1,0.996835,1,0.996835,1,1,0.974684,1,0.993711,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,0.974684,1,0.993711,1,1,1,1,1,1,0.996835,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.996835,0.996835,1,1,1,1,1,1,1,1,1,0.914557,1] area_under_roc_curve 0.9950200521455297 [0.993711,0.984177,1,1,1,1,1,1,1,1,1,1,0.987342,0.996835,1,1,1,0.96519,0.96519,0.993711,1,0.993711,1,1,1,0.882911,0.993671,1,1,1,1,1,1,1,1,1,0.949686,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.984177,1,0.996835,1,0.974843,1,1,1,0.962025,1,0.993711,1,0.996835,1,0.993671,0.993671,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.990506,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,0.984177,1] area_under_roc_curve 0.9964065361038135 [0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.958861,1,1,0.996835,1,1,0.920886,1,1,1,1,1,1,1,0.981013,1,1,0.993711,0.937107,1,1,1,1,1,1,0.996835,1,0.996835,1,0.984177,1,1,1,1,0.993671,1,1,1,1,0.981132,0.993671,1,1,0.996835,1,1,0.996835,1,1,1,0.996835,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.930818,1] area_under_roc_curve 0.9968386772549958 [0.993671,0.990506,1,1,1,0.968354,1,1,0.996835,1,0.993671,1,1,1,1,1,1,1,0.968553,0.977848,1,1,1,1,1,0.984177,0.977848,1,1,1,1,1,1,0.990506,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.974684,1,0.993671,1,1,1,1,1,1,0.996835,1,0.996835,0.996835,0.984177,1,1,1,1,0.993671,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.990506,1,0.990506] area_under_roc_curve 0.9946640394873022 [0.996835,1,1,1,1,1,1,1,1,1,1,1,0.968553,0.981132,1,1,1,0.996835,1,1,0.993671,1,1,1,1,0.974684,0.981013,1,1,1,1,1,1,0.968354,1,1,0.977848,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,0.993711,0.987342,0.943038,1,0.996835,1,1,1,1,1,1,1,1,0.987421,1,0.993671,0.990506,1,1,1,1,0.962025,1,1,0.927215,1,1,1,1,0.996835,0.996835,0.987421,1,1,1,1,1,1,0.981013,1,1,0.981013,1,0.996835,1,0.993711,0.996835] area_under_roc_curve 0.996362252209219 [0.990506,1,1,1,1,0.987342,1,1,1,1,0.987342,1,1,1,1,1,1,0.993671,1,0.971519,1,1,1,1,1,0.977848,0.990506,1,1,1,1,1,1,0.993671,1,0.984177,0.996835,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.949367,1,1,1,1,1,0.990506,1,1,0.971519,1,1,1,0.993711,1,1,1,1,1,1,1,1,0.990506,1,1,0.990506,1,1,0.987342,1,1,1,0.990506,1,0.993671,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.981132,0.987421,1] area_under_roc_curve 0.9949603435236047 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,0.990506,1,1,1,1,1,0.735849,0.974843,0.984177,1,1,0.993671,1,1,0.987421,1,1,0.993671,0.993671,1,1,0.996835,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.996835,0.993671,1,1,0.996835,0.993711,1,1,1,0.990506,1,1,0.962264,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,0.761006,1,1,1,1,0.984177,1,1,1,1,1,0.993671,1] area_under_roc_curve 0.9954166169094817 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,0.968354,0.996835,1,1,1,1,1,0.962264,0.993711,1,0.974843,1,1,1,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.990506,1,1,0.876582,1,1,1,0.993711,1,0.993671,1,1,1,0.974843,0.993711,1,0.993671,0.996835,1,1,1,1,0.996835,1,1,1,1,1,0.911392,1,0.996835,1,0.987342,1,1,0.993711,1,1,1,1,1,0.993711,1,1,1,1,1,1] area_under_roc_curve 0.9949038691187007 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1,1,0.899371,0.993711,1,1,1,1,1,1,1,1,1,1,0.968354,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,0.993671,0.996835,0.863924,1,1,1,1,0.993671,1,1,1,0.993671,1,1,1,0.996835,1,0.993671,0.993711,1,0.993711,0.958861,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,0.993671,1,1,0.993711,1,0.927215,1] area_under_roc_curve 0.9971964314146963 [1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.990506,1,1,1,0.993711,0.993671,1,1,1,1,1,1,0.981132,1,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.952532,1,1,1,1,1,1,1,1,0.984177,1,1,1,0.990506,1,0.990506,0.993711,1,1,0.96519,1,0.996835,1,1,1,1,1,1,0.962264,1,0.949686,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] 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 0.823127640254254 kappa 0.8041228970855383 kappa 0.867330016583748 kappa 0.7978202495656295 kappa 0.7535934291581109 kappa 0.7789095503178175 kappa 0.7978202495656295 kappa 0.8294310419710191 kappa 0.8420595435520809 kappa 0.8294377763739735 kb_relative_information_score 136.82735731658343 kb_relative_information_score 137.4492990283721 kb_relative_information_score 142.00579336587174 kb_relative_information_score 134.50272256672224 kb_relative_information_score 128.27017182523926 kb_relative_information_score 135.1563193208616 kb_relative_information_score 135.43831562185372 kb_relative_information_score 140.10778077494405 kb_relative_information_score 141.52639663421124 kb_relative_information_score 141.6996839847594 mean_absolute_error 0.00395671820134144 mean_absolute_error 0.004198451710098552 mean_absolute_error 0.0034565674045044952 mean_absolute_error 0.004221402534151296 mean_absolute_error 0.0049828137997169125 mean_absolute_error 0.00472360055069762 mean_absolute_error 0.004179721367208809 mean_absolute_error 0.0037969720143127992 mean_absolute_error 0.0035383776131083533 mean_absolute_error 0.003391537673848263 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 0.825 predictive_accuracy 0.80625 predictive_accuracy 0.86875 predictive_accuracy 0.8 predictive_accuracy 0.75625 predictive_accuracy 0.78125 predictive_accuracy 0.8 predictive_accuracy 0.83125 predictive_accuracy 0.84375 predictive_accuracy 0.83125 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 0.825 [1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0,1,1,0.5,0,0.5,1,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,0,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1] recall 0.80625 [0,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,0.5,0.5,0.5,0,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,1,0.5,1,0,1,1,1,0.5,1,0,0.5,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,0.5,1] recall 0.86875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,1,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.8 [0.5,0.5,1,1,0.5,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,0.5,1,1,1,0,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,0.5,1,0.5] recall 0.75625 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,1,1,1,0,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,0,0.5,0,1,1,1,0,0.5,1,0,1,0.5,1,0,1,0,0.5,1,1,1,0,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,0.5] recall 0.78125 [0.5,1,1,1,1,0,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,0,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0.5,1,1,0,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,0,1] recall 0.8 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,0,1,1,1,0,1,1,1,0,1,1,0,0.5,0,1,1,1,0,1,1,1,1,0.5,1,0.5,0,1,1,1,1,0.5,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,0,1] recall 0.83125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,0,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,1] recall 0.84375 [1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,0,1,0,0,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1] recall 0.83125 [0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,0.5,0,1,1,1,0,1,0.5,1,0,1,0,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1] relative_absolute_error 0.1998342525930017 relative_absolute_error 0.21204301566154268 relative_absolute_error 0.1745741113386106 relative_absolute_error 0.21320214818945907 relative_absolute_error 0.25165726261196486 relative_absolute_error 0.23856568437866726 relative_absolute_error 0.21109703874791932 relative_absolute_error 0.19176626334913094 relative_absolute_error 0.17870594005597712 relative_absolute_error 0.17128978150748772 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 0.054225043583729794 root_mean_squared_error 0.05453461165101118 root_mean_squared_error 0.04836170197295034 root_mean_squared_error 0.057012043387459986 root_mean_squared_error 0.06286885752778913 root_mean_squared_error 0.058905323686615836 root_mean_squared_error 0.057058786747592405 root_mean_squared_error 0.05280638641734175 root_mean_squared_error 0.04904016573344613 root_mean_squared_error 0.0501198210686995 root_relative_squared_error 0.5449821933572732 root_relative_squared_error 0.5480934694974181 root_relative_squared_error 0.486053392931111 root_relative_squared_error 0.5729925952959616 root_relative_squared_error 0.6318557921757182 root_relative_squared_error 0.5920207782513306 root_relative_squared_error 0.5734623837414152 root_relative_squared_error 0.5307241523661885 root_relative_squared_error 0.4928722102869234 root_relative_squared_error 0.5037231546806834 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 4299.254372 usercpu_time_millis 4186.832433999998 usercpu_time_millis 4358.453965999999 usercpu_time_millis 4310.128438000002 usercpu_time_millis 4320.119408 usercpu_time_millis 4156.417622999999 usercpu_time_millis 4137.375312000003 usercpu_time_millis 4111.088239999994 usercpu_time_millis 4102.029762000001 usercpu_time_millis 4131.4536020000005 usercpu_time_millis_testing 101.28393400000047 usercpu_time_millis_testing 94.45227799999856 usercpu_time_millis_testing 100.45763399999963 usercpu_time_millis_testing 95.6747809999996 usercpu_time_millis_testing 94.5296159999991 usercpu_time_millis_testing 94.4591680000002 usercpu_time_millis_testing 94.05422500000071 usercpu_time_millis_testing 94.57766199999895 usercpu_time_millis_testing 95.75905799999873 usercpu_time_millis_testing 95.17050200000199 usercpu_time_millis_training 4197.970438 usercpu_time_millis_training 4092.3801559999997 usercpu_time_millis_training 4257.996332 usercpu_time_millis_training 4214.453657000002 usercpu_time_millis_training 4225.589792000001 usercpu_time_millis_training 4061.958454999999 usercpu_time_millis_training 4043.3210870000025 usercpu_time_millis_training 4016.510577999995 usercpu_time_millis_training 4006.2707040000023 usercpu_time_millis_training 4036.2830999999987