5973898 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) 4008631 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.22700344580582563 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 18 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 36699 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 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 12871155 description https://api.openml.org/data/download/12871155/description.xml -1 12871156 predictions https://api.openml.org/data/download/12871156/predictions.arff area_under_roc_curve 0.9941279987373739 [0.984848,0.999487,0.999605,1,0.998185,0.993963,0.999645,0.999408,0.994752,0.999605,0.994752,1,0.99712,0.982363,0.999329,0.998935,0.999763,0.985953,0.987926,0.972104,0.998067,0.999566,0.993766,1,0.996804,0.965002,0.985874,0.997751,0.994831,0.999448,0.999961,1,0.998698,0.987492,0.998224,0.998067,0.992148,0.992661,0.998777,0.999645,0.997435,0.998737,0.999684,0.998146,0.998264,0.999408,0.999053,0.994515,0.996133,0.996252,0.995975,0.992779,0.996883,0.986072,0.994279,0.974116,1,0.999961,0.994239,0.979995,0.999921,0.998658,0.991477,0.998777,0.998737,0.993529,0.974787,1,0.988084,0.981218,0.992977,0.997001,0.993174,0.998303,0.966974,0.998856,0.999014,0.979324,0.999921,0.999092,0.989938,0.995857,0.994476,0.995265,0.996646,0.995344,0.999684,0.992898,0.996725,1,1,0.998856,0.998303,0.989228,0.99858,0.999329,0.995344,0.995107,0.957781,0.997159] average_cost 0 f_measure 0.7145007979240531 [0.64,0.842105,0.969697,1,0.857143,0.5,0.857143,0.833333,0.571429,0.888889,0.666667,0.882353,0.705882,0.5,0.941176,0.896552,0.842105,0.384615,0.526316,0.307692,0.75,1,0.733333,1,0.75,0.222222,0.322581,0.681818,0.866667,0.8,0.864865,1,0.848485,0.413793,0.866667,0.652174,0.484848,0.578947,0.882353,0.761905,0.606061,0.909091,0.842105,0.733333,0.909091,0.8,0.875,0.740741,0.774194,0.83871,0.666667,0.6875,0.787879,0.5,0.689655,0.1,1,0.914286,0.648649,0.583333,0.857143,0.722222,0.3,0.857143,0.8,0.551724,0.296296,0.914286,0.363636,0.545455,0.642857,0.697674,0.619048,0.875,0.64,0.857143,0.777778,0.210526,0.888889,0.866667,0.521739,0.733333,0.714286,0.642857,0.742857,0.875,0.888889,0.666667,0.833333,1,0.857143,0.714286,0.785714,0.47619,0.742857,0.777778,0.8125,0.647059,0.210526,0.823529] kappa 0.7316919191919192 kb_relative_information_score 982.9490468876497 mean_absolute_error 0.0161423782713436 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 0.7481961661265402 [0.888889,0.727273,0.941176,1,0.789474,0.5,0.789474,0.75,0.666667,0.8,0.714286,0.833333,0.666667,0.75,0.888889,1,0.727273,0.5,0.454545,0.4,0.625,1,0.785714,1,0.75,1,0.333333,0.535714,0.928571,0.666667,0.761905,1,0.823529,0.461538,0.928571,0.5,0.470588,0.5,0.833333,0.615385,0.588235,0.882353,0.727273,0.785714,0.882353,0.736842,0.875,0.909091,0.8,0.866667,0.714286,0.6875,0.764706,0.75,0.769231,0.25,1,0.842105,0.571429,0.875,0.789474,0.65,0.75,0.789474,0.666667,0.615385,0.363636,0.842105,0.666667,1,0.75,0.555556,0.5,0.875,0.888889,1,0.7,0.666667,0.8,0.928571,0.857143,0.785714,0.833333,0.75,0.684211,0.875,0.8,0.565217,0.75,1,0.789474,0.576923,0.916667,1,0.684211,0.7,0.8125,0.611111,0.666667,0.777778] predictive_accuracy 0.734375 prior_entropy 6.6438561897747395 recall 0.734375 [0.5,1,1,1,0.9375,0.5,0.9375,0.9375,0.5,1,0.625,0.9375,0.75,0.375,1,0.8125,1,0.3125,0.625,0.25,0.9375,1,0.6875,1,0.75,0.125,0.3125,0.9375,0.8125,1,1,1,0.875,0.375,0.8125,0.9375,0.5,0.6875,0.9375,1,0.625,0.9375,1,0.6875,0.9375,0.875,0.875,0.625,0.75,0.8125,0.625,0.6875,0.8125,0.375,0.625,0.0625,1,1,0.75,0.4375,0.9375,0.8125,0.1875,0.9375,1,0.5,0.25,1,0.25,0.375,0.5625,0.9375,0.8125,0.875,0.5,0.75,0.875,0.125,1,0.8125,0.375,0.6875,0.625,0.5625,0.8125,0.875,1,0.8125,0.9375,1,0.9375,0.9375,0.6875,0.3125,0.8125,0.875,0.8125,0.6875,0.125,0.875] relative_absolute_error 0.8152716298658368 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08406069575270954 root_relative_squared_error 0.8448417800847244 total_cost 0 area_under_roc_curve 0.9926866889578857 [0.993711,1,1,1,0.996835,1,1,1,0.993671,1,0.993671,1,1,0.987342,1,1,1,0.974684,0.974684,0.987421,1,1,1,1,1,0.990506,0.987342,1,0.974684,0.987421,1,1,1,0.993671,1,0.993711,1,0.993711,1,0.996835,1,1,1,1,1,1,1,1,1,0.977848,0.990506,1,0.993711,1,0.993711,1,1,1,0.987421,0.981013,1,1,0.990506,1,1,0.996835,0.987342,1,1,0.962264,0.990506,0.993711,1,1,1,1,1,0.96519,1,1,0.996835,1,0.993711,1,0.996835,0.968354,1,0.996835,0.990506,1,1,1,1,0.987342,1,0.996835,1,1,0.797468,1] area_under_roc_curve 0.9936007284451873 [0.981132,1,1,1,1,1,1,1,1,1,0.996835,1,0.987342,0.949367,1,1,1,0.981013,0.993671,0.987421,1,0.993711,1,1,1,0.955696,0.987342,0.993671,1,1,1,1,1,1,0.996835,0.993711,0.981132,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.971519,1,1,1,0.968553,1,1,1,0.914557,1,1,0.993671,0.993671,1,0.993671,0.993671,1,0.91195,1,1,1,0.996835,1,1,1,1,0.974684,1,0.990506,0.993671,0.996835,0.968553,0.987421,1,1,0.996835,0.996835,0.996835,1,1,1,1,0.977848,1,1,1,0.987342,0.993671,1] area_under_roc_curve 0.9938330944988454 [1,1,1,1,0.984177,0.996835,1,1,0.987342,1,1,1,1,0.993671,0.996835,1,1,0.990506,0.993711,0.908228,0.993711,1,0.962025,1,0.987421,0.984177,1,1,0.993671,1,1,1,0.996835,0.981013,0.993711,1,0.993711,0.993711,1,1,1,1,1,1,0.993671,1,0.996835,1,0.984177,1,1,1,1,1,1,0.996835,1,1,0.987421,0.971519,1,1,1,1,1,0.984177,0.977848,1,0.981132,0.958861,1,0.993671,0.993711,1,1,1,1,0.968354,1,1,1,0.993671,0.996835,1,1,1,1,1,0.993671,1,1,1,1,0.990506,1,1,0.993671,0.987342,0.981132,1] area_under_roc_curve 0.9938348360003184 [0.996835,1,1,1,0.996835,0.990506,1,1,0.993671,1,0.987342,1,1,0.990506,1,1,1,0.996835,0.937107,0.993671,1,1,1,1,0.993711,0.946203,0.968354,1,1,1,1,1,1,0.993671,1,0.993711,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,0.990506,1,1,1,0.987342,1,1,0.996835,1,0.996835,0.993671,0.939873,1,1,0.939873,0.990506,0.993671,0.987421,1,0.993711,0.996835,1,0.981013,1,1,0.981132,0.993671,1,0.993671,1,1,1,1,1,1,1,1,0.993711,0.993671,1,0.993711,0.990506,1,0.981132,0.977848] area_under_roc_curve 0.9916263633468672 [0.993671,1,1,1,1,0.996835,1,1,1,0.996835,0.993671,1,1,0.91195,1,1,1,0.996835,1,0.987342,0.977848,1,1,1,0.993671,0.952532,0.987342,1,1,1,1,1,1,0.968354,1,1,0.990506,0.990506,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.993711,0.981132,0.996835,0.987421,0.974684,0.962025,1,0.996835,0.993671,0.993711,1,1,0.993711,1,1,1,0.91195,1,0.974684,0.987342,1,1,0.987421,0.993711,0.822785,1,0.993671,0.990506,1,1,1,1,1,0.993671,0.981132,1,1,1,1,1,1,0.996835,1,0.981132,0.993671,1,0.996835,1,0.968553,0.996835] area_under_roc_curve 0.993913203566595 [0.958861,1,1,1,1,0.987342,1,1,1,1,0.996835,1,1,0.987421,1,1,1,1,1,0.917722,1,1,0.993671,1,1,0.984177,0.971519,1,1,1,1,1,0.984177,0.990506,0.987421,0.996835,0.987342,1,1,1,1,1,1,1,0.993711,1,1,0.996835,0.990506,0.990506,1,1,1,1,0.981013,0.958861,1,1,0.993671,1,1,1,0.981132,1,1,1,0.981132,1,0.996835,1,0.96519,0.990506,1,1,0.977848,1,1,0.977848,1,1,1,0.996835,1,0.996835,1,1,1,0.987421,1,1,1,0.996835,1,1,1,1,1,0.974843,0.981132,0.996835] area_under_roc_curve 0.9955420050155241 [1,1,1,1,1,1,1,1,0.987421,1,1,1,0.981013,1,1,1,1,0.993711,0.993671,0.981013,1,0.996835,1,1,0.996835,0.880503,0.987421,0.993671,1,1,1,1,1,0.974843,1,1,1,1,1,1,1,0.993671,1,1,1,0.993671,0.996835,0.987342,1,1,1,0.996835,1,1,0.993671,0.987342,1,1,0.993671,0.993711,0.996835,1,1,0.984177,1,0.993711,0.962264,1,0.996835,1,1,1,1,1,1,1,1,0.981132,1,1,0.981013,1,0.990506,1,1,1,1,0.943396,1,1,1,1,0.993671,1,1,1,1,1,0.96519,1] area_under_roc_curve 0.9953402396306028 [1,1,1,1,1,0.996835,1,1,0.993711,1,0.993711,1,1,1,1,0.993671,1,0.981132,0.993671,0.990506,1,1,1,1,0.993671,0.962264,0.987421,0.996835,1,0.996835,1,1,1,0.993711,1,1,0.987342,0.987342,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.981132,1,0.987342,1,0.996835,0.955696,1,1,0.993671,1,1,0.993671,1,1,1,0.974843,0.974843,1,0.987342,0.987342,1,1,1,0.993711,0.996835,1,1,0.987421,1,1,0.962025,1,0.990506,1,0.993671,0.996835,1,0.993711,0.993711,1,1,0.996835,1,0.987421,1,1,0.984177,1,0.981013,1] area_under_roc_curve 0.9965655103096888 [0.981132,0.996835,1,1,1,0.987421,1,1,1,1,0.981132,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,1,0.990506,0.984177,1,1,1,0.996835,1,0.993671,1,1,1,0.987342,0.993711,1,1,0.993671,0.996835,0.96519,0.990506,0.943396,1,1,0.993671,0.987342,1,1,1,1,1,1,1,1,0.996835,0.987421,1,0.987421,0.981013,1,0.996835,0.993671,1,1,1,0.996835,0.990506,0.993711,1,1,0.996835,1,1,0.993671,1,1,1,0.993671,1,1,1,1,0.993711,1,0.996835,1] area_under_roc_curve 0.9965682469548602 [0.930818,1,1,1,1,1,1,0.987421,0.996835,1,0.993711,1,1,0.990506,1,1,1,0.974843,0.990506,0.981132,1,1,1,1,1,0.981132,1,1,0.993671,1,1,1,1,0.987421,0.996835,1,0.993671,1,0.996835,1,1,1,1,1,1,1,1,0.987342,1,0.987421,1,0.990506,1,0.984177,1,1,1,1,0.993671,0.996835,1,1,0.977848,1,0.993711,0.993711,0.996835,1,1,1,1,1,0.993671,1,0.996835,1,1,1,0.993711,1,1,0.981132,1,0.981132,0.996835,1,0.996835,0.981013,1,1,1,1,1,0.996835,1,1,0.987421,1,1,1] 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 0.7032125661062436 kappa 0.7221016066000868 kappa 0.7158642462509865 kappa 0.7157296272899558 kappa 0.7220467466835123 kappa 0.6967303743484441 kappa 0.7725567620927937 kappa 0.7852094602598018 kappa 0.7473152242577384 kappa 0.7346390775548887 kb_relative_information_score 97.76687867394325 kb_relative_information_score 97.56958812854108 kb_relative_information_score 97.31929406137246 kb_relative_information_score 97.75632139428023 kb_relative_information_score 97.72562217665259 kb_relative_information_score 97.84018573363954 kb_relative_information_score 99.52776634420519 kb_relative_information_score 98.83950448892669 kb_relative_information_score 99.2595799558578 kb_relative_information_score 99.3443059302302 mean_absolute_error 0.016147939825121187 mean_absolute_error 0.01618704544149556 mean_absolute_error 0.016222014503732774 mean_absolute_error 0.016192894075305442 mean_absolute_error 0.016127438155071703 mean_absolute_error 0.01617162201968055 mean_absolute_error 0.016026595780776177 mean_absolute_error 0.016085233111179955 mean_absolute_error 0.0161319434032951 mean_absolute_error 0.016131056397777496 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 0.70625 predictive_accuracy 0.725 predictive_accuracy 0.71875 predictive_accuracy 0.71875 predictive_accuracy 0.725 predictive_accuracy 0.7 predictive_accuracy 0.775 predictive_accuracy 0.7875 predictive_accuracy 0.75 predictive_accuracy 0.7375 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 0.70625 [1,1,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,0,1,1,0,0,1,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,1,0,1,1,0,0.5,1,1,0,1,1,0.5,0.5,1,0,0,0,1,1,1,1,1,0.5,0,1,1,0,1,0,1,1,0.5,1,1,0.5,1,1,1,1,0.5,0.5,0.5,1,1,0,1] recall 0.725 [0,1,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,0.5,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,0,0,1,1,1,1,0,1,0.5,0,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0,0,1] recall 0.71875 [0.5,1,1,1,0.5,0.5,1,1,0,1,0.5,1,1,0.5,1,0.5,1,0.5,0,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0.5,0.5,1,0,0.5,0.5,1,0,1,1,1,1,0,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0,1] recall 0.71875 [0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0.5,1,1,0.5,1,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0.5,1,1,0,0.5,1,1,0,1,1,0.5,0,1,0,0,0,1,1,1,0,0.5,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0,0.5,1,0,0.5] recall 0.725 [0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0.5,0,0,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0,1,1,1,0,1,0.5,0,0,0.5,0,0,0,1,1,1,1,1,1,0,1,1,0,0,1,0,0.5,1,1,0,0,0.5,1,1,0,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.7 [0,1,1,1,1,0.5,1,1,0,1,0,1,1,1,1,1,1,0,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,0,0,1,1,0,1,1,0.5,0,1,1,0.5,0,1,0,0.5,0.5,1,1,1,0.5,0,1,0,1,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0.5] recall 0.775 [1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0,1,0.5,1,1,1,1,0.5,0,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,0.5,1,0.5,1,0.5,1,1,0,1,1,0,1,0,1,1,1,0,0.5,0.5,1,0.5,1,1,0,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,1,0,1,1,1,1,0,0,1,1,1,1,0,1] recall 0.7875 [0.5,1,1,1,1,0,1,1,1,1,1,1,0.5,0,1,0.5,1,1,1,0,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,0,1,0.5,1,0.5,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,0,1,1,1,1,1,1,0,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,0,1,1,0.5,1,0,1] recall 0.75 [1,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,0,1,1,1,0,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,0.5,1,0.5,0.5,0,1,1,1,0,1,1,0,1,1,1,0,1,0.5,0,1,1,0.5,0.5,0,0.5,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,0.5,1] recall 0.7375 [0,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0.5,0,1,0,1,1,1,0.5,1,1,0,1,1,1,0,1,0.5,0,1,0,1,1,0,0.5,1,0,1,1,0.5,0,1,0,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1] relative_absolute_error 0.8155525164202606 relative_absolute_error 0.8175275475502795 relative_absolute_error 0.8192936618046842 relative_absolute_error 0.8178229330962331 relative_absolute_error 0.8145170785389735 relative_absolute_error 0.8167485868525516 relative_absolute_error 0.8094240293321289 relative_absolute_error 0.8123855106656529 relative_absolute_error 0.8147446163280341 relative_absolute_error 0.8146998180695693 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 0.08410808221625694 root_mean_squared_error 0.08423648621635244 root_mean_squared_error 0.08445920088287599 root_mean_squared_error 0.08432472037522798 root_mean_squared_error 0.08411779108048323 root_mean_squared_error 0.08427022246424609 root_mean_squared_error 0.08348869473301969 root_mean_squared_error 0.08369392335410324 root_mean_squared_error 0.08394477082324484 root_mean_squared_error 0.08395833994524295 root_relative_squared_error 0.8453180319626903 root_relative_squared_error 0.8466085407199553 root_relative_squared_error 0.8488469073386454 root_relative_squared_error 0.8474953273826304 root_relative_squared_error 0.8454156097195965 root_relative_squared_error 0.8469476027687363 root_relative_squared_error 0.8390929535331735 root_relative_squared_error 0.841155578782798 root_relative_squared_error 0.8436766907062919 root_relative_squared_error 0.8438130655135716 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 2700.495576999998 usercpu_time_millis 2621.850932000001 usercpu_time_millis 2622.5539509999862 usercpu_time_millis 2624.7383570000125 usercpu_time_millis 2621.874686999973 usercpu_time_millis 2623.5693880000217 usercpu_time_millis 2620.5766069999754 usercpu_time_millis 2637.9556589999993 usercpu_time_millis 2631.238042000007 usercpu_time_millis 2633.0860260000295 usercpu_time_millis_testing 47.65055400000051 usercpu_time_millis_testing 38.46930099999213 usercpu_time_millis_testing 36.60387599998671 usercpu_time_millis_testing 36.87511300000779 usercpu_time_millis_testing 36.70908199998735 usercpu_time_millis_testing 36.77923600000099 usercpu_time_millis_testing 36.56375099998854 usercpu_time_millis_testing 36.88664500000982 usercpu_time_millis_testing 37.22963399999912 usercpu_time_millis_testing 36.7707070000165 usercpu_time_millis_training 2652.8450229999976 usercpu_time_millis_training 2583.381631000009 usercpu_time_millis_training 2585.9500749999997 usercpu_time_millis_training 2587.8632440000047 usercpu_time_millis_training 2585.165604999986 usercpu_time_millis_training 2586.7901520000205 usercpu_time_millis_training 2584.0128559999866 usercpu_time_millis_training 2601.0690139999897 usercpu_time_millis_training 2594.008408000008 usercpu_time_millis_training 2596.315319000013