6007225 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) 4041939 bootstrap false 6902 class_weight null 6902 criterion "gini" 6902 max_depth null 6902 max_features 0.4175265032157014 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 6 6902 min_samples_split 2 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 55692 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 12937569 description https://api.openml.org/data/download/12937569/description.xml -1 12937570 predictions https://api.openml.org/data/download/12937570/predictions.arff area_under_roc_curve 0.9947259706439395 [0.989149,0.999645,0.999842,1,0.999645,0.996528,0.998737,0.999645,0.99858,0.999882,0.997356,0.999527,1,0.986821,0.999961,0.998816,0.999842,0.981929,0.991083,0.984296,0.999803,1,0.996094,1,0.998106,0.963029,0.984099,0.998343,0.996765,1,0.999527,0.998126,0.995936,0.986506,0.999329,0.99708,0.991398,0.982599,0.99779,0.999408,0.99929,0.999132,0.998303,0.998185,0.998895,0.999566,0.997514,0.998185,0.99562,0.993016,0.997633,0.993647,0.996843,0.982915,0.996686,0.978141,0.999487,0.99858,0.991083,0.960997,1,0.99925,0.991734,0.995265,0.998382,0.995226,0.982994,0.999092,0.981337,0.990017,0.992227,0.997514,0.995462,1,0.979956,0.999053,0.999408,0.991556,0.99925,0.998698,0.99491,0.995305,0.998224,0.994634,0.996488,0.996409,0.999566,0.991122,0.998816,0.999842,0.999487,0.99858,0.997317,0.993884,0.996291,0.996962,0.997751,0.993095,0.969184,0.999369] average_cost 0 f_measure 0.7427430532944764 [0.689655,0.864865,0.969697,0.967742,0.914286,0.764706,0.823529,0.903226,0.827586,0.9375,0.8125,0.903226,0.8,0.642857,0.941176,0.827586,0.888889,0.5,0.451613,0.357143,0.823529,0.9375,0.705882,0.969697,0.787879,0.272727,0.3125,0.727273,0.848485,0.969697,0.848485,0.866667,0.875,0.466667,0.941176,0.666667,0.484848,0.444444,0.848485,0.903226,0.864865,0.941176,0.742857,0.8,0.848485,0.903226,0.774194,0.8125,0.647059,0.705882,0.823529,0.645161,0.645161,0.592593,0.666667,0.4,0.969697,0.8,0.432432,0.4,1,0.8,0.625,0.6875,0.857143,0.684211,0.424242,0.705882,0.434783,0.62069,0.56,0.8125,0.645161,0.969697,0.642857,0.857143,0.823529,0.769231,0.9375,0.827586,0.709677,0.666667,0.727273,0.516129,0.628571,0.714286,0.933333,0.529412,0.823529,0.9375,0.810811,0.857143,0.83871,0.666667,0.866667,0.6875,0.6875,0.740741,0.454545,0.888889] kappa 0.7462121212121212 kb_relative_information_score 1190.1097913603003 mean_absolute_error 0.012157903932178638 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 0.7532785592030943 [0.769231,0.761905,0.941176,1,0.842105,0.722222,0.777778,0.933333,0.923077,0.9375,0.8125,0.933333,0.736842,0.75,0.888889,0.923077,0.8,0.5,0.466667,0.416667,0.777778,0.9375,0.666667,0.941176,0.764706,0.5,0.3125,0.705882,0.823529,0.941176,0.823529,0.928571,0.875,0.5,0.888889,0.6,0.470588,0.4,0.823529,0.933333,0.761905,0.888889,0.684211,0.736842,0.823529,0.933333,0.8,0.8125,0.611111,0.666667,0.777778,0.666667,0.666667,0.727273,0.647059,0.368421,0.941176,0.857143,0.380952,0.555556,1,0.666667,0.625,0.6875,0.789474,0.590909,0.411765,0.666667,0.714286,0.692308,0.777778,0.8125,0.666667,0.941176,0.75,0.789474,0.777778,1,0.9375,0.923077,0.733333,0.714286,0.705882,0.533333,0.578947,0.833333,1,0.5,0.777778,0.9375,0.714286,0.789474,0.866667,0.818182,0.928571,0.6875,0.6875,0.909091,0.833333,0.8] predictive_accuracy 0.74875 prior_entropy 6.6438561897747395 recall 0.74875 [0.625,1,1,0.9375,1,0.8125,0.875,0.875,0.75,0.9375,0.8125,0.875,0.875,0.5625,1,0.75,1,0.5,0.4375,0.3125,0.875,0.9375,0.75,1,0.8125,0.1875,0.3125,0.75,0.875,1,0.875,0.8125,0.875,0.4375,1,0.75,0.5,0.5,0.875,0.875,1,1,0.8125,0.875,0.875,0.875,0.75,0.8125,0.6875,0.75,0.875,0.625,0.625,0.5,0.6875,0.4375,1,0.75,0.5,0.3125,1,1,0.625,0.6875,0.9375,0.8125,0.4375,0.75,0.3125,0.5625,0.4375,0.8125,0.625,1,0.5625,0.9375,0.875,0.625,0.9375,0.75,0.6875,0.625,0.75,0.5,0.6875,0.625,0.875,0.5625,0.875,0.9375,0.9375,0.9375,0.8125,0.5625,0.8125,0.6875,0.6875,0.625,0.3125,1] relative_absolute_error 0.6140355521302331 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.06980363063085773 root_relative_squared_error 0.7015528842639821 total_cost 0 area_under_roc_curve 0.994188360799299 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[1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.981013,1,0.946203,1,1,0.984177,1,1,0.993671,1,0.993711,1,1,1,1,1,0.977848,1,1,0.993711,0.949686,1,1,0.996835,1,1,1,1,1,0.993671,1,0.990506,1,1,1,1,1,1,1,1,1,0.981132,0.971519,1,1,0.996835,1,1,0.996835,0.990506,1,0.993711,0.974684,0.996835,1,1,1,1,1,1,0.996835,0.996835,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.993671,0.949686,1] area_under_roc_curve 0.9965242118461903 [0.981013,1,1,1,1,0.987342,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.955975,0.990506,1,1,1,1,0.993711,0.990506,0.977848,1,1,1,1,1,1,0.990506,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.993711,0.939873,1,0.987342,1,0.996835,0.993711,1,1,1,0.996835,1,0.996835,1,0.977848,0.993671,1,1,0.996835,0.996835,0.987421,1,0.993711,1,1,1,1,1,0.981132,1,1,0.993671,1,0.987421,1,1,1,1,1,1,0.993711,1,1,0.993711,1,1,1,1] area_under_roc_curve 0.9929287576626065 [1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.880503,1,1,1,0.996835,1,0.987342,0.996835,1,1,1,1,0.971519,0.977848,1,1,1,1,0.987421,1,0.977848,1,1,0.993671,0.936709,1,1,1,1,1,1,1,1,1,1,1,1,1,0.962264,0.996835,0.987421,0.984177,0.977848,1,0.993671,1,1,1,1,0.993711,1,1,1,0.968553,0.996835,0.977848,0.987342,0.990506,1,1,1,0.89557,1,1,0.977848,1,1,1,1,0.996835,0.993671,0.993711,1,1,1,1,1,1,0.993671,1,1,0.962025,1,0.996835,1,0.987421,0.996835] area_under_roc_curve 0.9960873437624389 [0.96519,1,1,1,1,0.996835,1,0.996835,1,1,1,1,1,1,1,1,1,0.996835,1,0.962025,1,1,0.996835,1,0.996835,1,0.981013,1,1,1,1,1,0.974684,0.996835,1,0.996835,0.987342,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,0.993671,1,1,1,1,0.993671,0.990506,1,1,0.996835,1,1,1,0.987421,1,1,0.996835,0.993711,1,0.977848,1,0.987342,0.993671,1,1,0.984177,1,1,1,1,1,1,0.993671,1,0.993671,1,1,1,1,0.993671,1,1,0.993671,0.981132,1,1,1,1,0.981132,0.968553,1] area_under_roc_curve 0.9969245083990126 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,0.990506,1,1,0.990506,1,0.990506,0.880503,0.981132,0.993671,1,1,1,1,1,0.974843,1,1,0.996835,1,1,1,0.993671,1,1,1,1,1,0.996835,0.996835,1,1,0.993711,1,1,1,0.993671,0.993671,1,1,0.993671,0.993711,1,1,1,0.993671,1,1,0.981132,0.996835,0.993671,0.987342,0.993711,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,1,1,1,0.955975,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1] area_under_roc_curve 0.9946705079213436 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,0.987421,0.971519,1,1,1,1,1,1,0.981132,0.993711,1,0.962264,1,1,1,1,1,1,1,0.984177,0.993671,1,1,1,1,1,1,0.993711,0.996835,1,1,0.987421,1,0.993711,0.987342,0.993671,1,0.996835,0.949367,1,1,0.981013,0.974843,1,1,1,1,1,0.955975,0.993711,1,0.955696,0.981013,0.993711,1,1,1,0.996835,1,1,1,1,1,0.974684,0.987421,0.996835,0.996835,1,0.977848,1,0.949686,1,1,1,1,1,0.981132,1,0.996835,0.993671,1,0.987342,1] area_under_roc_curve 0.9955810644057002 [0.987421,1,1,1,1,0.993711,0.990506,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.974843,1,1,0.886792,0.981132,1,1,1,1,1,1,1,1,1,1,0.968354,1,1,1,1,0.996835,1,1,1,1,1,0.987421,1,1,0.993671,0.996835,0.952532,0.996835,0.968553,1,1,1,0.990506,1,1,0.996835,0.996835,1,1,0.974684,1,0.996835,1,1,0.981132,0.993671,1,0.996835,0.996835,1,1,1,1,1,0.974843,1,0.993711,1,1,1,0.996835,1,1,1,1,1,0.993671,1,0.993671,0.993711,1,0.968354,1] area_under_roc_curve 0.9957009792213993 [0.930818,1,0.981132,1,1,1,1,0.993711,1,1,1,1,1,0.984177,1,1,1,0.974843,0.993671,1,1,1,1,1,1,0.90566,0.993711,1,0.993671,1,1,1,1,1,0.996835,0.993671,0.987342,0.993671,0.996835,1,1,1,1,1,1,1,1,0.996835,1,0.993711,0.993671,0.996835,1,0.990506,1,0.981132,1,0.993711,0.996835,0.990506,1,1,0.968354,0.993671,1,1,0.993671,1,1,0.993711,0.993711,1,0.987342,1,0.993671,0.996835,1,1,1,0.996835,1,0.981132,1,0.968553,1,0.996835,1,0.987342,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1] 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 0.7662758103359786 kappa 0.7726016581129096 kappa 0.7473351756810107 kappa 0.7599020653161157 kappa 0.7536128879412461 kappa 0.7788571654227382 kappa 0.7536128879412461 kappa 0.7346705097326964 kappa 0.6778523489932886 kb_relative_information_score 117.95822678995115 kb_relative_information_score 118.37035825846495 kb_relative_information_score 118.86192961336229 kb_relative_information_score 119.91612957446561 kb_relative_information_score 117.76064681192811 kb_relative_information_score 118.84156654312156 kb_relative_information_score 122.18696916781013 kb_relative_information_score 118.74531278061546 kb_relative_information_score 119.3849855146747 kb_relative_information_score 118.08366630590594 mean_absolute_error 0.012069374549061856 mean_absolute_error 0.012114341991341246 mean_absolute_error 0.01220709740259686 mean_absolute_error 0.012274195165944628 mean_absolute_error 0.012190073818542256 mean_absolute_error 0.012236165133477927 mean_absolute_error 0.011732573728354725 mean_absolute_error 0.012138773313491863 mean_absolute_error 0.012228634514790473 mean_absolute_error 0.012387809704184752 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 0.76875 predictive_accuracy 0.775 predictive_accuracy 0.75 predictive_accuracy 0.7625 predictive_accuracy 0.75625 predictive_accuracy 0.78125 predictive_accuracy 0.75625 predictive_accuracy 0.7375 predictive_accuracy 0.68125 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 [1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0,1,0,1,0,0.5,1,1,1,0,1,0,0.5,0,1,0.5,1,0.5,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,1,1,1,0,0.5,1,1,0.5,0.5,1,0.5,0.5,1,1,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,0,1,0.5,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0.5,0,1] recall 0.76875 [1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,0.5,1,1,1,0.5,1,0.5,0.5,1,0,0,0.5,1,1,1,0,1,0.5,0.5,1,0,0.5,0.5,0,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1] recall 0.775 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0,1,0,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,0.5,0.5,0,0.5,0,1,1,1,0,1,1,0.5,0.5,1,0,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1] recall 0.75 [0.5,1,1,1,1,0.5,1,0.5,0.5,1,0.5,1,1,0.5,1,1,1,1,0,0,1,1,1,1,0,0,0.5,0,1,1,1,0.5,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,0,0,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,0,0.5,0,1,0,1,1,0.5,1,1,1,0.5,1,0.5,1,0,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1] recall 0.7625 [0.5,1,1,1,1,1,1,1,1,1,1,0.5,0,0,1,1,1,0.5,1,0,0.5,1,1,1,1,0.5,0.5,1,1,1,1,0,1,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,1,1,1,1,1,0,1,0.5,1,0,0.5,0.5,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1] recall 0.75625 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0,0,0,1,1,1,1,0.5,0,1,0.5,0.5,1,1,0,1,1,0,1,1,1,1,0,1,0.5,1,1,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,0,1,1,1,1,1,1,1,0,1,1,1,0.5,0,0,1] recall 0.78125 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,1,1,1,1,0.5,0,0,0.5,1,1,0.5,0,1,1,1,1,0.5,1,1,1,1,1,1,1,0,0.5,0,1,1,1,0,1,1,0,0.5,0.5,1,0.5,0,0,1,1,1,0.5,1,1,0,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,1,1,0,1,1,0,1] recall 0.75625 [1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,0.5,0,1,1,1,1,1,0,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0.5,1,0,1,1,0,1,1,0,1,0.5,0.5,0,0,1] recall 0.7375 [0,1,1,1,1,1,0.5,1,0.5,1,0,1,1,1,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,0.5,1,0.5,1,1,1,0,1,1,0.5,0.5,0.5,0.5,0,1,0,0.5,0,1,1,0.5,0.5,1,1,0.5,1,0.5,1,1,0,0,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,0,0.5,0,0.5,0.5,1] recall 0.68125 [0,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,1,1,1,0,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,0,1,0.5,0.5,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,0,0.5,1,0,1,0,1,0,1,1,0,0.5,1,1,0,0,0,0,0,1,0,1,0,1,1,1,1,0.5,1,0,1,0,1,0.5,0.5,0,1,0.5,1,1,1,0.5,0,1,1,0.5,1,1] relative_absolute_error 0.6095643711647392 relative_absolute_error 0.6118354541081428 relative_absolute_error 0.6165200708382242 relative_absolute_error 0.6199088467648791 relative_absolute_error 0.6156602938657695 relative_absolute_error 0.6179881380544398 relative_absolute_error 0.5925542287047831 relative_absolute_error 0.6130693592672648 relative_absolute_error 0.6176078037772956 relative_absolute_error 0.6256469547568045 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 0.06998750188993073 root_mean_squared_error 0.06936241186106187 root_mean_squared_error 0.06958574090579615 root_mean_squared_error 0.07019200724118525 root_mean_squared_error 0.0700148576004411 root_mean_squared_error 0.07019932618406323 root_mean_squared_error 0.06778728039847369 root_mean_squared_error 0.06959758703810619 root_mean_squared_error 0.0697488306470419 root_mean_squared_error 0.07150605646430308 root_relative_squared_error 0.7034008599490592 root_relative_squared_error 0.6971184687795124 root_relative_squared_error 0.699363010131549 root_relative_squared_error 0.7054562160633958 root_relative_squared_error 0.7036757951843212 root_relative_squared_error 0.7055297742069966 root_relative_squared_error 0.6812878019404556 root_relative_squared_error 0.6994820682409106 root_relative_squared_error 0.7010021237038773 root_relative_squared_error 0.7186629076668498 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 2470.4410769991227 usercpu_time_millis 2387.63397799994 usercpu_time_millis 2464.4572339984734 usercpu_time_millis 2400.2272130019264 usercpu_time_millis 2428.788061999512 usercpu_time_millis 2413.1908299987117 usercpu_time_millis 2374.563322002359 usercpu_time_millis 2375.1179020018753 usercpu_time_millis 2377.3564229995827 usercpu_time_millis 2383.1572530016274 usercpu_time_millis_testing 39.078853000319214 usercpu_time_millis_testing 36.33918800005631 usercpu_time_millis_testing 43.5171339995577 usercpu_time_millis_testing 38.135344000693294 usercpu_time_millis_testing 37.78427599900169 usercpu_time_millis_testing 36.91324099963822 usercpu_time_millis_testing 36.9655030008289 usercpu_time_millis_testing 37.046363000627025 usercpu_time_millis_testing 37.17445000074804 usercpu_time_millis_testing 37.75459800090175 usercpu_time_millis_training 2431.3622239988035 usercpu_time_millis_training 2351.2947899998835 usercpu_time_millis_training 2420.9400999989157 usercpu_time_millis_training 2362.091869001233 usercpu_time_millis_training 2391.0037860005104 usercpu_time_millis_training 2376.2775889990735 usercpu_time_millis_training 2337.5978190015303 usercpu_time_millis_training 2338.0715390012483 usercpu_time_millis_training 2340.1819729988347 usercpu_time_millis_training 2345.4026550007256