6016103 1 Jan van Rijn 9954 Supervised Classification 6969 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1) 4050792 bootstrap true 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.6036642443171817 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 9 6902 min_samples_split 5 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 19937 6902 verbose 0 6902 warm_start false 6902 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 false 6948 threshold 0.0 6949 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12955337 description https://api.openml.org/data/download/12955337/description.xml -1 12955338 predictions https://api.openml.org/data/download/12955338/predictions.arff area_under_roc_curve 0.9938273358585856 [0.981258,0.999763,1,1,0.997475,0.993292,0.999566,0.998974,0.995265,0.999684,0.997277,0.999684,0.99858,0.978812,0.999211,0.998067,0.999961,0.981889,0.986387,0.965041,0.998698,0.999487,0.99199,1,0.997988,0.969973,0.989583,0.99637,0.996646,0.999645,0.999684,1,0.998027,0.989031,0.997672,0.998698,0.992385,0.987689,0.999014,0.999645,0.996015,0.998185,0.999961,0.998146,0.998658,0.999092,0.999171,0.993134,0.990925,0.997199,0.995502,0.991832,0.996528,0.979482,0.988636,0.976918,1,0.999645,0.994752,0.984217,0.999921,0.996765,0.994239,0.997909,0.997751,0.994476,0.976168,0.999842,0.97968,0.980074,0.993687,0.998146,0.993253,0.998264,0.967448,0.998303,0.999329,0.979837,0.99929,0.99925,0.989268,0.995502,0.996765,0.993845,0.995857,0.990215,0.999882,0.994831,0.997238,0.999882,0.999803,0.999408,0.997672,0.989781,0.998343,0.999211,0.995818,0.993174,0.966461,0.995739] average_cost 0 f_measure 0.7375112928754727 [0.56,0.864865,1,0.969697,0.866667,0.482759,0.909091,0.810811,0.645161,0.903226,0.6875,0.857143,0.769231,0.5,0.903226,0.83871,0.842105,0.461538,0.540541,0.296296,0.769231,0.967742,0.62069,1,0.810811,0.285714,0.344828,0.722222,0.8,0.833333,0.83871,0.969697,0.875,0.606061,0.777778,0.789474,0.545455,0.5,0.903226,0.941176,0.689655,0.909091,0.882353,0.882353,0.8125,0.8125,0.875,0.785714,0.733333,0.83871,0.645161,0.709677,0.777778,0.592593,0.642857,0.25,1,0.941176,0.647059,0.666667,0.857143,0.736842,0.62069,0.823529,0.810811,0.75,0.193548,0.914286,0.48,0.521739,0.571429,0.777778,0.55814,0.848485,0.814815,0.83871,0.842105,0.434783,0.888889,0.967742,0.571429,0.6875,0.8125,0.571429,0.8125,0.903226,0.969697,0.684211,0.764706,0.967742,0.888889,0.769231,0.866667,0.615385,0.833333,0.8,0.714286,0.580645,0.272727,0.709677] kappa 0.7468434343434344 kb_relative_information_score 1070.5682465276418 mean_absolute_error 0.014830392095493347 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 0.7511530398715418 [0.777778,0.761905,1,0.941176,0.928571,0.538462,0.882353,0.714286,0.666667,0.933333,0.6875,0.789474,0.652174,0.75,0.933333,0.866667,0.727273,0.6,0.47619,0.363636,0.652174,1,0.692308,1,0.714286,0.6,0.384615,0.65,0.857143,0.75,0.866667,0.941176,0.875,0.588235,0.7,0.681818,0.529412,0.45,0.933333,0.888889,0.769231,0.882353,0.833333,0.833333,0.8125,0.8125,0.875,0.916667,0.785714,0.866667,0.666667,0.733333,0.7,0.727273,0.75,0.375,1,0.888889,0.611111,0.818182,0.789474,0.636364,0.692308,0.777778,0.714286,0.625,0.2,0.842105,0.666667,0.857143,0.666667,0.7,0.444444,0.823529,1,0.866667,0.727273,0.714286,0.8,1,0.666667,0.6875,0.8125,0.666667,0.8125,0.933333,0.941176,0.590909,0.722222,1,0.8,0.652174,0.928571,0.8,0.75,0.736842,0.833333,0.6,0.5,0.733333] predictive_accuracy 0.749375 prior_entropy 6.6438561897747395 recall 0.749375 [0.4375,1,1,1,0.8125,0.4375,0.9375,0.9375,0.625,0.875,0.6875,0.9375,0.9375,0.375,0.875,0.8125,1,0.375,0.625,0.25,0.9375,0.9375,0.5625,1,0.9375,0.1875,0.3125,0.8125,0.75,0.9375,0.8125,1,0.875,0.625,0.875,0.9375,0.5625,0.5625,0.875,1,0.625,0.9375,0.9375,0.9375,0.8125,0.8125,0.875,0.6875,0.6875,0.8125,0.625,0.6875,0.875,0.5,0.5625,0.1875,1,1,0.6875,0.5625,0.9375,0.875,0.5625,0.875,0.9375,0.9375,0.1875,1,0.375,0.375,0.5,0.875,0.75,0.875,0.6875,0.8125,1,0.3125,1,0.9375,0.5,0.6875,0.8125,0.5,0.8125,0.875,1,0.8125,0.8125,0.9375,1,0.9375,0.8125,0.5,0.9375,0.875,0.625,0.5625,0.1875,0.6875] relative_absolute_error 0.7490097017925919 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.07876387718409253 root_relative_squared_error 0.791606750464452 total_cost 0 area_under_roc_curve 0.9932397400684658 [1,1,1,1,0.996835,1,1,1,0.993671,1,0.990506,0.996835,1,0.971519,1,1,1,0.962025,0.96519,0.993711,1,1,0.993711,1,1,0.987342,0.993671,1,0.987342,0.993711,1,1,1,0.996835,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.96519,1,0.993711,0.993671,1,1,1,1,0.993711,0.984177,1,1,1,1,1,1,0.996835,1,1,0.949686,0.993671,1,0.993671,1,1,1,1,0.968354,1,1,0.996835,0.996835,0.993711,1,1,0.946203,1,0.996835,0.993671,1,1,1,1,0.990506,1,0.993671,1,1,0.867089,1] area_under_roc_curve 0.9938756368919668 [0.981132,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.939873,1,1,1,0.946203,1,0.987421,1,1,1,1,1,0.946203,0.984177,0.990506,1,1,1,1,1,1,0.996835,0.993711,0.974843,1,1,1,1,1,1,0.996835,1,1,1,1,0.993671,1,1,0.949367,1,1,0.993711,0.949686,1,1,1,0.949367,1,1,1,0.993671,1,1,1,1,0.974843,0.993711,1,1,1,1,1,1,1,0.971519,1,1,0.996835,0.996835,0.987421,0.987421,1,1,1,0.996835,0.993671,1,1,1,1,0.984177,1,1,1,0.987342,0.993671,1] area_under_roc_curve 0.9932822824615875 [0.996835,1,1,1,0.993671,0.984177,1,1,0.987342,1,1,1,1,0.996835,0.993671,1,1,0.996835,0.974843,0.901899,1,1,0.955696,1,1,0.984177,1,1,1,1,1,1,1,0.962025,0.993711,1,0.993711,0.955975,1,1,1,1,1,1,0.993671,1,1,1,0.955696,1,0.993671,1,1,0.996835,1,0.981013,1,1,0.993711,0.974684,1,0.981132,1,1,1,0.987342,0.993671,1,0.974843,0.987342,0.996835,0.996835,0.993711,1,1,1,1,0.977848,1,1,1,0.996835,1,0.996835,1,1,1,1,0.993671,1,1,1,0.993711,0.987342,0.996835,1,0.996835,0.993671,0.968553,1] area_under_roc_curve 0.993126293686808 [1,1,1,1,0.996835,0.996835,1,1,0.993671,1,1,1,1,0.996835,1,1,1,0.981013,0.943396,0.990506,1,1,0.993671,1,0.987421,0.977848,0.971519,1,1,1,1,1,1,0.990506,1,0.993711,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.955696,1,0.990506,1,1,1,0.993671,1,1,0.996835,1,0.993671,0.996835,0.946203,1,1,0.936709,0.993671,0.996835,0.974843,1,1,0.993671,1,0.96519,1,1,0.924528,0.987342,1,0.987342,1,1,1,1,1,1,1,1,0.962264,1,1,0.987421,0.984177,0.996835,0.993711,0.971519] area_under_roc_curve 0.9906789865456572 [0.996835,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,0.830189,1,1,1,0.996835,1,0.984177,0.984177,1,1,1,0.993671,0.968354,0.993671,1,1,1,1,1,0.993671,0.977848,1,1,0.993671,0.971519,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,0.993711,0.936709,0.968354,1,0.996835,0.996835,0.987421,1,1,0.987421,1,0.996835,1,0.893082,1,0.93038,0.987342,1,1,1,1,0.835443,1,0.993671,0.984177,1,1,1,1,0.996835,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,0.993711,0.990506,1,0.996835,1,0.987421,0.993671] area_under_roc_curve 0.9935561957646684 [0.924051,1,1,1,1,0.984177,1,1,1,0.996835,1,1,1,1,1,1,1,0.993671,1,0.908228,1,0.996835,0.993671,1,0.993671,0.993671,0.981013,0.993711,1,1,1,1,0.984177,0.996835,0.974843,1,0.981013,1,1,1,1,0.993671,1,1,1,1,1,0.990506,0.993671,0.990506,1,1,1,1,0.990506,0.96519,1,1,0.993671,1,1,0.996835,0.987421,1,1,0.993671,0.993711,1,0.993671,1,0.984177,0.990506,1,1,0.971519,1,1,0.996835,1,1,1,0.990506,1,0.993671,1,1,1,0.987421,0.990506,1,1,1,1,1,1,1,1,0.968553,0.993711,0.987342] area_under_roc_curve 0.9960540064485309 [0.993671,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.996835,1,0.993711,0.993671,0.958861,1,1,1,1,0.996835,0.867925,0.987421,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.996835,0.996835,1,1,1,0.996835,0.996835,0.974684,1,1,1,1,1,1,0.993671,0.990506,1,1,0.993671,0.993711,1,1,1,0.981013,1,1,0.968553,1,1,0.996835,0.993711,1,1,1,1,1,1,0.981132,1,1,0.984177,1,0.993671,0.996835,1,1,1,0.974843,1,1,1,1,1,1,1,1,1,1,0.977848,1] area_under_roc_curve 0.9950250278640234 [1,1,1,1,1,1,0.996835,1,0.993711,1,0.993711,1,1,1,1,0.996835,1,0.962264,0.987342,0.977848,0.996835,1,1,1,1,0.981132,0.974843,0.981013,1,0.996835,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.996835,0.987342,1,1,0.968354,1,1,0.990506,1,1,0.993671,0.987421,0.996835,1,0.962264,0.968553,1,0.977848,0.984177,1,1,1,0.981132,0.993671,1,1,0.987421,1,1,0.984177,1,0.984177,1,0.981013,0.987342,1,1,0.993711,1,1,1,1,0.987421,1,1,0.984177,1,0.987342,1] area_under_roc_curve 0.9963291636812354 [0.962264,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.968553,1,1,1,0.993711,1,0.993671,1,1,1,1,0.993711,1,1,1,0.984177,1,1,0.962264,1,1,0.990506,0.996835,0.996835,1,1,0.993711,1,1,0.996835,1,0.93038,1,0.955975,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,0.993711,0.990506,1,1,0.993671,0.993711,1,1,0.996835,1,1,1,0.993711,0.996835,1,1,0.993671,1,1,1,0.993671,1,0.996835,1,1,0.993711,1,0.971519,1] area_under_roc_curve 0.9968068326566357 [0.899371,1,1,1,1,1,1,0.993711,0.996835,1,1,1,1,0.996835,1,1,1,0.993711,0.993671,0.993711,1,1,1,1,1,0.962264,1,1,0.993671,1,1,1,1,0.974843,1,1,0.993671,1,1,1,1,1,1,0.996835,1,1,1,0.990506,1,1,1,0.996835,1,0.984177,1,1,1,1,0.993671,1,1,0.996835,0.981013,1,0.993711,1,1,1,1,1,0.981132,1,0.981013,1,1,0.996835,1,1,0.981132,1,1,0.974843,1,0.974843,1,1,0.996835,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1] 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 0.7283960364770439 kappa 0.7725747226280255 kappa 0.7221125759848425 kappa 0.7409776514254126 kappa 0.7662942639453635 kappa 0.7346705097326964 kappa 0.7788833609729132 kappa 0.709423980417703 kappa 0.7599115463591849 kappa 0.7536226161803609 kb_relative_information_score 106.65503657361809 kb_relative_information_score 106.740614078105 kb_relative_information_score 105.96429717169862 kb_relative_information_score 106.01963214288679 kb_relative_information_score 105.5407571779912 kb_relative_information_score 106.46809992164553 kb_relative_information_score 109.2212976455596 kb_relative_information_score 106.72060734729399 kb_relative_information_score 108.60483561543504 kb_relative_information_score 108.63306885340953 mean_absolute_error 0.014818839951977487 mean_absolute_error 0.014881212794261318 mean_absolute_error 0.014929382306983882 mean_absolute_error 0.014919498164106699 mean_absolute_error 0.014854141070805293 mean_absolute_error 0.014890047937772568 mean_absolute_error 0.014606503049083003 mean_absolute_error 0.014849387293801575 mean_absolute_error 0.014779377354886158 mean_absolute_error 0.014775531031255456 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 0.73125 predictive_accuracy 0.775 predictive_accuracy 0.725 predictive_accuracy 0.74375 predictive_accuracy 0.76875 predictive_accuracy 0.7375 predictive_accuracy 0.78125 predictive_accuracy 0.7125 predictive_accuracy 0.7625 predictive_accuracy 0.75625 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 0.73125 [1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0,1,1,1,0,0.5,0,1,1,0,1,1,0.5,0,1,0.5,0,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,0,1,1,1,0,1,1,1,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0,1,0.5,1,1,0,1] recall 0.775 [0,1,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0,0,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1] recall 0.725 [0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,0.5,0,0.5,1,1,0,0,1,0,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,0.5] recall 0.74375 [1,1,1,1,0.5,0,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,0,0.5,0,0.5,0,1,1,0.5,1,0,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,0,1,1,0,0.5,0.5,0,0] recall 0.76875 [0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,0,0,0.5,0,0,0,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0.5,1,1,1,0,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5] recall 0.7375 [0,1,1,1,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,0,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,0,0,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0.5,0,1,0.5,1,1,1,0.5,1,0.5,0,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0.5] recall 0.78125 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,0.5,1,0.5,0,0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,0.5,0.5,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,1,0.5,0.5,1,0.5,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.7125 [0.5,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0.5,1,0,0.5,0,1,1,0.5,1,1,0,0,0.5,0,1,0,1,1,1,1,1,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,0,0,1,0,1,0,1,1,0,1,1,1,0,1,1,0,0,0,1,0,0.5,1,1,1,1,1,1,1,0,1,1,0,1,0,1] recall 0.7625 [0,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,0,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,0,1,1,1,0.5,0.5,1,1,0,1,0.5,0.5,1,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,1,1,0,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0.5,0,1,1,0.5,1,0.5,1,1,0,0.5,0.5,1] recall 0.75625 [0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,0,1,1,0,1,0.5,1,1,1,0.5,0.5,1,0.5,1,0.5,1,1,0.5,1,1,0,0.5,0,1,1,1,0.5,1,1,0,1,1,1,0,1,0.5,0,0,0,0.5,1,0,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,0.5,1] relative_absolute_error 0.7484262602008819 relative_absolute_error 0.7515764037505704 relative_absolute_error 0.7540092074234273 relative_absolute_error 0.7535100082882158 relative_absolute_error 0.7502091449901651 relative_absolute_error 0.7520226231198254 relative_absolute_error 0.7377021741961102 relative_absolute_error 0.7499690552425026 relative_absolute_error 0.746433199741724 relative_absolute_error 0.7462389409724964 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 0.07862110376131576 root_mean_squared_error 0.07879006469351588 root_mean_squared_error 0.07936235162006469 root_mean_squared_error 0.07923612985145291 root_mean_squared_error 0.07906730045753332 root_mean_squared_error 0.07925400490619303 root_mean_squared_error 0.07762522828015535 root_mean_squared_error 0.07896638529463607 root_mean_squared_error 0.07826658241716873 root_mean_squared_error 0.07843293198985779 root_relative_squared_error 0.7901718235754056 root_relative_squared_error 0.7918699448370313 root_relative_squared_error 0.7976216448606316 root_relative_squared_error 0.7963530683549942 root_relative_squared_error 0.7946562691028294 root_relative_squared_error 0.7965327194146306 root_relative_squared_error 0.7801628983968488 root_relative_squared_error 0.7936420335543815 root_relative_squared_error 0.7866087500035627 root_relative_squared_error 0.7882806261146099 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 5188.622411999859 usercpu_time_millis 5023.217693999868 usercpu_time_millis 5128.989156999523 usercpu_time_millis 5074.163813000268 usercpu_time_millis 5001.825188999646 usercpu_time_millis 5009.1098209995835 usercpu_time_millis 5036.883517000206 usercpu_time_millis 5005.422235999504 usercpu_time_millis 5034.966830000485 usercpu_time_millis 5109.766876999856 usercpu_time_millis_testing 32.650522999574605 usercpu_time_millis_testing 32.400494999819784 usercpu_time_millis_testing 32.308756999555044 usercpu_time_millis_testing 32.25111000028846 usercpu_time_millis_testing 32.16800599966518 usercpu_time_millis_testing 32.77918599997065 usercpu_time_millis_testing 32.2260519997144 usercpu_time_millis_testing 32.516153999495145 usercpu_time_millis_testing 32.35056999983499 usercpu_time_millis_testing 32.24152700022387 usercpu_time_millis_training 5155.971889000284 usercpu_time_millis_training 4990.817199000048 usercpu_time_millis_training 5096.680399999968 usercpu_time_millis_training 5041.91270299998 usercpu_time_millis_training 4969.657182999981 usercpu_time_millis_training 4976.330634999613 usercpu_time_millis_training 5004.657465000491 usercpu_time_millis_training 4972.906082000009 usercpu_time_millis_training 5002.61626000065 usercpu_time_millis_training 5077.525349999632