8958282 1935 Hilde Weerts 9954 Supervised Classification 8317 sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf=sklearn.svm.classes.SVC)(1) 6893889 categorical_features [] 7644 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 7644 handle_unknown "ignore" 7644 n_values "auto" 7644 sparse true 7644 threshold 0.0 7645 copy true 7646 with_mean false 7646 with_std true 7646 C 32359.525567777717 7650 cache_size 200 7650 class_weight null 7650 coef0 0.9990951417854717 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 7.910191118480936 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.09917005797934816 7650 verbose false 7650 axis 0 8316 categorical_features [] 8316 copy true 8316 fill_empty 0 8316 missing_values "NaN" 8316 strategy "mean" 8316 strategy_nominal "most_frequent" 8316 verbose 0 8316 memory null 8317 openml-python Sklearn_0.19.1. study_98 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 18831832 description https://api.openml.org/data/download/18831832/description.xml -1 18831833 predictions https://api.openml.org/data/download/18831833/predictions.arff area_under_roc_curve 0.5340909090909091 [0.576073,0.5,0.530619,0.624053,0.5,0.61774,0.607639,0.530619,0.618056,0.53125,0.617109,0.620581,0.5,0.565657,0.624684,0.525884,0.530934,0.499369,0.560922,0.499369,0.499684,0.60101,0.5,0.529987,0.5,0.5,0.529356,0.5,0.53125,0.53125,0.5,0.619003,0.53125,0.562184,0.565972,0.499684,0.530619,0.53125,0.53125,0.53125,0.5,0.53125,0.5,0.53125,0.586806,0.53125,0.616793,0.5,0.605114,0.53125,0.5,0.53125,0.52178,0.525253,0.5,0.5,0.5625,0.53125,0.53125,0.562184,0.5625,0.53125,0.499684,0.5625,0.5,0.53125,0.499053,0.528093,0.525568,0.55524,0.5,0.53125,0.530619,0.5,0.5,0.53125,0.5,0.530934,0.5,0.5,0.5,0.5,0.5,0.499684,0.5,0.53125,0.615215,0.5,0.5,0.5,0.5,0.5,0.5,0.596591,0.5,0.5625,0.576389,0.5,0.530303,0.573232] average_cost 0 kappa 0.06818181818181819 kb_relative_information_score 120.77877361299527 mean_absolute_error 0.01844999999999966 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] predictive_accuracy 0.0775 prior_entropy 6.6438561897747395 recall 0.0775 [0.25,0,0.0625,0.25,0,0.25,0.25,0.0625,0.25,0.0625,0.25,0.25,0,0.1875,0.25,0.0625,0.0625,0,0.125,0,0,0.25,0,0.0625,0,0,0.0625,0,0.0625,0.0625,0,0.25,0.0625,0.125,0.25,0,0.0625,0.0625,0.0625,0.0625,0,0.0625,0,0.0625,0.1875,0.0625,0.25,0,0.25,0.0625,0,0.0625,0.0625,0.0625,0,0,0.125,0.0625,0.0625,0.25,0.125,0.0625,0,0.125,0,0.0625,0,0.0625,0.0625,0.125,0,0.0625,0.0625,0,0,0.0625,0,0.0625,0,0,0,0,0,0,0,0.0625,0.25,0,0,0,0,0,0,0.25,0,0.125,0.1875,0,0.0625,0.25] relative_absolute_error 0.931818181818163 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.13583077707206 root_relative_squared_error 1.3651506743346413 total_cost 0 area_under_roc_curve 0.5377358490566039 [0.823899,0.5,0.5,0.996855,0.5,0.974843,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.962264,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.930818,0.5,0.5,0.874214] area_under_roc_curve 0.5314465408805031 [0.874214,0.5,0.5,1,0.5,0.981132,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.946541,0.5,0.5,0.5,0.496855,0.5,0.984277,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.977987,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.968553,0.943396,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.867925] area_under_roc_curve 0.5283018867924529 [0.5,0.5,0.5,0.996855,0.5,0.5,0.946541,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.924528,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.827044,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.90566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.949686,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.996855,0.5] area_under_roc_curve 0.5345911949685533 [0.5,0.5,0.5,0.996855,0.5,0.5,0.90566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.889937,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.786164,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.965409,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.496855,0.5] area_under_roc_curve 0.5283018867924529 [0.5,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.974843,0.5,0.5,0.5,0.5,0.449686,1,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.899371,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.836478,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.937107,0.5,0.5,0.5,0.5,0.496855,0.5] area_under_roc_curve 0.550314465408805 [0.5,0.5,0.5,0.5,0.5,0.5,0.987421,0.5,0.974843,0.5,0.5,0.5,0.5,0.955975,0.996855,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.984277,0.5,0.5,0.899371,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.849057,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.990566,0.5,0.5,0.5,0.5,0.5,0.5,0.937107,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5283018867924528 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.984277,0.987421,0.5,0.893082,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.962264,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.827044,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.91195,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5471698113207547 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.987421,0.990566,0.5,0.921384,1,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.987421,1,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.974843,0.5,0.5,0.5,0.974843,0.5,0.5,0.5,0.5,0.940252,0.5,0.5,0.5,0.5,0.5,0.861635,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.930818,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5440251572327044 [0.940252,0.5,0.993711,0.5,0.5,0.987421,0.5,0.5,0.5,1,0.974843,0.990566,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.977987,0.5,0.940252,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.927673,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.940252,0.5,0.5,0.886792] area_under_roc_curve 0.5283018867924528 [0.874214,0.5,0.5,0.5,0.5,0.984277,0.5,0.5,0.5,0.5,0.974843,0.987421,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.981132,0.5,0.924528,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.955975,0.5,0.5,0.855346] 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 0.07547169811320754 kappa 0.06289308176100629 kappa 0.05660377358490566 kappa 0.0691823899371069 kappa 0.05660377358490566 kappa 0.10062893081761005 kappa 0.05660377358490566 kappa 0.09433962264150943 kappa 0.0880503144654088 kappa 0.05660377358490566 kb_relative_information_score 12.679186802919855 kb_relative_information_score 10.674821997517387 kb_relative_information_score 9.672639594816188 kb_relative_information_score 11.677004400218612 kb_relative_information_score 9.67263959481618 kb_relative_information_score 16.687916413724732 kb_relative_information_score 9.672639594816184 kb_relative_information_score 15.685734011023515 kb_relative_information_score 14.683551608322285 kb_relative_information_score 9.672639594816184 mean_absolute_error 0.018375000000000013 mean_absolute_error 0.018625000000000013 mean_absolute_error 0.018750000000000013 mean_absolute_error 0.018500000000000013 mean_absolute_error 0.018750000000000013 mean_absolute_error 0.017875000000000012 mean_absolute_error 0.018750000000000013 mean_absolute_error 0.018000000000000013 mean_absolute_error 0.018125000000000013 mean_absolute_error 0.018750000000000013 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 0.08125 predictive_accuracy 0.06875 predictive_accuracy 0.0625 predictive_accuracy 0.075 predictive_accuracy 0.0625 predictive_accuracy 0.10625 predictive_accuracy 0.0625 predictive_accuracy 0.1 predictive_accuracy 0.09375 predictive_accuracy 0.0625 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 0.08125 [1,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1] recall 0.06875 [1,0,0,1,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1] recall 0.0625 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0] recall 0.075 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0] recall 0.0625 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0] recall 0.10625 [0,0,0,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0] recall 0.0625 [0,0,0,0,0,0,0,0,1,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0] recall 0.1 [0,0,0,0,0,0,0,0,1,0,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0] recall 0.09375 [1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1] recall 0.0625 [1,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1] relative_absolute_error 0.9280303030303021 relative_absolute_error 0.9406565656565649 relative_absolute_error 0.946969696969696 relative_absolute_error 0.9343434343434334 relative_absolute_error 0.946969696969696 relative_absolute_error 0.9027777777777769 relative_absolute_error 0.946969696969696 relative_absolute_error 0.9090909090909082 relative_absolute_error 0.9154040404040396 relative_absolute_error 0.946969696969696 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 0.13555441711725963 root_mean_squared_error 0.13647344063956185 root_mean_squared_error 0.13693063937629157 root_mean_squared_error 0.13601470508735447 root_mean_squared_error 0.13693063937629157 root_mean_squared_error 0.13369741957120942 root_mean_squared_error 0.13693063937629157 root_mean_squared_error 0.13416407864998742 root_mean_squared_error 0.13462912017836265 root_mean_squared_error 0.13693063937629157 root_relative_squared_error 1.3623731522826648 root_relative_squared_error 1.371609686212929 root_relative_squared_error 1.3762047064079501 root_relative_squared_error 1.366999220441207 root_relative_squared_error 1.3762047064079501 root_relative_squared_error 1.3437096247164246 root_relative_squared_error 1.3762047064079501 root_relative_squared_error 1.3483997249264836 root_relative_squared_error 1.3530735681433144 root_relative_squared_error 1.3762047064079501 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 690.8555709999291 usercpu_time_millis 726.5485279998529 usercpu_time_millis 689.4268050000392 usercpu_time_millis 700.340914000094 usercpu_time_millis 712.9545140001028 usercpu_time_millis 711.4427180000575 usercpu_time_millis 719.6485810000013 usercpu_time_millis 705.5477759998894 usercpu_time_millis 712.1909740000092 usercpu_time_millis 709.4018910000841 usercpu_time_millis_testing 88.55834899998172 usercpu_time_millis_testing 88.99092999990899 usercpu_time_millis_testing 88.37833200004752 usercpu_time_millis_testing 94.380787000091 usercpu_time_millis_testing 92.85687500005224 usercpu_time_millis_testing 93.1166980000171 usercpu_time_millis_testing 102.82019999999648 usercpu_time_millis_testing 91.90278899995974 usercpu_time_millis_testing 94.78632100001505 usercpu_time_millis_testing 93.82824000010714 usercpu_time_millis_training 602.2972219999474 usercpu_time_millis_training 637.5575979999439 usercpu_time_millis_training 601.0484729999916 usercpu_time_millis_training 605.960127000003 usercpu_time_millis_training 620.0976390000505 usercpu_time_millis_training 618.3260200000404 usercpu_time_millis_training 616.8283810000048 usercpu_time_millis_training 613.6449869999296 usercpu_time_millis_training 617.4046529999941 usercpu_time_millis_training 615.573650999977