6027930 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) 4062615 bootstrap false 6902 class_weight null 6902 criterion "gini" 6902 max_depth null 6902 max_features 0.3189538637161444 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 16 6902 min_samples_split 19 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 1899 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 true 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 12978959 description https://api.openml.org/data/download/12978959/description.xml -1 12978960 predictions https://api.openml.org/data/download/12978960/predictions.arff area_under_roc_curve 0.9930535827020204 [0.98256,0.998619,0.999329,1,0.999645,0.993292,0.998382,0.99712,0.995896,0.999645,0.995857,0.998816,0.99925,0.987334,0.998974,0.997159,0.999882,0.98331,0.985519,0.974669,0.999171,0.999803,0.995147,1,0.997909,0.963344,0.978575,0.997317,0.987808,0.999763,0.99854,0.999171,0.994555,0.98836,0.998895,0.995147,0.987571,0.982442,0.996133,0.999171,0.999566,0.998895,0.998816,0.99779,0.996488,0.999684,0.996804,0.993687,0.993924,0.995818,0.996133,0.990096,0.995423,0.97964,0.99491,0.981652,0.999724,0.998698,0.987492,0.975655,0.999921,0.998343,0.991004,0.995028,0.996015,0.994555,0.976523,0.998619,0.968947,0.987019,0.990688,0.997475,0.988439,0.998974,0.97313,0.990688,0.999053,0.981929,0.998974,0.996567,0.988439,0.994792,0.998185,0.995344,0.9942,0.993411,1,0.989978,0.996804,0.999684,0.999724,0.998185,0.996686,0.986466,0.99637,0.996291,0.9942,0.990372,0.962831,0.996528] average_cost 0 f_measure 0.6579344169175053 [0.333333,0.769231,0.941176,0.969697,0.864865,0.692308,0.787879,0.774194,0.742857,0.914286,0.736842,0.8,0.697674,0.521739,0.914286,0.758621,0.8,0.516129,0.444444,0.071429,0.833333,0.866667,0.64,0.969697,0.722222,0.210526,0.16,0.758621,0.777778,0.875,0.875,0.83871,0.823529,0.457143,0.833333,0.585366,0.5,0.45,0.785714,0.8,0.810811,0.903226,0.717949,0.685714,0.642857,0.823529,0.736842,0.666667,0.6875,0.666667,0.8125,0.5625,0.777778,0.4,0.625,0.333333,0.914286,0.727273,0,0.56,0.914286,0.744186,0.466667,0.736842,0.634146,0.666667,0.275862,0.551724,0.2,0.434783,0.3,0.764706,0.457143,0.967742,0.5,0.285714,0.810811,0.666667,0.842105,0.769231,0.347826,0.594595,0.8125,0.590909,0.666667,0.785714,0.914286,0.615385,0.666667,0.857143,0.761905,0.769231,0.785714,0.3,0.875,0.733333,0.62069,0.380952,0.210526,0.647059] kappa 0.6786616161616161 kb_relative_information_score 1052.9906710856694 mean_absolute_error 0.014940893494486773 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 0.6869474573700581 [0.5,0.652174,0.888889,0.941176,0.761905,0.9,0.764706,0.8,0.684211,0.842105,0.636364,0.736842,0.555556,0.857143,0.842105,0.846154,0.666667,0.533333,0.545455,0.083333,0.75,0.928571,0.888889,0.941176,0.65,0.666667,0.222222,0.846154,0.7,0.875,0.875,0.866667,0.777778,0.421053,0.75,0.48,0.45,0.375,0.916667,0.736842,0.714286,0.933333,0.608696,0.631579,0.75,0.777778,0.636364,0.647059,0.6875,0.6,0.8125,0.5625,0.7,0.555556,0.625,0.5,0.842105,0.705882,0,0.777778,0.842105,0.592593,0.5,0.636364,0.52,0.538462,0.307692,0.615385,0.5,0.714286,0.75,0.722222,0.421053,1,0.75,0.6,0.714286,1,0.727273,1,0.571429,0.52381,0.8125,0.464286,0.647059,0.916667,0.842105,0.521739,0.565217,0.789474,0.615385,0.652174,0.916667,0.75,0.875,0.785714,0.692308,0.8,0.666667,0.611111] predictive_accuracy 0.681875 prior_entropy 6.6438561897747395 recall 0.681875 [0.25,0.9375,1,1,1,0.5625,0.8125,0.75,0.8125,1,0.875,0.875,0.9375,0.375,1,0.6875,1,0.5,0.375,0.0625,0.9375,0.8125,0.5,1,0.8125,0.125,0.125,0.6875,0.875,0.875,0.875,0.8125,0.875,0.5,0.9375,0.75,0.5625,0.5625,0.6875,0.875,0.9375,0.875,0.875,0.75,0.5625,0.875,0.875,0.6875,0.6875,0.75,0.8125,0.5625,0.875,0.3125,0.625,0.25,1,0.75,0,0.4375,1,1,0.4375,0.875,0.8125,0.875,0.25,0.5,0.125,0.3125,0.1875,0.8125,0.5,0.9375,0.375,0.1875,0.9375,0.5,1,0.625,0.25,0.6875,0.8125,0.8125,0.6875,0.6875,1,0.75,0.8125,0.9375,1,0.9375,0.6875,0.1875,0.875,0.6875,0.5625,0.25,0.125,0.6875] relative_absolute_error 0.7545905805296336 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08004915586301634 root_relative_squared_error 0.8045242872191001 total_cost 0 area_under_roc_curve 0.992051787278083 [0.993711,0.996835,1,1,1,1,1,1,0.993671,0.993711,0.987342,0.996835,0.996835,0.981013,1,1,1,0.977848,0.962025,0.993711,1,1,0.993711,1,0.993711,0.990506,0.949367,1,0.977848,1,0.987342,1,0.987342,0.984177,1,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.968354,0.993671,1,0.987421,0.993671,1,1,1,1,0.987421,0.993671,1,1,1,0.990506,1,1,0.987342,1,1,1,0.974684,1,0.974684,1,1,0.996835,1,0.977848,1,1,0.987342,1,1,1,0.981013,0.987342,1,1,0.993671,1,1,1,1,0.993671,1,0.987342,1,0.993671,0.857595,1] area_under_roc_curve 0.9927717737441286 [0.962264,1,1,1,1,0.993711,1,1,1,1,1,0.993671,1,0.968354,1,1,1,0.974684,0.993671,0.987421,1,1,0.993711,1,1,0.949367,0.987342,0.996835,1,1,1,1,1,0.996835,0.996835,0.987421,0.981132,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.968354,1,1,0.993711,0.968553,1,1,1,0.898734,1,0.987421,0.996835,0.990506,1,0.996835,1,1,0.899371,1,0.993671,1,0.996835,1,1,0.996835,1,0.952532,1,0.987342,0.984177,1,0.987421,0.993711,0.996835,1,1,1,1,1,0.996835,1,1,0.990506,1,1,1,0.971519,0.987342,1] area_under_roc_curve 0.9937574635777405 [0.996835,1,1,1,0.996835,0.993671,1,1,0.990506,1,1,1,1,0.993671,1,1,1,0.987342,0.987421,0.920886,0.993711,0.993711,0.993671,1,0.993711,0.993671,1,1,1,1,1,1,0.996835,0.974684,1,1,0.993711,0.949686,1,1,0.996835,1,1,1,0.996835,1,0.993671,1,0.977848,1,0.996835,1,1,0.996835,1,1,1,1,0.962264,0.952532,1,0.987421,0.996835,1,0.993671,0.987342,0.993671,1,0.987421,0.974684,0.993671,1,0.993711,1,1,1,1,0.984177,0.993671,1,1,1,1,1,1,1,1,0.996835,0.993671,1,1,1,1,0.971519,1,1,0.996835,0.981013,0.968553,0.987342] area_under_roc_curve 0.9944284392166225 [0.971519,1,1,1,1,0.993671,1,1,0.996835,1,0.993671,1,1,0.993671,1,1,1,1,0.930818,0.987342,1,1,1,1,0.993711,0.990506,0.971519,1,0.996835,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.917722,1,0.990506,1,0.996835,1,0.996835,1,1,0.993671,1,0.996835,1,0.946203,0.993671,1,0.996835,0.993671,1,0.993711,1,0.987421,0.990506,1,0.981013,1,1,0.981132,1,1,0.993671,1,0.987421,1,1,1,1,1,1,0.987421,0.996835,1,1,0.987342,0.996835,0.987421,0.984177] area_under_roc_curve 0.9922948511265023 [0.990506,1,1,1,1,0.993671,1,0.996835,1,1,0.993671,0.990506,1,0.962264,1,0.996835,1,0.996835,0.993711,0.987342,1,1,1,1,0.996835,0.984177,0.990506,1,1,1,1,1,1,0.977848,1,1,1,0.93038,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.962264,0.996835,0.993711,0.981013,0.987342,1,0.990506,0.993671,0.981132,1,1,1,1,0.993671,1,0.955975,0.996835,0.962025,0.958861,0.996835,1,1,1,0.889241,1,1,0.981013,1,1,1,1,0.990506,0.993671,0.981132,0.981132,1,1,1,1,1,0.990506,1,0.987421,0.974684,1,0.996835,1,0.987421,0.993671] area_under_roc_curve 0.9934785745561658 [0.955696,1,1,1,1,0.990506,1,0.993671,1,1,0.996835,1,1,0.993711,1,1,1,0.996835,1,0.946203,1,1,1,1,0.996835,0.984177,0.96519,1,1,1,1,1,0.981013,0.996835,0.987421,0.993671,0.974684,0.993671,1,1,1,0.996835,1,1,0.993711,1,1,0.974684,1,0.996835,1,1,0.996835,1,0.993671,0.987342,1,1,0.984177,1,1,1,0.987421,1,1,1,0.987421,1,0.968354,1,0.984177,0.990506,1,1,0.968354,0.981132,1,0.981013,1,1,0.993711,0.993671,1,0.996835,1,1,1,0.993711,0.977848,1,1,0.993671,0.981132,1,1,1,1,0.987421,0.974843,0.996835] area_under_roc_curve 0.9955840498367963 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.993671,1,0.993711,0.993671,0.974684,0.993671,1,0.993671,1,0.993671,0.91195,0.981132,0.993671,1,1,1,1,1,0.955975,1,1,1,1,1,1,1,1,1,1,0.981132,0.996835,0.993671,0.990506,1,1,0.993711,1,1,1,0.990506,1,1,1,0.993671,0.993711,1,1,1,0.996835,0.996835,1,0.962264,0.996835,0.993671,1,0.993711,1,1,1,1,0.987421,1,1,1,1,0.974684,1,1,1,1,0.996835,1,0.90566,1,1,1,1,0.984177,0.987421,1,1,1,0.993711,0.987342,1] area_under_roc_curve 0.9929367188121961 [1,1,1,1,1,0.996835,1,1,0.993711,1,0.987421,1,1,1,0.987421,0.993671,1,0.987421,0.974684,0.993671,1,1,1,1,1,0.974843,0.987421,1,0.861635,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,0.996835,1,0.996835,1,1,0.993711,1,0.981132,0.993671,0.981013,1,0.996835,0.958861,1,1,0.974684,0.974843,1,0.996835,1,1,1,0.955975,0.981132,1,0.96519,0.981013,1,1,1,1,0.984177,1,1,1,1,1,0.977848,0.993711,1,0.996835,1,0.968354,1,0.987421,1,1,1,1,1,0.924528,1,0.990506,0.987342,0.987421,0.968354,1] area_under_roc_curve 0.9937238774779079 [0.993711,1,1,1,1,0.993711,0.990506,0.981132,1,1,0.993711,1,1,1,0.996835,1,1,1,1,1,1,1,0.955975,1,1,0.899371,0.981132,1,1,1,1,1,1,1,1,1,0.996835,0.981013,0.996835,0.987421,1,0.993671,0.996835,1,1,1,1,0.993671,0.987421,1,1,0.987342,1,0.96519,0.996835,0.962264,1,1,0.993671,0.984177,1,1,1,0.993671,1,1,0.974684,1,0.955696,0.987421,1,0.981132,0.968354,0.996835,0.990506,0.971519,1,1,1,0.996835,0.990506,0.974843,1,0.993711,1,1,1,0.993671,0.993711,1,1,0.996835,1,1,1,0.993671,0.993711,1,0.971519,1] area_under_roc_curve 0.9941622382772071 [0.943396,1,0.974843,1,1,0.993711,1,0.968553,0.996835,1,1,1,1,0.993671,1,1,1,0.974843,0.990506,1,1,1,1,1,1,0.880503,0.993711,0.996835,0.996835,1,1,1,1,1,0.996835,0.993671,0.971519,0.987342,0.993671,1,1,1,1,1,0.996835,1,1,0.990506,0.993711,1,1,1,1,0.981013,1,0.974843,1,0.993711,0.993671,0.996835,1,1,0.971519,0.984177,1,1,0.993671,1,0.987342,0.981132,0.981132,1,0.977848,1,0.996835,0.990506,1,0.993711,1,0.990506,1,0.981132,1,0.968553,0.996835,1,1,0.987342,1,0.996835,1,0.996835,0.996835,1,1,1,0.981132,1,1,1] 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 0.6463669732012473 kappa 0.7094583925469762 kappa 0.6464088397790055 kappa 0.6715875898002684 kappa 0.6715097915350601 kappa 0.7156959526159921 kappa 0.7283745903904615 kappa 0.6652455392389073 kappa 0.6651794527579263 kappa 0.6652983896431954 kb_relative_information_score 104.1021811334494 kb_relative_information_score 106.00216267027871 kb_relative_information_score 105.13024007486965 kb_relative_information_score 105.32414908699977 kb_relative_information_score 104.98404786790738 kb_relative_information_score 105.48246628593668 kb_relative_information_score 107.44574613283179 kb_relative_information_score 104.48219649156921 kb_relative_information_score 105.31473799804533 kb_relative_information_score 104.72274334378055 mean_absolute_error 0.015028557689550807 mean_absolute_error 0.014819471249993868 mean_absolute_error 0.014996708524509239 mean_absolute_error 0.015028868265044081 mean_absolute_error 0.014829449879874057 mean_absolute_error 0.01493685194418159 mean_absolute_error 0.014714761147751587 mean_absolute_error 0.014948001295983832 mean_absolute_error 0.015030249002203993 mean_absolute_error 0.015076015945774771 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 0.65 predictive_accuracy 0.7125 predictive_accuracy 0.65 predictive_accuracy 0.675 predictive_accuracy 0.675 predictive_accuracy 0.71875 predictive_accuracy 0.73125 predictive_accuracy 0.66875 predictive_accuracy 0.66875 predictive_accuracy 0.66875 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 0.65 [1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0,1,1,1,0,0.5,0,1,0,0,1,0,0,0,1,0.5,0,0.5,1,0.5,0,1,0,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,0,1,0,1,1,0,0.5,1,1,0,1,1,1,0,0,0,1,0,1,0,1,1,0.5,1,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,0,1,0.5,0,1] recall 0.7125 [0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,0.5,1,1,1,0,0.5,1,1,0,1,0.5,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,0,0,0,1,1,1,0,0,0.5,0.5,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,0,1] recall 0.65 [0,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,0,1,0,0,1,1,0,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0.5,1,0.5,1,0.5,1,1,0,1,0.5,1,1,0,0,1,1,0.5,1,0.5,1,0,0,0,0.5,0,1,0,1,0,0.5,1,0.5,1,0.5,0,1,0.5,0.5,1,1,1,0.5,1,1,1,1,0,0,1,1,0.5,0.5,0,0.5] recall 0.675 [0,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,1,0.5,1,1,0,0.5,0,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0,0.5,1,1,0.5,1,1,1,0,1,0,0,0,1,1,1,0,0.5,1,0.5,1,0.5,1,0.5,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,0,0] recall 0.675 [0,1,1,1,1,1,1,0.5,1,1,1,0.5,0,0,1,0.5,1,1,1,0,1,1,0.5,1,0.5,0.5,0,1,1,0.5,1,0,1,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,1,0,1,1,1,0,1,0.5,1,0,0,0,0.5,0.5,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,0,0.5,1,0.5,0,0,0.5] recall 0.71875 [0,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,0,0.5,0.5,1,0,1,1,0.5,0,1,1,1,1,0,1,0.5,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0,1,1,1,1,1,0,0.5,0,0.5,1,1,0.5,0,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,0,1,1,1,0,0,1,1,1,0,0,1] recall 0.73125 [0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,0.5,1,0.5,1,0.5,0,0,0.5,1,1,0.5,0,1,1,1,1,0.5,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0,1,1,0,0.5,0.5,1,0.5,0,0,1,1,1,1,0.5,1,0,0.5,0.5,0.5,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,0,1,1,0.5,1,0,0,1] recall 0.66875 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0,1,0.5,0.5,1,1,0,0,0.5,0,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0,0.5,0.5,1,0.5,0,1,1,0,0,1,1,1,1,1,0,1,0.5,0,0,0,1,0.5,1,0.5,0,1,1,1,1,0,0,0,1,0,0.5,1,0,1,1,1,1,1,0,1,0.5,0,0,0,0.5] recall 0.66875 [0,1,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0.5,0.5,0,1,0.5,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,0.5,0.5,0,1,0,0,0.5,1,1,0.5,0.5,1,1,0.5,1,0.5,0,1,0,0,0.5,0.5,0,1,0,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,0,0.5,0,0,0.5,1] recall 0.66875 [0,0.5,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,0.5,0.5,0.5,0.5,1,1,1,1,0.5,0.5,0.5,1,1,0,1,1,1,1,0,0.5,0,1,0,0,0.5,1,1,0,0.5,1,1,0.5,0,0,0,0,0,0,1,0,0,1,1,1,0.5,0.5,0,1,0,1,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,0.5,0.5,1] relative_absolute_error 0.7590180651288274 relative_absolute_error 0.7484581439390829 relative_absolute_error 0.7574095214398594 relative_absolute_error 0.7590337507598008 relative_absolute_error 0.7489621151451531 relative_absolute_error 0.7543864618273518 relative_absolute_error 0.7431697549369476 relative_absolute_error 0.7549495604032227 relative_absolute_error 0.7591034849597963 relative_absolute_error 0.7614149467563003 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 0.08078776177853501 root_mean_squared_error 0.07933646780722761 root_mean_squared_error 0.08013051873954337 root_mean_squared_error 0.08036197239964545 root_mean_squared_error 0.07989268994166857 root_mean_squared_error 0.07991579467112382 root_mean_squared_error 0.07884131518616143 root_mean_squared_error 0.07990565308361144 root_mean_squared_error 0.08027632903036172 root_mean_squared_error 0.08102010740209298 root_relative_squared_error 0.8119475559758047 root_relative_squared_error 0.7973615027535881 root_relative_squared_error 0.8053420148957797 root_relative_squared_error 0.807668211704607 root_relative_squared_error 0.8029517455415615 root_relative_squared_error 0.8031839568097001 root_relative_squared_error 0.7923850316686257 root_relative_squared_error 0.8030820300201331 root_relative_squared_error 0.8068074634570437 root_relative_squared_error 0.814282717354662 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 1483.6645159994077 usercpu_time_millis 1343.070634000469 usercpu_time_millis 1363.960861999658 usercpu_time_millis 1356.310677001602 usercpu_time_millis 1372.9063870014215 usercpu_time_millis 1362.752883000212 usercpu_time_millis 1332.4880029977066 usercpu_time_millis 1337.301278999803 usercpu_time_millis 1338.6256949961535 usercpu_time_millis 1363.8907919958 usercpu_time_millis_testing 31.286006000300404 usercpu_time_millis_testing 32.08893600094598 usercpu_time_millis_testing 32.83774800001993 usercpu_time_millis_testing 32.28295100052492 usercpu_time_millis_testing 32.2510890000558 usercpu_time_millis_testing 31.614835999789648 usercpu_time_millis_testing 32.451332997879945 usercpu_time_millis_testing 33.29811699950369 usercpu_time_millis_testing 32.01766299753217 usercpu_time_millis_testing 32.25145999749657 usercpu_time_millis_training 1452.3785099991073 usercpu_time_millis_training 1310.981697999523 usercpu_time_millis_training 1331.123113999638 usercpu_time_millis_training 1324.027726001077 usercpu_time_millis_training 1340.6552980013657 usercpu_time_millis_training 1331.1380470004224 usercpu_time_millis_training 1300.0366699998267 usercpu_time_millis_training 1304.0031620002992 usercpu_time_millis_training 1306.6080319986213 usercpu_time_millis_training 1331.6393319983035