5976882 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) 4011615 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.44223410820422193 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 12 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 24486 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 12877111 description https://api.openml.org/data/download/12877111/description.xml -1 12877112 predictions https://api.openml.org/data/download/12877112/predictions.arff area_under_roc_curve 0.9932496843434341 [0.980193,0.999487,0.999961,1,0.999053,0.991714,0.999448,0.998382,0.996252,0.999724,0.997356,0.999448,0.997711,0.983507,0.999092,0.997711,0.999961,0.981771,0.98548,0.970644,0.99925,0.999605,0.992622,1,0.996686,0.96441,0.983349,0.994476,0.996686,0.999645,0.999763,1,0.994003,0.986545,0.99491,0.998461,0.985835,0.988439,0.998816,0.999842,0.993687,0.998224,0.999842,0.997988,0.998422,0.998895,0.998698,0.99562,0.990688,0.994515,0.991635,0.992069,0.996173,0.978259,0.992306,0.972735,1,0.99929,0.994713,0.980627,1,0.997869,0.993095,0.997199,0.997751,0.993568,0.975418,1,0.978378,0.985717,0.989978,0.997988,0.990846,0.998619,0.968119,0.996173,0.99925,0.978101,0.999448,0.999448,0.992266,0.994949,0.991951,0.994042,0.996962,0.98986,0.999921,0.992266,0.996804,1,0.999803,0.999487,0.99633,0.98694,0.998067,0.998619,0.996054,0.993134,0.959951,0.995975] average_cost 0 f_measure 0.7080567986716444 [0.538462,0.888889,1,0.941176,0.933333,0.580645,0.857143,0.810811,0.709677,0.967742,0.62069,0.848485,0.717949,0.5,0.941176,0.8,0.8,0.48,0.555556,0.181818,0.810811,0.933333,0.709677,1,0.731707,0.2,0.363636,0.756757,0.848485,0.864865,0.848485,0.969697,0.848485,0.551724,0.769231,0.7,0.529412,0.512821,0.909091,0.888889,0.666667,0.8,0.882353,0.727273,0.764706,0.83871,0.83871,0.774194,0.758621,0.774194,0.625,0.666667,0.742857,0.384615,0.645161,0.181818,1,0.909091,0.571429,0.538462,0.914286,0.717949,0.689655,0.8,0.769231,0.666667,0.222222,0.864865,0.454545,0.416667,0.6,0.769231,0.5,0.888889,0.48,0.866667,0.842105,0.3,0.909091,0.967742,0.571429,0.666667,0.75,0.666667,0.823529,0.875,0.969697,0.529412,0.666667,1,0.820513,0.780488,0.714286,0.3,0.709677,0.705882,0.787879,0.516129,0.111111,0.689655] kappa 0.7241161616161617 kb_relative_information_score 1088.3407666027224 mean_absolute_error 0.014389284038757964 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 0.725481690392735 [0.7,0.8,1,0.888889,1,0.6,0.789474,0.714286,0.733333,1,0.692308,0.823529,0.608696,0.75,0.888889,0.857143,0.666667,0.666667,0.5,0.333333,0.714286,1,0.733333,1,0.6,0.5,0.352941,0.666667,0.823529,0.761905,0.823529,0.941176,0.823529,0.615385,0.652174,0.583333,0.5,0.434783,0.882353,0.8,0.6,0.736842,0.833333,0.705882,0.722222,0.866667,0.866667,0.8,0.846154,0.8,0.625,0.714286,0.684211,0.5,0.666667,0.333333,1,0.882353,0.526316,0.7,0.842105,0.608696,0.769231,0.736842,0.652174,0.6,0.272727,0.761905,0.833333,0.625,0.642857,0.652174,0.416667,0.8,0.666667,0.928571,0.727273,0.75,0.882353,1,0.666667,0.818182,0.75,0.714286,0.777778,0.875,0.941176,0.5,0.818182,1,0.695652,0.64,0.833333,0.75,0.733333,0.666667,0.764706,0.533333,0.5,0.769231] predictive_accuracy 0.726875 prior_entropy 6.6438561897747395 recall 0.726875 [0.4375,1,1,1,0.875,0.5625,0.9375,0.9375,0.6875,0.9375,0.5625,0.875,0.875,0.375,1,0.75,1,0.375,0.625,0.125,0.9375,0.875,0.6875,1,0.9375,0.125,0.375,0.875,0.875,1,0.875,1,0.875,0.5,0.9375,0.875,0.5625,0.625,0.9375,1,0.75,0.875,0.9375,0.75,0.8125,0.8125,0.8125,0.75,0.6875,0.75,0.625,0.625,0.8125,0.3125,0.625,0.125,1,0.9375,0.625,0.4375,1,0.875,0.625,0.875,0.9375,0.75,0.1875,1,0.3125,0.3125,0.5625,0.9375,0.625,1,0.375,0.8125,1,0.1875,0.9375,0.9375,0.5,0.5625,0.75,0.625,0.875,0.875,1,0.5625,0.5625,1,1,1,0.625,0.1875,0.6875,0.75,0.8125,0.5,0.0625,0.625] relative_absolute_error 0.7267315171089866 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.07744304211967383 root_relative_squared_error 0.7783318585898406 total_cost 0 area_under_roc_curve 0.9920525336358571 [1,1,1,1,0.996835,1,1,1,0.996835,1,0.996835,0.996835,1,0.962025,1,1,1,0.96519,0.96519,0.974843,1,1,1,1,1,0.987342,0.993671,1,0.993671,1,0.996835,1,0.996835,0.990506,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.968354,0.946203,1,0.987421,0.990506,1,1,1,1,0.993711,0.987342,1,1,1,1,1,1,0.993671,1,1,0.968553,0.984177,1,0.987342,1,1,1,1,0.977848,1,1,1,1,1,1,0.996835,0.939873,1,0.996835,0.990506,1,1,1,1,0.981013,1,1,1,0.993671,0.835443,1] area_under_roc_curve 0.9938383190032638 [0.987421,1,1,1,1,1,0.996835,1,1,1,0.996835,1,0.990506,0.962025,1,1,1,0.977848,0.993671,0.993711,1,1,1,1,1,0.952532,0.987342,0.971519,1,1,1,1,1,0.996835,0.996835,0.993711,0.949686,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.96519,1,1,0.993711,0.949686,1,1,1,0.943038,1,1,1,0.993671,1,1,0.996835,1,0.937107,1,0.996835,1,0.993671,1,1,1,1,0.971519,1,0.996835,0.993671,0.993671,0.974843,0.993711,1,1,1,0.993671,0.996835,1,1,1,1,0.987342,0.996835,1,1,0.987342,1,1] area_under_roc_curve 0.9932424767136375 [0.996835,1,1,1,0.996835,0.984177,1,1,0.984177,1,1,1,1,0.996835,0.996835,1,1,0.990506,0.993711,0.93038,1,1,0.955696,1,0.974843,0.971519,1,1,0.996835,1,1,1,1,0.971519,0.993711,1,0.993711,0.943396,1,1,1,1,1,1,0.996835,1,0.996835,1,0.962025,1,0.996835,1,1,0.990506,1,1,1,1,0.987421,0.958861,1,0.993711,0.993671,1,1,0.981013,0.987342,1,0.981132,0.977848,0.996835,0.996835,0.993711,0.996835,1,1,1,0.977848,1,1,1,0.996835,1,0.996835,1,1,1,0.996835,0.996835,1,1,1,0.993711,0.984177,1,1,0.993671,0.996835,0.981132,1] area_under_roc_curve 0.9927685395271076 [0.996835,0.996835,1,1,0.996835,0.990506,1,1,0.993671,1,0.996835,1,1,1,1,1,1,0.984177,0.91195,0.990506,1,1,1,1,0.993711,0.962025,0.955696,1,1,1,1,1,1,0.990506,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.993711,0.936709,1,0.990506,1,1,1,0.990506,1,1,0.993671,1,0.993671,0.993671,0.955696,1,1,0.955696,0.990506,0.993671,0.981132,1,1,0.977848,1,0.962025,1,1,0.981132,0.984177,1,0.987342,1,1,1,1,1,1,1,1,0.968553,1,1,0.993711,0.993671,0.996835,1,0.974684] area_under_roc_curve 0.9909546413502108 [0.984177,1,1,1,1,0.996835,1,1,1,1,0.996835,0.996835,1,0.930818,1,1,1,1,1,0.990506,0.993671,1,1,1,0.996835,0.962025,0.984177,1,1,1,1,1,0.996835,0.974684,1,1,0.987342,0.990506,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.981132,0.996835,0.981132,0.955696,0.949367,1,0.990506,0.993671,0.974843,1,1,1,1,0.996835,1,0.874214,1,0.924051,0.993671,1,1,0.993711,1,0.860759,1,0.996835,0.968354,1,1,1,1,0.996835,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,0.987421,0.990506,1,0.996835,1,0.955975,0.993671] area_under_roc_curve 0.9913432449645729 [0.901899,1,1,1,1,0.984177,1,1,1,0.996835,0.996835,1,1,1,1,0.996835,1,0.996835,1,0.933544,1,1,0.984177,1,0.993671,0.990506,0.977848,0.993711,1,1,1,1,0.952532,0.993671,0.949686,1,0.958861,0.984177,1,1,1,0.984177,1,1,1,1,1,0.996835,0.987342,0.977848,1,1,1,1,0.990506,0.96519,1,1,0.996835,1,1,0.993671,0.987421,1,1,1,0.981132,1,0.990506,1,0.977848,0.990506,1,1,0.952532,1,1,0.984177,1,1,1,0.984177,1,0.993671,1,1,1,0.981132,0.987342,1,1,1,0.993711,1,1,1,1,0.974843,0.981132,0.990506] area_under_roc_curve 0.9945545736804391 [1,1,1,1,1,1,1,1,0.993711,1,1,1,0.987342,0.987421,1,0.990506,1,0.987421,0.996835,0.96519,0.993671,1,1,1,0.993671,0.861635,0.987421,0.981013,1,1,1,1,1,0.974843,1,1,0.990506,1,1,1,0.993671,1,1,1,1,0.993671,0.993671,0.987342,1,1,1,1,1,1,0.996835,0.996835,1,1,0.993671,0.993711,1,1,1,0.977848,1,0.993711,0.968553,1,0.996835,0.990506,0.993711,1,0.996835,1,0.996835,1,1,0.981132,1,1,0.990506,1,0.990506,1,1,1,1,0.968553,1,1,1,1,0.987342,0.974843,1,1,1,0.993711,0.952532,1] area_under_roc_curve 0.9946685176339466 [1,1,1,1,1,0.993671,1,1,1,1,0.993711,1,1,1,1,0.996835,1,0.981132,0.990506,0.987342,1,1,1,1,1,0.974843,0.974843,0.993671,1,0.996835,1,1,1,1,1,1,0.981013,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,0.987342,1,1,0.936709,1,1,0.990506,1,1,0.993671,0.993711,1,1,0.962264,0.962264,1,0.987342,0.987342,1,1,1,1,0.987342,1,1,0.974843,1,1,0.984177,1,0.96519,0.996835,0.990506,0.981013,1,0.993711,1,1,1,1,1,0.974843,1,1,0.987342,1,0.974684,1] area_under_roc_curve 0.9959330964891331 [0.962264,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.996835,1,1,1,1,0.993711,1,1,0.993671,0.987342,1,1,0.955975,1,1,0.990506,1,0.993671,1,1,0.993711,1,1,0.993671,1,0.933544,1,0.955975,1,1,0.996835,1,1,1,1,1,1,1,0.996835,1,0.990506,0.981132,1,0.993711,0.974684,1,0.993671,0.987342,1,1,1,0.996835,0.996835,1,1,1,1,1,1,0.987342,1,1,1,1,1,0.981013,0.987421,0.996835,0.993711,0.996835,0.990506,1] area_under_roc_curve 0.99660805270281 [0.974843,1,1,1,1,1,1,0.987421,0.996835,1,1,1,0.996835,0.990506,1,1,1,0.987421,0.993671,0.993711,1,1,1,1,1,0.949686,1,1,0.993671,1,1,1,1,0.974843,0.996835,0.996835,0.987342,1,0.996835,1,0.993711,1,1,0.996835,1,1,1,0.996835,1,1,1,0.993671,1,0.984177,1,0.987421,1,1,0.993671,1,1,1,0.974684,1,0.987421,1,1,1,1,0.993711,0.981132,1,0.987342,1,0.993671,0.996835,1,1,0.981132,1,1,0.981132,1,0.974843,1,1,0.996835,0.990506,1,1,1,1,1,1,1,1,1,1,1,1] 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 0.7157632939876041 kappa 0.7726285872182529 kappa 0.6652983896431954 kappa 0.7094469227428842 kappa 0.7283424149095791 kappa 0.6841689696012634 kappa 0.7409367348550667 kappa 0.7346076379289918 kappa 0.7409571947559628 kappa 0.7472753119570368 kb_relative_information_score 108.34812718764775 kb_relative_information_score 108.79071115079627 kb_relative_information_score 107.44472673011552 kb_relative_information_score 108.25050730103841 kb_relative_information_score 108.01654180798438 kb_relative_information_score 107.28218863690584 kb_relative_information_score 110.13165127144181 kb_relative_information_score 109.51476565456876 kb_relative_information_score 110.49725220061683 kb_relative_information_score 110.06429466160695 mean_absolute_error 0.014370277102367846 mean_absolute_error 0.014395545740441199 mean_absolute_error 0.014525834595083633 mean_absolute_error 0.014499193409784209 mean_absolute_error 0.01432813962878996 mean_absolute_error 0.014507123328128568 mean_absolute_error 0.014249760113871215 mean_absolute_error 0.014279658553473486 mean_absolute_error 0.014317729475725974 mean_absolute_error 0.014419578439913459 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 0.71875 predictive_accuracy 0.775 predictive_accuracy 0.66875 predictive_accuracy 0.7125 predictive_accuracy 0.73125 predictive_accuracy 0.6875 predictive_accuracy 0.74375 predictive_accuracy 0.7375 predictive_accuracy 0.74375 predictive_accuracy 0.75 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 0.71875 [1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,0,1,0,1,1,1,0,0,1,0.5,1,1,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,0.5,0.5,1,0.5,0,1,1,1,1,0.5,1,0,1,0.5,0,1] recall 0.775 [0,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,0,1,1,0.5,1,1,1,1,0.5,1,0.5,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0,0,1] recall 0.66875 [0.5,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,0,0.5,1,0,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0.5,1,0,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,0,0,0.5,1,0,1,0,1,1,0,0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0,1,1,0.5,0.5,0,0.5] recall 0.7125 [0.5,1,1,1,1,0,1,1,0.5,1,0,0.5,1,0.5,1,1,1,0.5,0,0,1,1,0.5,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,0,1,0,0.5,0,0.5,0,1,1,0.5,1,0,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,0,0,1,0,1,1,0,0] recall 0.73125 [0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,1,1,0,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,0,0,0,0,0,0,1,0.5,1,0,1,1,1,1,1,0,0,1,0.5,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0,0.5] recall 0.6875 [0,1,1,1,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,0,1,0.5,1,0,0.5,0.5,0.5,1,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,0,1,1,0.5,0,1,1,0,1,1,0.5,0,1,1,1,0,1,0.5,0.5,0.5,1,1,1,0,1,1,0,1,1,1,0,1,0.5,1,1,1,0,0,1,1,1,0,1,0.5,1,1,0,0,0.5] recall 0.74375 [0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,0.5,1,0,1,0.5,1,1,0.5,1,1,0,0,0.5,1,1,0.5,1,1,0,1,1,0.5,1,1,1,0.5,0.5,1,1,1,0.5,0.5,0.5,1,1,0,1,1,0,0.5,0.5,1,1,0,0,1,1,1,0.5,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0.5,0,1,0.5,1,0,0,1] recall 0.7375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,0,1,0,1,1,0.5,1,1,0,0,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,0,1,1,0.5,1,1,0.5,1,1,1,0,0,1,0,1,0,1,1,1,0,1,1,0,1,1,0,0,0,1,0.5,0.5,1,0,1,1,1,1,1,0,0,1,0.5,1,0,1] recall 0.74375 [0,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0.5,0.5,0.5,1,1,0,1,1,0.5,1,0,0.5,0,1,1,0.5,0,1,1,0.5,0.5,1,1,0,1,0.5,0,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0,0,0,1,0,0.5,0.5,1] recall 0.75 [0,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0,1,0.5,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,1,0,0.5,0,1,1,1,0.5,1,1,0,1,1,1,0.5,1,0.5,0,0,1,0.5,1,0,0.5,1,0,1,1,1,0,1,0,1,1,1,0.5,0,1,1,1,1,0.5,1,1,1,0.5,0,0] relative_absolute_error 0.7257715708266577 relative_absolute_error 0.7270477646687462 relative_absolute_error 0.7336280098527075 relative_absolute_error 0.7322824954436455 relative_absolute_error 0.7236434155954514 relative_absolute_error 0.7326829963701285 relative_absolute_error 0.7196848542359188 relative_absolute_error 0.7211948764380537 relative_absolute_error 0.7231176502891894 relative_absolute_error 0.7282615373693653 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 0.07729352033222983 root_mean_squared_error 0.07732122369475425 root_mean_squared_error 0.07822259156091682 root_mean_squared_error 0.07777413753232472 root_mean_squared_error 0.0773762581693923 root_mean_squared_error 0.07827390561503945 root_mean_squared_error 0.07688645719312465 root_mean_squared_error 0.07698220905326247 root_mean_squared_error 0.07675426399297611 root_mean_squared_error 0.07753001373034353 root_relative_squared_error 0.7768291080839771 root_relative_squared_error 0.7771075373534458 root_relative_squared_error 0.7861666252629748 root_relative_squared_error 0.7816594926915709 root_relative_squared_error 0.7776606546349875 root_relative_squared_error 0.7866823509114498 root_relative_squared_error 0.7727379696039889 root_relative_squared_error 0.773700312007188 root_relative_squared_error 0.7714093779532947 root_relative_squared_error 0.7792059561656113 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 5605.972623000071 usercpu_time_millis 5542.473944000221 usercpu_time_millis 5598.849026999915 usercpu_time_millis 5682.362812000065 usercpu_time_millis 5703.29671200011 usercpu_time_millis 5700.167487000272 usercpu_time_millis 5713.273281999818 usercpu_time_millis 5722.658256000159 usercpu_time_millis 5731.617814000174 usercpu_time_millis 5749.752551000256 usercpu_time_millis_testing 41.25723900006051 usercpu_time_millis_testing 39.68293700017966 usercpu_time_millis_testing 40.984627999932854 usercpu_time_millis_testing 41.015745000095194 usercpu_time_millis_testing 40.75161600007959 usercpu_time_millis_testing 40.92011100010495 usercpu_time_millis_testing 41.080556999986584 usercpu_time_millis_testing 41.05417000005218 usercpu_time_millis_testing 45.30403800004024 usercpu_time_millis_testing 40.987166000149955 usercpu_time_millis_training 5564.71538400001 usercpu_time_millis_training 5502.791007000042 usercpu_time_millis_training 5557.864398999982 usercpu_time_millis_training 5641.34706699997 usercpu_time_millis_training 5662.545096000031 usercpu_time_millis_training 5659.247376000167 usercpu_time_millis_training 5672.192724999832 usercpu_time_millis_training 5681.604086000107 usercpu_time_millis_training 5686.313776000134 usercpu_time_millis_training 5708.765385000106