6001851 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) 4036583 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.3724528793077694 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 1 6902 min_samples_split 6 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 3854 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 "mean" 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 12926815 description https://api.openml.org/data/download/12926815/description.xml -1 12926816 predictions https://api.openml.org/data/download/12926816/predictions.arff area_under_roc_curve 0.9960327888257575 [0.992227,0.999842,1,1,0.999842,0.995048,0.999921,0.999684,0.998264,0.999803,0.999448,1,0.999211,0.986959,1,0.999882,0.999921,0.984612,0.9869,0.98183,0.999605,1,0.997751,1,0.998974,0.973248,0.991221,0.998619,0.99925,0.999842,0.999961,1,0.999684,0.987433,0.999211,0.999132,0.990866,0.989149,0.997948,0.999921,0.999132,0.999763,1,0.999487,0.999566,0.999566,0.999566,0.998698,0.995147,0.996449,0.997633,0.996173,0.997869,0.989189,0.997711,0.983862,1,0.999842,0.996607,0.990747,1,0.999566,0.995423,0.99779,0.999448,0.99637,0.982659,0.999961,0.991477,0.990787,0.994949,0.998619,0.994555,0.999724,0.95492,0.999527,1,0.994022,1,0.999842,0.99562,0.996646,0.998501,0.995896,0.997988,0.998343,1,0.994121,0.999132,1,0.999882,0.999605,0.998698,0.996962,0.999684,0.999645,0.997948,0.996488,0.967448,0.998816] average_cost 0 f_measure 0.8199075247674662 [0.709677,0.864865,1,1,0.967742,0.740741,0.969697,0.9375,0.909091,0.967742,0.866667,0.969697,0.823529,0.709677,1,0.933333,0.941176,0.709677,0.611111,0.26087,0.882353,1,0.875,1,0.810811,0.357143,0.421053,0.833333,0.875,0.941176,0.9375,1,0.909091,0.666667,0.9375,0.909091,0.451613,0.564103,0.857143,0.969697,0.75,0.9375,1,0.888889,0.941176,0.866667,0.827586,0.866667,0.8,0.903226,0.8,0.689655,0.787879,0.62069,0.8125,0.375,1,0.969697,0.648649,0.666667,0.969697,0.857143,0.666667,0.857143,0.848485,0.882353,0.518519,0.914286,0.709677,0.615385,0.642857,0.774194,0.628571,0.941176,0.8125,0.967742,0.969697,0.692308,1,0.967742,0.733333,0.709677,0.866667,0.709677,0.848485,0.933333,0.969697,0.764706,0.787879,1,0.914286,0.823529,0.9375,0.72,0.9375,0.8125,0.823529,0.764706,0.615385,0.83871] kappa 0.8219696969696969 kb_relative_information_score 1237.1687578128126 mean_absolute_error 0.01145354583333299 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 0.8269917673130922 [0.733333,0.761905,1,1,1,0.909091,0.941176,0.9375,0.882353,1,0.928571,0.941176,0.777778,0.733333,1,1,0.888889,0.733333,0.55,0.428571,0.833333,1,0.875,1,0.714286,0.416667,0.363636,0.75,0.875,0.888889,0.9375,1,0.882353,0.714286,0.9375,0.882353,0.466667,0.478261,0.789474,0.941176,0.75,0.9375,1,0.8,0.888889,0.928571,0.923077,0.928571,0.736842,0.933333,0.857143,0.769231,0.764706,0.692308,0.8125,0.375,1,0.941176,0.571429,0.714286,0.941176,0.789474,0.714286,0.789474,0.823529,0.833333,0.636364,0.842105,0.733333,0.8,0.75,0.8,0.578947,0.888889,0.8125,1,0.941176,0.9,1,1,0.785714,0.733333,0.928571,0.733333,0.823529,1,0.941176,0.722222,0.764706,1,0.842105,0.777778,0.9375,1,0.9375,0.8125,0.777778,0.722222,0.8,0.866667] predictive_accuracy 0.82375 prior_entropy 6.6438561897747395 recall 0.82375 [0.6875,1,1,1,0.9375,0.625,1,0.9375,0.9375,0.9375,0.8125,1,0.875,0.6875,1,0.875,1,0.6875,0.6875,0.1875,0.9375,1,0.875,1,0.9375,0.3125,0.5,0.9375,0.875,1,0.9375,1,0.9375,0.625,0.9375,0.9375,0.4375,0.6875,0.9375,1,0.75,0.9375,1,1,1,0.8125,0.75,0.8125,0.875,0.875,0.75,0.625,0.8125,0.5625,0.8125,0.375,1,1,0.75,0.625,1,0.9375,0.625,0.9375,0.875,0.9375,0.4375,1,0.6875,0.5,0.5625,0.75,0.6875,1,0.8125,0.9375,1,0.5625,1,0.9375,0.6875,0.6875,0.8125,0.6875,0.875,0.875,1,0.8125,0.8125,1,1,0.875,0.9375,0.5625,0.9375,0.8125,0.875,0.8125,0.5,0.8125] relative_absolute_error 0.5784619107743924 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.06573324174372441 root_relative_squared_error 0.6606439367201837 total_cost 0 area_under_roc_curve 0.9954932429742858 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.974684,0.987342,0.987421,1,1,0.993711,1,0.993711,0.990506,0.993671,1,1,1,0.996835,1,1,0.987342,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.987342,0.981013,1,1,0.993671,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.990506,1,1,0.968553,0.990506,1,0.993671,1,1,1,1,0.996835,1,1,1,1,1,1,0.996835,0.990506,1,0.996835,1,1,1,1,1,0.990506,1,1,1,0.996835,0.844937,1] area_under_roc_curve 0.9964055409601146 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.984177,1,1,1,0.96519,1,0.993711,1,1,1,1,1,0.958861,0.990506,0.993671,1,1,1,1,1,1,1,1,0.981132,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.977848,1,0.996835,1,0.974843,1,1,1,0.96519,1,1,1,0.996835,1,1,1,1,0.937107,1,1,1,1,1,1,1,1,0.981013,1,0.996835,0.993671,1,0.987421,0.993711,1,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,0.996835,1,1] area_under_roc_curve 0.99642544383409 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.993671,1,0.955696,1,1,0.990506,1,1,0.977848,1,1,1,1,1,1,1,0.968354,1,1,0.993711,0.974843,1,1,1,1,1,1,1,1,1,1,0.976266,1,1,1,1,0.996835,1,0.996835,1,1,0.987421,0.981013,1,1,1,1,1,1,0.987342,1,0.962264,0.990506,1,1,0.993711,1,1,1,1,0.985759,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.996835,0.95283,1] area_under_roc_curve 0.9958111913860364 [1,0.996835,1,1,1,0.984177,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.930818,0.984177,1,1,1,1,1,0.974684,0.977848,1,1,1,1,1,1,0.984177,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.981013,1,0.990506,1,1,1,0.984177,1,1,0.996835,1,0.996835,0.996835,0.955696,1,1,0.974684,0.984177,0.996835,0.981132,1,1,1,1,1,1,1,0.993711,1,1,0.993671,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.990506,0.996835,1,0.996835] area_under_roc_curve 0.9911081422657432 [0.993671,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.899371,1,1,1,1,1,0.990506,0.996835,1,1,1,1,0.977848,0.990506,1,1,1,1,1,1,0.962025,1,1,0.996835,0.962025,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.981132,0.993671,0.993711,0.974684,0.971519,1,0.996835,1,1,1,1,1,1,0.996835,1,0.962264,1,0.977848,0.977848,1,1,1,1,0.677215,1,1,0.981013,1,1,1,1,1,0.993671,0.981132,1,1,1,1,1,1,0.996835,1,0.993711,0.996835,1,0.996835,1,0.981132,0.996835] area_under_roc_curve 0.9964421124910438 [0.955696,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.952532,1,1,0.993671,1,0.996835,0.996835,0.981013,0.993711,1,1,1,1,0.993671,0.993671,0.993711,1,0.977848,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,0.984177,1,1,0.990506,1,1,1,0.987421,1,1,1,1,1,1,1,0.990506,1,1,1,0.981013,1,1,1,1,1,1,0.993671,1,0.993671,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.981132,0.993711,0.996835] area_under_roc_curve 0.9971198053498925 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.993711,1,1,1,0.993711,0.993671,0.977848,1,1,1,1,0.996835,0.90566,0.993711,0.993671,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.993671,1,0.990506,1,1,1,1,1,1,0.996835,0.990506,1,1,0.993671,0.993711,1,1,1,0.971519,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,1,1,0.943396,1,1,1,1,0.996835,1,1,1,1,1,0.987342,1] area_under_roc_curve 0.9966866690550112 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993711,0.987342,0.996835,1,1,1,1,1,0.924528,0.993711,1,0.987421,0.996835,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,0.971519,1,1,1,0.993711,1,0.996835,1,1,1,0.949686,0.955975,1,0.993671,0.993671,1,1,1,1,0.996835,1,1,1,1,1,0.981013,0.993711,0.996835,1,0.993671,0.990506,1,0.987421,1,1,1,1,1,0.987421,1,1,0.993671,1,0.993671,1] area_under_roc_curve 0.9973544104768728 [0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.962025,1,1,0.993711,1,1,0.996835,1,1,1,1,0.987421,1,1,1,1,0.971519,0.996835,0.981132,1,1,1,1,1,1,0.993671,1,1,1,0.990506,1,1,0.993711,1,0.987421,0.984177,1,1,0.996835,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,0.996835,1,1,1,1,0.987421,1,0.962025,1] area_under_roc_curve 0.9977489849534271 [0.993711,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.96519,1,1,1,1,0.977848,1,1,1,1,1,1,0.974843,1,1,1,1,1,1,1,0.993711,1,1,0.990506,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,1,0.996835,1,1,1,0.981013,1,1,1,0.993671,1,1,0.993711,1,1,0.987342,1,1,0.996835,1,1,1,1,1,0.968553,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] 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 0.8104864181933038 kappa 0.8736426456071076 kappa 0.7978681405448086 kappa 0.8168107702633345 kappa 0.7915021323645554 kappa 0.7978362157466635 kappa 0.8357094901465187 kappa 0.8294243070362474 kappa 0.842040832444813 kappa 0.8231066887783305 kb_relative_information_score 123.5235652696856 kb_relative_information_score 123.47692862400726 kb_relative_information_score 122.89584286913203 kb_relative_information_score 123.21073899539357 kb_relative_information_score 122.12856548767799 kb_relative_information_score 122.24959082847076 kb_relative_information_score 125.67805011137783 kb_relative_information_score 123.80090584049866 kb_relative_information_score 124.56329269078996 kb_relative_information_score 125.64127709577728 mean_absolute_error 0.011380979166666097 mean_absolute_error 0.011587604166666134 mean_absolute_error 0.011633083333333584 mean_absolute_error 0.011499958333332597 mean_absolute_error 0.011467999999999761 mean_absolute_error 0.011822666666666395 mean_absolute_error 0.011093458333332928 mean_absolute_error 0.011346458333333123 mean_absolute_error 0.011476895833332581 mean_absolute_error 0.011226354166666628 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 0.8125 predictive_accuracy 0.875 predictive_accuracy 0.8 predictive_accuracy 0.81875 predictive_accuracy 0.79375 predictive_accuracy 0.8 predictive_accuracy 0.8375 predictive_accuracy 0.83125 predictive_accuracy 0.84375 predictive_accuracy 0.825 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 0.8125 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0.5,0,1,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,0,1,1,0,1] recall 0.875 [1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1] recall 0.8 [0.5,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,0.5,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0,0.5,0.5,1,0,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0,1] recall 0.81875 [1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,0,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5] recall 0.79375 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0,0,0.5,0,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,0.5] recall 0.8 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,0,1,1,0.5,0,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.5] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0.5,0,1,1,1,0,0.5,1] recall 0.83125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,0.5,1,0,1,1,1,1,1,1,1,1,1,0,1,0.5,1,0.5,0.5,1,0,1,1,1,1,1,0,1,1,0.5,1,1,1] recall 0.84375 [0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,0.5,1,1,0,1,1,1,1,0.5,0.5,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,0,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,0,1,0.5,1] recall 0.825 [0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,0.5,0.5,0,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0,0,0,0,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] relative_absolute_error 0.5747969276093978 relative_absolute_error 0.5852325336700058 relative_absolute_error 0.5875294612794729 relative_absolute_error 0.5808059764309382 relative_absolute_error 0.5791919191919062 relative_absolute_error 0.5971043771043624 relative_absolute_error 0.560275673400652 relative_absolute_error 0.5730534511784395 relative_absolute_error 0.5796412037036647 relative_absolute_error 0.5669875841750812 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 0.06560189222795897 root_mean_squared_error 0.0658921417977452 root_mean_squared_error 0.06665449216961475 root_mean_squared_error 0.06598296447337272 root_mean_squared_error 0.0662458860357876 root_mean_squared_error 0.06731252989270099 root_mean_squared_error 0.0642321775972843 root_mean_squared_error 0.06562223531213449 root_mean_squared_error 0.06532985263899772 root_mean_squared_error 0.06439798917991862 root_relative_squared_error 0.6593238244165812 root_relative_squared_error 0.6622409423515602 root_relative_squared_error 0.6699028518736182 root_relative_squared_error 0.6631537445864468 root_relative_squared_error 0.6657962057131868 root_relative_squared_error 0.6765163798293057 root_relative_squared_error 0.6455576744171628 root_relative_squared_error 0.6595282801053353 root_relative_squared_error 0.6565897236750451 root_relative_squared_error 0.6472241435247176 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 7384.132007000062 usercpu_time_millis 7239.262049999979 usercpu_time_millis 7193.729832999907 usercpu_time_millis 7206.641981999383 usercpu_time_millis 7193.551054999716 usercpu_time_millis 7218.138082999758 usercpu_time_millis 7252.92459100001 usercpu_time_millis 7203.076040000269 usercpu_time_millis 7212.611003999882 usercpu_time_millis 7221.537007999814 usercpu_time_millis_testing 40.839753999989625 usercpu_time_millis_testing 35.938399999849935 usercpu_time_millis_testing 36.04726699995808 usercpu_time_millis_testing 35.77982199976759 usercpu_time_millis_testing 36.66761099975702 usercpu_time_millis_testing 38.33827700009351 usercpu_time_millis_testing 35.796468000171444 usercpu_time_millis_testing 36.6238980000162 usercpu_time_millis_testing 36.06063099960011 usercpu_time_millis_testing 35.865714000010485 usercpu_time_millis_training 7343.292253000072 usercpu_time_millis_training 7203.323650000129 usercpu_time_millis_training 7157.682565999949 usercpu_time_millis_training 7170.862159999615 usercpu_time_millis_training 7156.883443999959 usercpu_time_millis_training 7179.799805999664 usercpu_time_millis_training 7217.1281229998385 usercpu_time_millis_training 7166.452142000253 usercpu_time_millis_training 7176.550373000282 usercpu_time_millis_training 7185.671293999803