5974743 1 Jan van Rijn 9956 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) 4009476 bootstrap true 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.16607142256994223 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 11 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 14798 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 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 12872841 description https://api.openml.org/data/download/12872841/description.xml -1 12872842 predictions https://api.openml.org/data/download/12872842/predictions.arff area_under_roc_curve 0.9905930839959316 [0.99638,1,0.977298,0.995775,0.973666,0.995381,0.992972,0.994946,0.987168,0.999289,0.994749,0.980614,0.999329,0.998144,0.987208,0.999763,0.980614,0.996644,0.999882,0.995341,1,0.964545,0.990998,0.999566,0.868683,0.995183,0.990366,0.935447,1,0.999171,0.992814,0.999921,0.973626,0.999408,0.996684,0.976153,0.995539,0.999368,0.964664,0.998342,0.998105,0.992814,0.988708,0.96415,0.9741,0.999289,0.98322,0.998263,0.994315,0.993288,0.994354,0.994828,0.997434,0.992617,0.987168,0.997355,1,0.966519,0.999013,0.999961,0.999803,0.999566,0.999092,0.999763,0.998342,0.998934,0.999961,0.993288,0.998421,0.972757,0.998539,0.987879,1,0.988234,1,0.999566,0.993091,0.997986,0.99846,0.991077,0.995973,0.989695,0.982825,0.996012,0.989893,0.998302,0.954596,0.999329,0.999645,0.99925,0.9771,0.979193,0.997789,0.999052,0.994709,0.995578,0.999645,0.997394,0.998184,0.999605] average_cost 0 kappa 0.7271021672046786 kb_relative_information_score 953.5462169565703 mean_absolute_error 0.016171366350369143 mean_prior_absolute_error 0.019799992711748222 number_of_instances 1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] predictive_accuracy 0.7298311444652908 prior_entropy 6.6438309601245775 recall 0.7298311444652908 [0.666667,0.9375,0.3125,0.6875,0.75,0.625,0.625,0.8125,0.625,0.875,0.75,0.75,1,0.875,0.5,1,0.4375,0.8125,0.9375,0.9375,1,0.0625,0.5,1,0,0.8125,0.75,0,1,0.9375,0.375,0.9375,0.1875,1,0.8125,0.0625,0.875,1,0.5625,0.8125,0.875,0.25,0.4375,0.375,0.3125,0.9375,0.4375,0.875,0.6875,0.625,0.8125,0.75,0.9375,0.75,0.4375,0.8125,1,0.625,0.9375,1,0.9375,1,0.875,1,0.75,0.875,1,0.6875,0.75,0.1875,0.8125,0.4375,1,0.8125,0.9375,1,0.75,0.9375,0.875,0.625,0.6875,0.6875,0.1875,0.625,0.8125,0.9375,0.1875,1,1,0.9375,0.875,0.125,0.875,0.8125,0.9375,0.875,0.9375,1,0.8125,0.9375] relative_absolute_error 0.8167359748962911 root_mean_prior_squared_error 0.09949872432040595 root_mean_squared_error 0.08386901472851163 root_relative_squared_error 0.8429154775737274 total_cost 0 area_under_roc_curve 0.9900366212881144 [1,1,0.993711,1,0.955696,0.962025,0.962025,1,1,1,1,1,1,1,0.987342,1,0.996835,1,1,1,1,0.892405,1,0.996835,0.996835,1,1,0.993671,1,0.987421,1,1,1,1,0.987421,0.933544,0.993711,1,0.990506,0.987342,1,1,0.987421,1,1,1,0.949367,1,0.987342,0.993671,1,0.996835,1,1,0.924528,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,1,0.996835,0.898734,1,1,1,0.867089,0.977848,1,0.996835,0.96519,0.996835,1,1,1,1] area_under_roc_curve 0.9911927294801371 [1,1,1,0.993671,0.996835,0.987342,0.996835,1,1,1,1,1,1,1,1,1,0.974684,1,1,0.996835,1,0.962025,1,1,0.943038,0.974684,0.91195,0.996835,1,1,1,1,1,1,0.981132,0.958861,1,1,0.993671,1,0.996835,0.987421,0.880503,0.841772,1,1,0.981013,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,1,0.949686,1,0.933544,1,0.974684,1,1,1,1,1,0.993671,1,0.993711,1,1,0.955975,1,1,1,0.990506,0.996835,1,1,1,0.996835,1,1,1,0.996835,0.993711,1,1,1] area_under_roc_curve 0.9911880025475679 [1,1,0.939873,1,1,1,1,1,1,1,1,1,0.993671,0.990506,1,1,1,1,1,1,1,0.977848,0.984177,1,0.962264,1,1,0.962025,1,1,0.990506,1,0.968354,1,1,0.981132,1,1,1,1,1,0.993711,1,1,0.96519,1,0.987342,1,1,0.981132,1,0.971519,1,1,1,0.996835,1,0.924528,0.987421,1,1,1,1,1,1,1,1,0.974843,0.981132,0.977848,1,0.955696,1,1,1,1,1,1,1,0.987342,1,0.949367,0.987421,0.993671,0.993711,1,0.857595,1,0.993671,1,1,0.968354,1,1,1,1,1,1,1,1] area_under_roc_curve 0.989660208184062 [1,1,0.996835,1,1,1,1,0.996835,1,1,0.993671,1,1,0.993671,0.924051,1,0.977848,1,1,1,1,1,1,1,0.666667,0.993671,1,0.825949,1,1,0.987342,1,0.981013,1,1,1,1,1,0.798742,1,1,0.987421,0.974843,0.993671,1,0.996835,1,0.996835,0.993711,1,1,1,1,0.977848,0.996835,1,1,1,1,1,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,1,0.987342,1,1,1,0.996835,0.93038,0.981132,0.990506,1,1,0.981013,0.993711,0.990506,1,1,1,1,1,1,1,0.996835,0.984177,1,1,1,1,1,0.996835,1] area_under_roc_curve 0.9934514568903745 [0.993671,1,0.962025,1,1,1,1,0.971519,0.880503,0.993711,1,0.962264,1,1,0.968553,1,0.974684,0.990506,1,1,1,0.90566,0.996835,1,0.937107,0.996835,1,0.987421,1,1,1,1,1,1,1,1,1,0.990506,1,0.987421,1,1,0.993671,0.996835,0.981013,1,0.984177,1,0.993711,1,0.993671,0.996835,1,0.981132,0.955696,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,0.996835,1,1,0.993711,1,1,0.993671,0.990506,0.984177,0.987421,0.993711,1,1,0.984177,1,1,1,0.987421,0.987342,1,0.993711,1,1,1,1,0.990506,1] area_under_roc_curve 0.9919092329432374 [0.993711,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.955975,0.984177,1,1,1,0.984177,0.72327,1,1,0.893082,1,1,1,1,0.987421,1,1,1,1,1,0.996835,1,0.996835,0.955696,1,0.987342,1,1,1,0.993671,0.993711,1,1,0.993671,0.996835,1,0.841772,1,1,1,1,1,1,1,1,1,0.990506,0.996835,1,1,1,1,1,1,1,1,1,1,0.996835,0.977848,0.993711,0.984177,1,0.958861,1,0.996835,0.993711,1,1,1,0.96519,0.996835,0.996835,1,1,1,1,1,1] area_under_roc_curve 0.990950660775416 [1,1,0.996835,0.962264,1,0.996835,1,1,0.990506,1,0.984177,0.867089,0.993711,1,1,1,1,1,1,1,1,0.974843,0.962264,1,0.946203,1,0.996835,0.968553,1,1,0.993711,1,0.974684,1,0.990506,0.990506,1,1,0.968354,1,1,1,0.987342,1,0.908228,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.952532,1,1,1,1,1,0.993671,1,1,1,1,0.993671,0.981132,1,1,1,0.908228,1,1,0.987421,1,1,1,1,1,0.955696,1,1,1,1,1,1,1,1,0.955975,1,1,1,0.993671,1,0.996835,1,1] area_under_roc_curve 0.9836255324018788 [0.974843,1,0.933544,1,1,1,0.981132,0.996835,0.96519,1,0.984177,1,1,1,1,1,0.981132,0.990506,1,0.977848,1,1,1,1,0.511076,1,0.987342,0.855346,1,1,0.993711,1,0.886076,1,1,0.968354,1,1,0.882911,1,0.987421,0.990506,1,0.937107,1,1,1,1,1,0.981013,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.955975,1,0.981132,1,1,1,1,1,1,0.993671,0.96519,1,1,0.993671,1,0.984177,0.987421,0.81761,1,1,1,1,1,1,1,1,0.990506,1,0.993671,0.993711,1] area_under_roc_curve 0.9941614919194329 [0.993711,1,1,1,0.993671,1,0.996835,0.987342,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,0.981013,1,1,0.971519,1,1,0.977848,1,1,1,0.996835,0.981132,1,1,1,0.974684,1,1,1,1,1,1,0.91195,1,1,1,0.987421,0.971519,1,0.984177,0.993711,0.993711,0.968354,0.987342,0.993711,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.786164,0.996835,0.993671,1,1,1,1,0.996835,1,1,1,1,1,0.971519,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.962264,1,0.996835] area_under_roc_curve 0.9931574679893329 [1,1,1,0.980892,0.872611,1,0.996815,1,1,1,0.987342,1,1,1,0.996815,1,0.93038,1,1,0.996815,1,0.996815,0.987342,1,0.808917,1,1,0.993631,1,1,1,1,1,1,1,1,1,1,0.977707,1,0.993671,0.980892,1,0.987342,1,0.993671,0.968354,1,1,0.990446,0.977707,1,0.993671,1,0.987342,1,1,1,0.996815,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.993631,1,0.993631,1,1,1,1,1,0.996815,1,0.987342,1,1,1,1,1,1,1,1] 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 0.7222002998974035 kappa 0.7536809694864406 kappa 0.7409981048641819 kappa 0.7031891379854752 kappa 0.7409469652094933 kappa 0.6714708785784798 kappa 0.7346705097326964 kappa 0.7346390775548887 kappa 0.7158418186123608 kappa 0.7520591763294683 kb_relative_information_score 94.36932801479341 kb_relative_information_score 94.55760319321092 kb_relative_information_score 95.33770849470868 kb_relative_information_score 95.18683832297958 kb_relative_information_score 95.68910975535569 kb_relative_information_score 96.68398592599311 kb_relative_information_score 94.8892745342302 kb_relative_information_score 94.26692272051687 kb_relative_information_score 96.4052837446445 kb_relative_information_score 96.16016225013774 mean_absolute_error 0.016191522105838876 mean_absolute_error 0.01625282206668923 mean_absolute_error 0.016203277326187895 mean_absolute_error 0.016185353183397404 mean_absolute_error 0.016122736947350086 mean_absolute_error 0.01603241908007302 mean_absolute_error 0.016189210434474976 mean_absolute_error 0.01625935329756303 mean_absolute_error 0.016176090081029954 mean_absolute_error 0.01610043566429881 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.01980002942907591 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.019799955856386102 mean_prior_absolute_error 0.01979995631910742 number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1] number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1] number_of_instances 160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1] number_of_instances 160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1] number_of_instances 160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2] number_of_instances 160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2] number_of_instances 159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2] predictive_accuracy 0.725 predictive_accuracy 0.75625 predictive_accuracy 0.74375 predictive_accuracy 0.70625 predictive_accuracy 0.74375 predictive_accuracy 0.675 predictive_accuracy 0.7375 predictive_accuracy 0.7375 predictive_accuracy 0.71875 predictive_accuracy 0.7547169811320755 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 recall 0.725 [1,1,0,1,0.5,0.5,0,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,0,1,1,0,1,0,1,1,0,1,0,0,1,1,0.5,0.5,1,1,1,0.5,0,1,0.5,1,0.5,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,0,1,1,1,0.5,0,1,1,0.5,0.5,1,1,0.5,1] recall 0.75625 [1,1,0,0.5,1,0,0.5,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,0,0.5,0,0,1,1,0.5,1,1,1,1,0,1,1,0.5,1,0.5,0,0,0.5,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,1,0,1,1,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0,1,1,1,1,0.5,1,1,1,1,1,1,1,1] recall 0.74375 [1,1,0,0.5,0.5,1,1,1,0,1,1,0,1,0.5,0.5,1,1,1,1,1,1,0,0.5,1,0,1,1,0,1,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,0.5,1,0.5,1,0,0,1,0.5,1,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,0,0.5,1,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.70625 [0.5,1,0.5,1,1,0,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1,0.5,1,1,0,0.5,1,0,0.5,1,0,1,1,0.5,1,0,1,0.5,0,1,1,0,1,1,0,0,0.5,0.5,0.5,1,0.5,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,0,1,1,0.5,1,0.5,0,0.5,1,1,0,1,1,1,1,0,1,1,1,1,0,0.5,1,1,1,1,1,1,1] recall 0.74375 [0.5,1,0.5,1,1,1,1,0.5,0,0,1,0,1,1,0,1,0,0.5,1,1,1,0,0,1,0,1,1,0,1,1,1,1,0.5,1,1,1,1,1,1,0,1,0.5,1,0,0.5,1,0.5,1,0,1,0,0.5,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0,0.5,0,0,1,1,0.5,1,1,1,0,0.5,1,0,1,1,1,1,0.5,1] recall 0.675 [0,1,0.5,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,0.5,1,1,1,0,0,1,0,1,0.5,0,1,1,0,1,0.5,1,1,0,1,1,1,1,1,0,0.5,0,0,1,0.5,0.5,1,1,1,0,0.5,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,0,1,0.5,1,1,1,1,1,0.5,0,0,0,1,0,1,0,1,1,1,1,0,0.5,1,1,1,0.5,1,0.5,1] recall 0.7375 [1,1,0,0,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,0,1,0,1,0.5,0,1,1,0,1,0,1,0.5,0,0.5,1,0.5,1,1,0,0,1,0,1,0,1,1,1,1,1,1,0,0.5,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0.5,0.5,0,1,1,1,0,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.7375 [0,1,0.5,1,1,1,0,0.5,0.5,0,0,1,1,1,1,1,0,0.5,1,0.5,1,1,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0,1,1,0.5,1,0,0,1,0,0.5,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0,0.5,1,0,1,1,1,1,0,1,1,1,0.5,1,1,1,1] recall 0.71875 [0,1,1,1,1,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0,0,1,0,1,1,0,0.5,0,1,1,0,0.5,1,0.5,0.5,1,0.5,0,0,0,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,0.5,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,1,0.5] recall 0.7547169811320755 [1,0.5,0,0.5,0,1,0.5,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,0,1,0,1,1,0,1,1,0.5,1,0,1,1,0,1,1,0.5,1,1,0,0.5,0,0,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0.5,1,1,1,1,0.5,1,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,0,1,0.5,1,1,1,1,1,1] relative_absolute_error 0.8177524262697292 relative_absolute_error 0.8208483792868665 relative_absolute_error 0.8183461233847324 relative_absolute_error 0.8174408649933399 relative_absolute_error 0.8142784335297099 relative_absolute_error 0.8097199406079522 relative_absolute_error 0.8176387135354881 relative_absolute_error 0.821181290276407 relative_absolute_error 0.8169760679447506 relative_absolute_error 0.8131551102848401 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.0994985414402977 root_mean_squared_error 0.08406376269249294 root_mean_squared_error 0.08429278458787322 root_mean_squared_error 0.08394707121410591 root_mean_squared_error 0.08385286723901475 root_mean_squared_error 0.08374279912366663 root_mean_squared_error 0.08328950931487623 root_mean_squared_error 0.08392622920938927 root_mean_squared_error 0.08410134314327365 root_mean_squared_error 0.08397371087817183 root_mean_squared_error 0.0834930443256545 root_relative_squared_error 0.8448712019004754 root_relative_squared_error 0.8471729547344434 root_relative_squared_error 0.8436984103617832 root_relative_squared_error 0.8427516263598558 root_relative_squared_error 0.841645402013876 root_relative_squared_error 0.8370927860416602 root_relative_squared_error 0.8434920749174186 root_relative_squared_error 0.845252039791696 root_relative_squared_error 0.8439692846252682 root_relative_squared_error 0.8391383744630367 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 3277.1760379999932 usercpu_time_millis 3214.3301749998727 usercpu_time_millis 3207.2677770000837 usercpu_time_millis 3196.1161110000376 usercpu_time_millis 3206.0296009999547 usercpu_time_millis 3188.1865409999364 usercpu_time_millis 3152.2677160000967 usercpu_time_millis 3198.015193999936 usercpu_time_millis 3208.775750000086 usercpu_time_millis 3160.7308939999257 usercpu_time_millis_testing 36.228143000016644 usercpu_time_millis_testing 40.158825999924375 usercpu_time_millis_testing 36.301518000072974 usercpu_time_millis_testing 36.04091199997583 usercpu_time_millis_testing 36.196858000039356 usercpu_time_millis_testing 36.152554999944186 usercpu_time_millis_testing 36.24680100006117 usercpu_time_millis_testing 36.16315800002212 usercpu_time_millis_testing 36.20589199999813 usercpu_time_millis_testing 35.07347799995841 usercpu_time_millis_training 3240.9478949999766 usercpu_time_millis_training 3174.1713489999483 usercpu_time_millis_training 3170.9662590000107 usercpu_time_millis_training 3160.0751990000617 usercpu_time_millis_training 3169.8327429999154 usercpu_time_millis_training 3152.033985999992 usercpu_time_millis_training 3116.0209150000355 usercpu_time_millis_training 3161.852035999914 usercpu_time_millis_training 3172.569858000088 usercpu_time_millis_training 3125.6574159999673