5988095 1 Jan van Rijn 9956 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) 4022828 bootstrap false 6902 class_weight null 6902 criterion "gini" 6902 max_depth null 6902 max_features 0.6436106348401507 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 5 6902 min_samples_split 11 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 26640 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 "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 openml-pimp openml-python Sklearn_0.18.1. study_71 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 12899477 description https://api.openml.org/data/download/12899477/description.xml -1 12899478 predictions https://api.openml.org/data/download/12899478/predictions.arff area_under_roc_curve 0.9846936256154634 [0.98367,0.999763,0.98172,0.985629,0.975975,0.992143,0.981819,0.995973,0.997394,0.998223,0.983812,0.972599,0.999368,0.997552,0.958722,0.999368,0.978285,0.99621,0.999368,0.974534,1,0.987879,0.996565,0.998579,0.913653,0.967269,0.955642,0.943245,0.999368,0.999605,0.989063,0.999368,0.991669,0.994334,0.991196,0.965058,0.997355,0.998895,0.98626,0.959472,0.994986,0.994117,0.968414,0.972402,0.959728,0.996091,0.99009,0.999763,0.982253,0.996526,0.954991,0.988708,0.996249,0.991156,0.989182,0.99771,0.999684,0.986616,0.998342,0.99617,0.998895,0.997671,0.998144,0.998934,0.996762,0.987563,0.997986,0.965828,0.99317,0.924333,0.982865,0.957399,0.999487,0.99463,0.999605,0.997868,0.996565,0.999052,0.99925,0.986931,0.997197,0.982667,0.928241,0.988392,0.988866,0.997789,0.961525,0.995933,0.995045,0.998539,0.923681,0.89865,0.99925,0.961209,0.990287,0.99463,0.998105,0.964506,0.995104,0.99696] average_cost 0 f_measure 0.6839482424557106 [0.666667,0.882353,0.518519,0.580645,0.5625,0.625,0.666667,0.717949,0.75,0.764706,0.823529,0.827586,0.833333,0.903226,0.592593,0.909091,0.5,0.764706,0.875,0.764706,0.914286,0.6,0.764706,0.742857,0.08,0.516129,0.647059,0.16,0.882353,0.810811,0.538462,0.777778,0.642857,0.787879,0.571429,0.296296,0.789474,0.823529,0.466667,0.727273,0.848485,0.62069,0.413793,0.384615,0.689655,0.727273,0.580645,0.941176,0.529412,0.684211,0.578947,0.742857,0.634146,0.709677,0.5,0.666667,0.909091,0.625,0.8125,0.83871,0.882353,0.787879,0.83871,0.848485,0.774194,0.6875,0.83871,0.5,0.774194,0.333333,0.705882,0.538462,0.848485,0.634146,0.83871,0.666667,0.75,0.866667,0.896552,0.363636,0.684211,0.6,0.48,0.375,0.625,0.685714,0.466667,0.545455,0.8,0.756757,0.787879,0.210526,0.9375,0.823529,0.764706,0.722222,0.8125,0.882353,0.714286,0.83871] kappa 0.6910943261158908 kb_relative_information_score 1176.80052598295 mean_absolute_error 0.010880288473947031 mean_prior_absolute_error 0.019799992711748222 number_of_instances 1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] precision 0.6918641216254191 [0.75,0.833333,0.636364,0.6,0.5625,0.625,0.714286,0.608696,0.75,0.722222,0.777778,0.923077,0.75,0.933333,0.727273,0.882353,0.45,0.722222,0.875,0.722222,0.842105,0.642857,0.722222,0.684211,0.111111,0.533333,0.611111,0.222222,0.833333,0.714286,0.7,0.7,0.75,0.764706,0.526316,0.363636,0.681818,0.777778,0.5,0.705882,0.823529,0.692308,0.461538,0.5,0.769231,0.705882,0.6,0.888889,0.5,0.590909,0.5,0.684211,0.52,0.733333,0.75,0.6,0.882353,0.625,0.8125,0.866667,0.833333,0.764706,0.866667,0.823529,0.8,0.6875,0.866667,0.583333,0.8,0.5,0.666667,0.7,0.823529,0.52,0.866667,0.647059,0.75,0.928571,1,0.352941,0.590909,0.642857,0.666667,0.375,0.625,0.631579,0.5,0.529412,0.857143,0.666667,0.764706,0.666667,0.9375,0.777778,0.722222,0.65,0.8125,0.833333,0.833333,0.866667] predictive_accuracy 0.6941838649155723 prior_entropy 6.6438309601245775 recall 0.6941838649155723 [0.6,0.9375,0.4375,0.5625,0.5625,0.625,0.625,0.875,0.75,0.8125,0.875,0.75,0.9375,0.875,0.5,0.9375,0.5625,0.8125,0.875,0.8125,1,0.5625,0.8125,0.8125,0.0625,0.5,0.6875,0.125,0.9375,0.9375,0.4375,0.875,0.5625,0.8125,0.625,0.25,0.9375,0.875,0.4375,0.75,0.875,0.5625,0.375,0.3125,0.625,0.75,0.5625,1,0.5625,0.8125,0.6875,0.8125,0.8125,0.6875,0.375,0.75,0.9375,0.625,0.8125,0.8125,0.9375,0.8125,0.8125,0.875,0.75,0.6875,0.8125,0.4375,0.75,0.25,0.75,0.4375,0.875,0.8125,0.8125,0.6875,0.75,0.8125,0.8125,0.375,0.8125,0.5625,0.375,0.375,0.625,0.75,0.4375,0.5625,0.75,0.875,0.8125,0.125,0.9375,0.875,0.8125,0.8125,0.8125,0.9375,0.625,0.8125] relative_absolute_error 0.5495097211571836 root_mean_prior_squared_error 0.09949872432040595 root_mean_squared_error 0.06873569261801483 root_relative_squared_error 0.6908198380179433 total_cost 0 area_under_roc_curve 0.9889868690788948 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area_under_roc_curve 0.9891260648037574 [0.996835,1,1,0.971519,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.993671,0.996835,1,0.974843,0.868671,1,0.949367,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,0.96519,1,0.974684,1,1,0.987421,1,0.943038,1,1,1,0.996835,1,0.968553,1,1,1,0.993711,0.987421,1,1,0.993671,0.996835,1,1,0.974684,1,0.96519,0.993671,1,1,0.996835,1,1,1,0.971519,1,0.962025,1,0.987342,0.993711,0.996835,0.898734,1,1,0.993711,1,0.808544,1,0.993711,1,1,1,1,1,1] area_under_roc_curve 0.9854169154525915 [0.993671,1,0.984177,1,1,1,0.984177,1,1,0.993671,1,1,1,0.987342,0.825949,1,0.981013,1,1,1,1,1,1,1,0.937107,0.993671,1,0.857595,1,1,0.993671,1,1,1,0.993671,1,1,1,0.893082,1,1,0.993711,0.930818,0.990506,0.85443,0.996835,1,1,1,1,1,1,0.996835,0.993671,0.971519,0.996835,1,1,1,1,1,1,1,1,1,0.943396,1,0.987421,1,0.946203,1,0.841772,1,0.987421,0.996835,0.993671,0.990506,1,0.996835,1,1,0.996835,0.993711,0.993671,1,1,1,1,0.96519,1,1,0.892405,1,1,1,1,1,1,1,0.993711] area_under_roc_curve 0.9757313062256188 [0.996835,1,0.974684,1,0.993711,1,1,0.990506,1,1,1,0.968553,1,1,0.993711,1,0.949367,0.996835,1,1,1,0.981132,1,1,0.981132,0.920886,0.996835,0.993711,1,1,1,1,1,1,0.993671,1,1,0.996835,0.993711,0.408805,1,1,0.89557,0.943038,0.993671,1,1,1,1,1,0.669304,0.981013,1,0.924528,0.981013,1,1,1,1,1,1,1,1,0.996835,1,0.993711,1,0.996835,1,0.981013,1,1,1,1,0.990506,1,0.993711,1,1,0.993671,0.981013,0.952532,0.377358,0.993711,1,1,0.901899,1,1,1,0.427673,1,1,0.993711,1,0.993711,0.993671,1,0.984177,1] area_under_roc_curve 0.9909904665233658 [1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,0.993711,1,0.993711,1,1,0.993711,1,0.702532,0.899371,1,1,0.962264,1,0.987342,1,0.996835,1,0.993671,1,1,1,1,0.996835,0.993671,1,0.946203,1,0.993671,1,1,1,0.993671,0.993711,1,1,0.996835,0.996835,1,0.958861,1,1,1,0.968553,0.996835,1,1,1,1,0.936709,0.996835,0.996835,1,1,1,1,1,1,1,1,1,0.987342,0.993671,0.987421,1,0.974843,0.981013,1,0.990506,0.993711,1,1,1,0.987342,0.996835,0.993671,1,1,1,1,1,1] area_under_roc_curve 0.983092632951198 [1,0.996835,0.996835,0.91195,1,0.996835,0.987421,1,1,1,0.927215,0.871835,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,0.901899,1,1,1,1,1,0.974843,1,1,1,1,0.89557,0.996835,0.996835,0.996835,1,1,1,0.984177,1,0.920886,0.996835,0.993711,1,0.993711,1,1,1,1,1,1,0.987421,1,0.981013,1,1,0.996835,1,1,1,0.987421,1,1,1,0.962025,0.867925,1,1,1,0.96519,1,0.993711,1,1,1,1,1,1,0.816456,0.993711,1,1,1,0.993671,1,1,1,0.27044,0.996835,1,0.981132,1,1,1,1,1] area_under_roc_curve 0.9912580357853675 [0.842767,1,0.936709,1,1,1,0.993711,0.996835,0.990506,1,0.977848,1,1,1,1,1,0.993711,0.987342,1,0.957278,1,0.993711,1,1,0.89557,0.993711,0.996835,0.987421,1,1,0.993711,1,0.946203,0.984177,1,0.993671,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.861635,0.996835,1,1,1,1,0.996835,0.996835,0.968354,1,1,0.996835,0.930818,0.974684,0.993711,0.949686,0.993671,1,1,1,0.962264,1,1,1,0.981013,1,1,1,1] area_under_roc_curve 0.9813495143698747 [0.943396,1,1,0.977848,0.990506,1,1,0.996835,0.993671,1,1,1,1,1,0.958861,0.996835,1,1,0.993711,1,1,1,0.993711,1,0.642405,0.993711,1,0.958861,1,1,0.996835,0.996835,0.993711,1,0.968553,0.993671,0.990506,1,1,1,0.91195,1,0.981013,0.962264,1,1,1,1,0.924051,0.990506,1,1,0.993711,0.990506,1,1,0.993671,0.996835,0.996835,1,1,0.996835,1,1,1,1,1,1,1,0.273585,0.996835,0.977848,1,0.996835,1,1,1,1,1,0.981132,1,0.987421,0.946203,1,1,1,1,1,1,1,1,0.987421,1,1,1,0.990506,1,0.5,1,0.993671] area_under_roc_curve 0.99128127349997 [1,1,0.93038,0.993631,0.894904,0.996815,0.926752,0.987342,0.993631,0.993631,1,0.964968,0.996815,1,1,1,0.987342,0.993671,1,1,1,0.993631,0.993671,0.996815,0.977707,1,1,0.933121,1,1,1,0.996815,1,0.987342,1,0.996815,1,1,0.993631,1,1,0.980892,0.993631,0.955696,1,0.962025,0.943038,1,0.974522,1,1,1,0.974684,1,0.974684,1,1,1,0.996815,0.984076,1,1,1,1,1,0.987261,1,1,0.996815,0.993671,0.996815,0.996815,1,1,1,1,0.987261,1,1,1,1,0.990446,1,0.984076,1,1,1,1,1,0.996815,1,0.981013,1,1,0.968153,1,1,1,0.981013,1] 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 0.7095157279867388 kappa 0.621137377165634 kappa 0.7094125078963993 kappa 0.6463390566410104 kappa 0.72203577210092 kappa 0.7031305514981644 kappa 0.7220247966516623 kappa 0.7030484915495183 kappa 0.6652983896431954 kappa 0.70749850029994 kb_relative_information_score 119.17902239876224 kb_relative_information_score 114.35107359557192 kb_relative_information_score 119.39416024529821 kb_relative_information_score 114.912440732304 kb_relative_information_score 116.90314586356192 kb_relative_information_score 120.59255667727217 kb_relative_information_score 118.6512279689924 kb_relative_information_score 117.2433282934195 kb_relative_information_score 117.67174515956317 kb_relative_information_score 117.90182504820221 mean_absolute_error 0.010508022321428268 mean_absolute_error 0.011249626984127434 mean_absolute_error 0.010949568452380593 mean_absolute_error 0.011187417658730044 mean_absolute_error 0.010954486111111647 mean_absolute_error 0.010363448908729795 mean_absolute_error 0.010616369047619178 mean_absolute_error 0.011103811011904517 mean_absolute_error 0.011196247519841553 mean_absolute_error 0.010672588599380986 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.01980002942907591 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.019799955856386102 mean_prior_absolute_error 0.01979995631910742 number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1] number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1] number_of_instances 160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1] number_of_instances 160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1] number_of_instances 160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2] number_of_instances 160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2] number_of_instances 159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2] predictive_accuracy 0.7125 predictive_accuracy 0.625 predictive_accuracy 0.7125 predictive_accuracy 0.65 predictive_accuracy 0.725 predictive_accuracy 0.70625 predictive_accuracy 0.725 predictive_accuracy 0.70625 predictive_accuracy 0.66875 predictive_accuracy 0.7106918238993711 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 recall 0.7125 [1,1,0,1,0.5,0.5,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,1,0.5,0,1,1,0,0.5,1,1,1,0,1,0,0,1,1,0,0.5,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,1,1,0,0.5,0,1,0,0,0,1,0.5,0,1,1,0.5,0.5,1,1,1,1] recall 0.625 [1,1,1,0,1,0,0.5,1,1,0.5,1,1,1,1,0.5,1,0.5,0,1,0.5,1,0.5,1,1,0,0,0,0,1,1,0,1,1,1,1,0,1,1,0,0.5,1,1,0,0.5,1,1,0,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0,1,0,0,0,1,0,1,0.5,1,1,0.5,0.5,0.5,0.5,1,0,1,0.5,0,0.5,1,1,0,0.5,1,1,1,0,1,0,1,1,0,1,0,1] recall 0.7125 [1,1,0,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,0.5,1,0,1,0.5,0,1,0.5,0.5,1,1,1,1,1,1,0.5,1,0,0.5,0.5,1,0.5,1,0.5,0,1,0.5,1,1,1,0.5,0,0,1,0,1,1,0,1,0.5,0.5,0.5,0,1,0.5,1,0.5,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,0,0,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.65 [0,1,0.5,1,0.5,0,0.5,1,1,0.5,1,1,1,0.5,0,1,0,1,0.5,1,1,0.5,1,1,0,0,1,0,1,1,0.5,1,1,1,0.5,0,1,1,0,1,1,0,0,0.5,0.5,0.5,0.5,1,1,1,1,1,0.5,0,0,0.5,1,1,1,1,1,1,1,1,0.5,0,1,0,1,0.5,1,0,1,0,0.5,0.5,0.5,1,0.5,1,1,1,0,0.5,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0] recall 0.725 [0.5,1,0.5,1,1,1,1,0.5,0,1,1,0,1,1,0,1,0,1,1,1,1,0,1,0,0,0.5,1,1,1,1,1,1,1,1,0.5,0,1,1,1,0,1,1,0.5,0,0.5,1,1,1,1,1,0,0.5,0.5,0,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,1,1,1,0,0.5,0,0,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,1,0,1] recall 0.70625 [1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0,1,1,1,1,0,0.5,0,0,1,1,0,1,0,1,0.5,1,1,1,1,1,1,0.5,0.5,0.5,0.5,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,0,0.5,1,1,0,0.5,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0.5,0,1,1,1,0,0.5,0.5,1,1,1,1,1,1] recall 0.725 [1,0.5,0.5,0,1,1,0,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,0.5,1,0.5,0,1,1,1,1,1,0,0,0,0.5,0.5,1,1,0,0.5,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0,0.5,0,1,1,1,0,1,0,0,0.5,0.5,1,1,1,0,0,0.5,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1] recall 0.70625 [0,1,0.5,0,1,0.5,1,1,0,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0,0.5,0,1,1,0,1,0.5,0,1,0,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,0,0,0,0.5,1,1,1,1,0.5,0.5,0,1,1,1,0,0.5,0,0,0,1,0.5,1,0,1,1,1,0.5,1,1,1,1] recall 0.66875 [0,1,1,0.5,0,1,0.5,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,0,1,1,0,1,0.5,0,1,1,0.5,0.5,0,1,0,0.5,0.5,1,0,1,0,0.5,0,0,0,1,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,0.5,1,0.5,0.5,1,1,0.5,0.5,0,1,0,1,1,1,1,1,1,1,0,1,0,0.5,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,0,1,0] recall 0.710691823899371 [0,1,0,0.5,0,0.5,0.5,0,0.5,0.5,1,0.5,0.5,1,1,1,0,0,1,1,1,0.5,0,1,0.5,1,1,0,1,1,1,0.5,1,1,1,0.5,1,1,0.5,0.5,1,0.5,0.5,0,1,0,0,1,0.5,1,0,1,0,1,0,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,0,1,0.5,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,1,1,0,1] relative_absolute_error 0.5307074092525066 relative_absolute_error 0.5681621345273152 relative_absolute_error 0.5530076857512841 relative_absolute_error 0.5650202540760653 relative_absolute_error 0.553256051984712 relative_absolute_error 0.5234076774664761 relative_absolute_error 0.5361814503336418 relative_absolute_error 0.5607997862441293 relative_absolute_error 0.5654683071543524 relative_absolute_error 0.5390208153682484 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.0994985414402977 root_mean_squared_error 0.06699080600777148 root_mean_squared_error 0.07241094728238698 root_mean_squared_error 0.0685745827396241 root_mean_squared_error 0.07066878814101073 root_mean_squared_error 0.06899633727884508 root_mean_squared_error 0.06707509314047544 root_mean_squared_error 0.0671290287827178 root_mean_squared_error 0.06818256046599945 root_mean_squared_error 0.06936148951264534 root_mean_squared_error 0.0677621762143767 root_relative_squared_error 0.67328181579388 root_relative_squared_error 0.7277561948423892 root_relative_squared_error 0.6891993444426641 root_relative_squared_error 0.7102468657268142 root_relative_squared_error 0.6934381300150165 root_relative_squared_error 0.674131436873958 root_relative_squared_error 0.6746735115890452 root_relative_squared_error 0.6852619251743306 root_relative_squared_error 0.6971106322722602 root_relative_squared_error 0.6810368798726177 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 6308.159239000133 usercpu_time_millis 6272.260943000219 usercpu_time_millis 6255.742684000097 usercpu_time_millis 6224.857186000008 usercpu_time_millis 6360.281068999939 usercpu_time_millis 6039.45799600001 usercpu_time_millis 6246.619948999978 usercpu_time_millis 6253.300066000065 usercpu_time_millis 6328.287901000067 usercpu_time_millis 6016.537476999929 usercpu_time_millis_testing 35.63068300013583 usercpu_time_millis_testing 35.832351000181006 usercpu_time_millis_testing 36.478535000014745 usercpu_time_millis_testing 35.96720999985337 usercpu_time_millis_testing 36.12344599991957 usercpu_time_millis_testing 36.479193999866766 usercpu_time_millis_testing 35.79546799983291 usercpu_time_millis_testing 38.171013000010134 usercpu_time_millis_testing 36.277438000070106 usercpu_time_millis_testing 36.55045899995457 usercpu_time_millis_training 6272.5285559999975 usercpu_time_millis_training 6236.428592000038 usercpu_time_millis_training 6219.264149000082 usercpu_time_millis_training 6188.889976000155 usercpu_time_millis_training 6324.157623000019 usercpu_time_millis_training 6002.978802000143 usercpu_time_millis_training 6210.824481000145 usercpu_time_millis_training 6215.129053000055 usercpu_time_millis_training 6292.010462999997 usercpu_time_millis_training 5979.987017999974