5996933 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) 4031666 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.6716768941155856 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 13 6902 min_samples_split 13 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 61817 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 12916999 description https://api.openml.org/data/download/12916999/description.xml -1 12917000 predictions https://api.openml.org/data/download/12917000/predictions.arff area_under_roc_curve 0.9886710858585859 [0.977667,0.998461,0.999763,0.999724,0.996252,0.988202,0.997909,0.995857,0.995778,0.998343,0.996883,0.997396,0.994397,0.976997,0.996922,0.992858,0.999645,0.973879,0.975773,0.960701,0.997356,0.998303,0.988952,1,0.989781,0.956795,0.973288,0.989504,0.996488,0.998737,0.99925,0.999882,0.993253,0.980508,0.993924,0.997909,0.976681,0.979443,0.997593,0.999566,0.970486,0.995186,0.999211,0.995462,0.995344,0.982678,0.997869,0.990925,0.978496,0.982047,0.98114,0.984257,0.993647,0.962831,0.990175,0.958688,1,0.998974,0.992424,0.980508,0.999171,0.995423,0.993174,0.995857,0.995502,0.990688,0.97021,0.999763,0.946654,0.96295,0.981179,0.997356,0.989149,0.995344,0.964449,0.988913,0.998501,0.963068,0.998501,0.998106,0.98911,0.990175,0.989228,0.992898,0.990609,0.971788,0.999605,0.988636,0.995896,0.998816,0.998619,0.998737,0.992148,0.983467,0.9942,0.995818,0.993016,0.989228,0.956045,0.984138] average_cost 0 f_measure 0.6043093066100977 [0.482759,0.769231,0.941176,0.866667,0.764706,0.533333,0.8,0.857143,0.645161,0.774194,0.625,0.764706,0.634146,0.4,0.722222,0.592593,0.810811,0.375,0.5,0,0.65,0.8125,0.484848,1,0.540541,0.105263,0.342857,0.588235,0.857143,0.8,0.615385,0.914286,0.685714,0.428571,0.702703,0.7,0.378378,0.388889,0.64,0.810811,0.516129,0.702703,0.857143,0.666667,0.666667,0.5,0.684211,0.64,0.642857,0.8,0.533333,0.551724,0.647059,0.333333,0.466667,0.148148,0.914286,0.756757,0.444444,0.518519,0.833333,0.585366,0.5625,0.722222,0.684211,0.514286,0.275862,0.820513,0.347826,0.25,0.32,0.717949,0.526316,0.764706,0.454545,0.785714,0.789474,0.1,0.882353,0.866667,0.615385,0.5,0.611111,0.37037,0.628571,0.756757,0.866667,0.540541,0.592593,0.75,0.744186,0.780488,0.615385,0.105263,0.56,0.65,0.606061,0.466667,0,0.571429] kappa 0.6224747474747474 kb_relative_information_score 1066.1594975132646 mean_absolute_error 0.014398638976724998 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 0.6149599922529522 [0.538462,0.652174,0.888889,0.928571,0.722222,0.571429,0.736842,0.789474,0.666667,0.8,0.625,0.722222,0.52,0.555556,0.65,0.727273,0.714286,0.375,0.5,0,0.541667,0.8125,0.470588,1,0.47619,0.333333,0.315789,0.555556,0.789474,0.736842,0.8,0.842105,0.631579,0.5,0.619048,0.583333,0.333333,0.35,0.888889,0.714286,0.533333,0.619048,0.789474,0.647059,0.647059,0.583333,0.590909,0.888889,0.75,0.857143,0.571429,0.615385,0.611111,0.5,0.5,0.181818,0.842105,0.666667,0.4,0.636364,0.75,0.48,0.5625,0.65,0.590909,0.473684,0.307692,0.695652,0.571429,0.375,0.444444,0.608696,0.454545,0.722222,0.833333,0.916667,0.681818,0.25,0.833333,0.928571,0.8,0.583333,0.55,0.454545,0.578947,0.666667,0.928571,0.47619,0.727273,0.75,0.592593,0.64,0.8,0.333333,0.777778,0.541667,0.588235,0.5,0,0.666667] predictive_accuracy 0.62625 prior_entropy 6.6438561897747395 recall 0.62625 [0.4375,0.9375,1,0.8125,0.8125,0.5,0.875,0.9375,0.625,0.75,0.625,0.8125,0.8125,0.3125,0.8125,0.5,0.9375,0.375,0.5,0,0.8125,0.8125,0.5,1,0.625,0.0625,0.375,0.625,0.9375,0.875,0.5,1,0.75,0.375,0.8125,0.875,0.4375,0.4375,0.5,0.9375,0.5,0.8125,0.9375,0.6875,0.6875,0.4375,0.8125,0.5,0.5625,0.75,0.5,0.5,0.6875,0.25,0.4375,0.125,1,0.875,0.5,0.4375,0.9375,0.75,0.5625,0.8125,0.8125,0.5625,0.25,1,0.25,0.1875,0.25,0.875,0.625,0.8125,0.3125,0.6875,0.9375,0.0625,0.9375,0.8125,0.5,0.4375,0.6875,0.3125,0.6875,0.875,0.8125,0.625,0.5,0.75,1,1,0.5,0.0625,0.4375,0.8125,0.625,0.4375,0,0.5] relative_absolute_error 0.7272039887234834 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.07876530099801671 root_relative_squared_error 0.7916210603328088 total_cost 0 area_under_roc_curve 0.9886924309370271 [1,1,1,1,0.996835,1,1,1,0.996835,1,1,0.987342,0.987342,0.958861,1,1,1,0.96519,0.955696,0.981132,1,0.993711,0.993711,1,0.993711,0.990506,0.981013,0.996835,0.996835,0.993711,1,1,0.990506,0.981013,1,0.987421,1,0.993711,1,1,1,1,1,1,1,0.996835,1,1,1,0.968354,0.892405,1,1,0.987342,1,0.993711,1,1,0.987421,0.974684,1,1,0.996835,0.993671,1,1,0.996835,1,1,0.955975,0.968354,1,0.987342,0.996835,1,1,1,0.981013,0.996835,1,1,0.990506,0.993711,1,0.990506,0.851266,1,0.993671,0.993671,0.987421,1,1,1,0.984177,1,0.990506,1,0.996835,0.85443,1] area_under_roc_curve 0.9898871009473769 [0.987421,1,1,1,1,1,0.993671,1,0.996835,1,0.993671,1,0.993671,0.949367,1,1,1,0.943038,0.996835,0.987421,1,1,0.993711,1,1,0.946203,0.987342,0.955696,0.996835,1,1,1,1,0.990506,0.996835,1,0.924528,1,0.993711,1,0.993711,1,1,1,1,0.987342,1,1,0.990506,1,1,0.939873,1,0.987342,0.993711,0.937107,1,1,1,0.933544,1,1,1,0.993671,1,1,0.993671,1,0.893082,1,0.990506,1,0.990506,1,1,1,1,0.943038,1,1,0.987342,0.993671,0.962264,0.987421,1,1,0.993671,0.996835,0.977848,1,0.996835,1,1,0.968354,0.993671,0.996835,1,0.974684,0.993671,1] area_under_roc_curve 0.9884608112411433 [0.984177,0.996835,1,1,0.990506,0.977848,0.993711,1,0.981013,0.996835,0.996835,1,1,0.993671,0.977848,0.990506,1,0.987342,0.937107,0.898734,1,0.981132,0.946203,1,0.949686,0.984177,1,1,1,1,1,1,1,0.96519,0.987421,1,0.993711,0.949686,1,1,0.984177,1,1,1,0.993671,1,0.996835,1,0.873418,0.996835,0.990506,1,1,0.974684,1,0.993671,1,0.996835,0.987421,0.984177,1,0.987421,0.993671,1,0.996835,0.968354,0.987342,1,0.981132,0.936709,1,0.993671,0.981132,0.993671,1,1,1,0.962025,0.996835,1,1,1,1,0.996835,1,1,1,0.996835,1,1,0.996835,1,0.993711,0.981013,0.993671,1,0.990506,0.987342,0.987421,0.996835] area_under_roc_curve 0.9886600887668177 [0.993671,0.996835,1,1,0.993671,0.974684,1,1,0.993671,0.996835,1,0.996835,1,1,1,1,1,0.981013,0.855346,0.987342,1,1,0.996835,1,0.962264,0.968354,0.927215,1,1,1,1,1,1,0.993671,1,0.987421,1,1,1,1,0.990506,1,1,1,1,1,1,1,0.987342,1,0.993671,1,0.987421,0.927215,1,0.996835,1,1,1,0.993671,1,1,1,1,0.990506,0.993671,0.952532,1,1,0.905063,0.987342,0.993671,0.993711,1,0.993711,0.946203,1,0.924051,1,0.996835,0.955975,0.977848,1,0.987342,1,1,1,1,1,1,1,1,0.968553,0.993671,1,0.981132,0.977848,0.993671,0.987421,0.946203] area_under_roc_curve 0.9856181832656633 [0.987342,1,1,1,0.993711,0.987342,0.993711,1,1,1,0.993671,0.993671,1,0.874214,1,0.990506,1,0.996835,0.993711,0.990506,0.981013,0.993671,1,1,0.996835,0.952532,0.993671,1,1,1,1,1,0.984177,0.946203,1,1,0.987342,0.943038,0.990506,1,1,0.996835,0.987421,1,1,0.993711,1,0.987342,1,0.993671,0.993711,0.962264,0.990506,0.981132,0.968354,0.914557,1,0.990506,0.993671,0.981132,1,1,1,1,0.996835,1,0.880503,1,0.781646,0.96519,1,1,1,0.987421,0.901899,1,0.993671,0.943038,1,1,1,1,0.993671,0.996835,0.981132,1,1,1,1,1,1,0.993671,0.993711,0.987421,0.984177,1,0.993671,1,0.987421,0.974684] area_under_roc_curve 0.9863635458960273 [0.908228,1,1,1,1,0.987342,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,1,0.93038,1,0.996835,0.974684,1,0.990506,0.987342,0.974684,0.993711,1,1,1,1,0.974684,0.990506,0.962264,1,0.933544,0.984177,1,1,1,0.968354,1,1,1,1,1,0.993671,0.977848,0.920886,1,0.974843,1,1,0.984177,0.939873,1,1,1,1,1,0.993671,0.968553,1,1,1,0.974843,1,0.974684,1,0.920886,0.990506,1,1,0.870253,1,0.996835,0.968354,1,0.993711,1,0.987342,1,0.990506,0.993711,1,1,0.974843,0.987342,1,1,0.996835,0.955975,0.993711,1,1,0.996835,0.962264,0.987421,0.955696] area_under_roc_curve 0.9909616073561018 [0.987342,1,1,1,1,1,1,1,0.993711,1,1,1,0.971519,0.981132,0.993711,0.990506,0.987421,0.949686,0.984177,0.981013,0.987342,0.993671,1,1,0.984177,0.855346,0.993711,0.977848,1,1,1,1,1,0.993711,1,1,0.993671,0.996835,1,0.987421,0.981013,0.996835,1,0.996835,1,0.993671,0.987342,0.981013,1,1,0.987421,0.993671,0.996835,0.974843,0.996835,0.974684,1,1,0.993671,0.981132,1,0.996835,1,0.974684,1,0.987421,0.949686,1,0.987342,0.968354,0.993711,1,0.996835,1,0.993671,1,1,0.974843,1,1,0.984177,1,0.974684,0.996835,1,1,1,0.962264,1,1,1,1,0.987342,0.974843,0.981132,0.990506,1,0.987421,0.939873,1] area_under_roc_curve 0.990443386274978 [1,1,1,1,1,0.987342,0.996835,1,0.993711,1,0.993711,1,1,1,1,0.984177,1,0.949686,0.990506,0.936709,0.990506,1,1,1,0.996835,0.962264,0.924528,0.984177,1,0.996835,1,1,1,1,1,1,0.984177,0.977848,1,1,1,1,1,0.993671,1,0.993671,1,1,0.993711,1,0.981132,0.981013,0.977848,1,0.996835,0.958861,1,1,0.990506,1,1,0.993671,0.993711,0.996835,1,0.974843,0.962264,1,0.96519,0.987342,0.993711,1,1,0.955975,0.984177,1,1,0.974843,1,1,0.987342,1,0.962025,0.996835,0.971519,0.955696,1,0.974843,1,1,1,0.996835,0.996835,0.974843,0.993711,1,0.984177,0.993711,0.958861,0.984177] area_under_roc_curve 0.9917109505612608 [0.968553,1,1,1,1,1,0.993671,1,1,1,0.987421,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.962264,1,0.987342,1,1,1,1,0.987421,0.996835,1,0.993671,0.943038,1,1,0.786164,1,1,0.984177,0.987342,0.971519,1,0.996835,0.974843,1,1,0.996835,1,0.882911,0.987342,0.955975,1,1,0.996835,0.990506,0.996835,0.996835,1,1,1,1,0.987342,1,0.981013,0.987421,1,0.993711,0.977848,1,0.996835,0.981013,1,1,1,0.996835,1,0.993711,0.993711,0.993711,0.993671,1,1,0.981013,1,1,1,1,1,0.987342,0.987421,0.990506,0.987421,0.993671,0.993671,1] area_under_roc_curve 0.9929421921025394 [0.968553,0.996835,0.993711,1,1,0.993711,1,0.937107,0.996835,1,1,1,0.993671,0.987342,0.996835,1,1,0.993711,0.990506,0.993711,1,1,1,1,1,0.842767,1,0.996835,0.990506,1,1,1,1,0.974843,0.996835,0.996835,0.987342,1,1,1,0.987421,1,1,0.996835,1,0.93038,1,0.990506,1,0.993711,1,0.990506,1,0.984177,0.993671,0.924528,1,1,0.987342,1,1,0.993671,0.974684,1,0.987421,1,0.993671,1,0.993671,0.955975,0.968553,1,0.977848,1,0.993671,0.996835,1,0.993711,0.981132,1,1,0.962264,1,0.974843,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711] 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 0.6337372222441489 kappa 0.6589832649194821 kappa 0.595895816890292 kappa 0.6525721504994275 kappa 0.5957681983262276 kappa 0.5894844872503355 kappa 0.5956404991312588 kappa 0.6021314387211367 kappa 0.646269245953415 kappa 0.65254471512615 kb_relative_information_score 107.3209532029916 kb_relative_information_score 106.25807155976071 kb_relative_information_score 105.1316859563904 kb_relative_information_score 105.16713543951181 kb_relative_information_score 105.67174589312356 kb_relative_information_score 104.72445235039646 kb_relative_information_score 107.05227052705727 kb_relative_information_score 106.88330562245626 kb_relative_information_score 109.36667025499172 kb_relative_information_score 108.58320670658524 mean_absolute_error 0.014313132870455849 mean_absolute_error 0.014468236898037732 mean_absolute_error 0.014469201838028464 mean_absolute_error 0.014535485286705651 mean_absolute_error 0.014381092686288394 mean_absolute_error 0.01444383592316357 mean_absolute_error 0.014470672351896006 mean_absolute_error 0.014353416234693286 mean_absolute_error 0.014212484884969318 mean_absolute_error 0.014338830793011615 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 0.6375 predictive_accuracy 0.6625 predictive_accuracy 0.6 predictive_accuracy 0.65625 predictive_accuracy 0.6 predictive_accuracy 0.59375 predictive_accuracy 0.6 predictive_accuracy 0.60625 predictive_accuracy 0.65 predictive_accuracy 0.65625 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 0.6375 [1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,0,0,1,0,0,1,1,0,0,1,0.5,0,0.5,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0.5,1,1,0,1,0,1,1,1,0.5,1,1,0,0.5,1,0.5,0.5,1,0,0,0,1,0.5,1,1,1,1,0,1,1,0.5,0.5,1,0,1,0.5,1,0.5,0,0,1,1,1,0.5,0.5,0.5,1,0.5,0,1] recall 0.6625 [1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0.5,1,1,1,0,0.5,0,1,1,0,1,1,0.5,0.5,0,1,1,0.5,1,1,0.5,0.5,1,0,1,0,1,1,1,1,1,0.5,0,1,0,0,1,0.5,0.5,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0,1,1,0,0,0,0,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,0,0,1] recall 0.6 [0,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0.5,0.5,0,1,0.5,0,0,1,0,0.5,1,0,0,0.5,1,1,1,0,1,1,0,0,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0.5,0.5,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,1,0,0,0.5,1,0,0.5,0,0.5,1,0,0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0.5,1,0.5,0.5,0,0.5] recall 0.65625 [0.5,1,1,1,0.5,0,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0,0,1,0.5,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,0,0,1,1,1,1,0,0.5,1,1,1,1,0.5,1,0,1,0,0.5,0,0.5,1,1,0,0.5,1,0,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,0,0,1,0,0.5,0.5,0,0] recall 0.6 [0.5,1,1,1,1,0.5,0,1,1,1,0.5,0.5,1,0,1,0.5,1,1,1,0,0.5,0.5,1,1,1,0,0.5,1,1,1,0,1,0,0,1,1,1,0,0,1,1,0.5,1,1,1,0,1,0,0.5,0.5,0,0,0.5,0,0,0,1,0.5,1,0,1,1,1,1,0.5,0,0,1,0,0.5,0,1,1,0,0,1,0.5,0,1,1,0,1,0.5,0,0,1,1,1,1,1,1,1,1,0,0.5,1,0.5,1,0,0.5] recall 0.59375 [0,1,1,0.5,1,0.5,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,0,1,1,0.5,1,0.5,0,0.5,1,1,1,0,1,0.5,0.5,0,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,0,1,1,0,0,1,1,0,1,0.5,0.5,0,1,1,0.5,0,1,0.5,0.5,0.5,1,1,1,0,0,1,0,1,0,1,0,1,0.5,0,1,0,0,0,1,1,1,0,0,0,1,0.5,0,0,0.5] recall 0.6 [0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0,0,0.5,0,0,0.5,0,1,1,0.5,1,0.5,0,0,0,1,1,0.5,1,1,0,1,1,0,1,0.5,0,0,0.5,1,0.5,0,0.5,0.5,0.5,1,1,0,0.5,0.5,0,0.5,0,1,0.5,0.5,0,1,0.5,1,0.5,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,0.5,0,0,0,1,1,0.5,0,0,0.5,1,0,0,0.5] recall 0.60625 [1,1,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0,1,0.5,1,0,0.5,0,0.5,1,0.5,1,0.5,0,0,0.5,1,1,0,1,1,1,1,1,0,0,1,1,0.5,1,1,0,1,0.5,1,1,1,1,0,0.5,0.5,1,0.5,0,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0,0,0,1,1,0,0,1,1,0,1,1,0,0,0,0.5,0,0.5,1,0,1,1,1,1,0,0,0,1,0.5,1,0,0.5] recall 0.65 [0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,0.5,0,0,1,0.5,0,1,1,0,1,0,0,0,1,1,0.5,0,1,1,0.5,0.5,1,1,0,1,0.5,0,0,0,0.5,1,0.5,0.5,1,1,1,0.5,1,1,1,0,0.5,1,1,0.5,0,1,1,1,0,0,0,1,0,0.5,0,1] recall 0.65625 [0,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,0.5,0,1,0,0.5,0,1,1,1,1,0.5,0,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,0,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0.5,0.5,0.5,0,1,1,0,1,1,0.5,0,1,1,1,0,1,0.5,0,0,1,0,1,0,0.5,1,0,1,0.5,1,0,1,0,1,1,1,1,0,0.5,1,1,1,0,1,1,1,0.5,0,0] relative_absolute_error 0.7228854985078699 relative_absolute_error 0.7307190352544296 relative_absolute_error 0.7307677695973959 relative_absolute_error 0.7341154185204863 relative_absolute_error 0.7263178124388067 relative_absolute_error 0.7294866627860377 relative_absolute_error 0.7308420379745445 relative_absolute_error 0.7249200118531951 relative_absolute_error 0.717802266917641 relative_absolute_error 0.7241833733844237 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 0.07800984792766356 root_mean_squared_error 0.0786786306782386 root_mean_squared_error 0.07939437932793893 root_mean_squared_error 0.0791778001909607 root_mean_squared_error 0.0790105131766116 root_mean_squared_error 0.07944131728515516 root_mean_squared_error 0.07936265522304148 root_mean_squared_error 0.07857455890621666 root_mean_squared_error 0.07747453062613038 root_mean_squared_error 0.07850472769524344 root_relative_squared_error 0.784028471299223 root_relative_squared_error 0.7907499908444329 root_relative_squared_error 0.7979435354361284 root_relative_squared_error 0.7957668332095352 root_relative_squared_error 0.7940855354553087 root_relative_squared_error 0.7984152796558617 root_relative_squared_error 0.7976246961853566 root_relative_squared_error 0.7897040301806021 root_relative_squared_error 0.7786483299871896 root_relative_squared_error 0.7890022001034679 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 7102.1598810002615 usercpu_time_millis 6928.397249999762 usercpu_time_millis 6880.319194999174 usercpu_time_millis 6817.889874000684 usercpu_time_millis 6843.169843998112 usercpu_time_millis 6826.403444998505 usercpu_time_millis 6839.086585998302 usercpu_time_millis 6888.643756999954 usercpu_time_millis 6869.785174998469 usercpu_time_millis 6999.598336999043 usercpu_time_millis_testing 34.258572000908316 usercpu_time_millis_testing 33.18105000107607 usercpu_time_millis_testing 33.16534599980514 usercpu_time_millis_testing 33.359888000632054 usercpu_time_millis_testing 32.92691099886724 usercpu_time_millis_testing 33.20104799968249 usercpu_time_millis_testing 32.95185099887021 usercpu_time_millis_testing 33.128814000519924 usercpu_time_millis_testing 33.06646999953955 usercpu_time_millis_testing 33.095533999585314 usercpu_time_millis_training 7067.901308999353 usercpu_time_millis_training 6895.216199998686 usercpu_time_millis_training 6847.153848999369 usercpu_time_millis_training 6784.529986000052 usercpu_time_millis_training 6810.242932999245 usercpu_time_millis_training 6793.202396998822 usercpu_time_millis_training 6806.134734999432 usercpu_time_millis_training 6855.514942999434 usercpu_time_millis_training 6836.71870499893 usercpu_time_millis_training 6966.502802999457