8958232 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) 6893840 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 5993.249048403246 7650 cache_size 200 7650 class_weight null 7650 coef0 0.877456130537656 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 1.734127950151362 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.03234629344564362 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 18831732 description https://api.openml.org/data/download/18831732/description.xml -1 18831733 predictions https://api.openml.org/data/download/18831733/predictions.arff area_under_roc_curve 0.5268308080808083 [0.562184,0.5,0.53125,0.444444,0.5,0.473485,0.59375,0.53125,0.562184,0.53125,0.5,0.5625,0.5,0.5625,0.449495,0.53125,0.53125,0.49779,0.56029,0.498422,0.499684,0.5,0.5,0.53125,0.530619,0.499684,0.529356,0.53125,0.53125,0.53125,0.5,0.5,0.562184,0.562184,0.499053,0.530619,0.530303,0.530934,0.53125,0.53125,0.53125,0.53125,0.53125,0.5625,0.53125,0.53125,0.5625,0.53125,0.498422,0.53125,0.5,0.53125,0.59375,0.529987,0.5,0.499684,0.5,0.53125,0.530619,0.560922,0.5625,0.5625,0.530619,0.5625,0.5,0.530934,0.498737,0.59375,0.53125,0.5625,0.5,0.53125,0.530303,0.5,0.5,0.53125,0.5,0.561237,0.5,0.5,0.530934,0.499684,0.5,0.499684,0.5,0.53125,0.5625,0.53125,0.562184,0.5,0.562184,0.5,0.5,0.59375,0.5,0.5625,0.562184,0.5,0.528725,0.561869] average_cost 0 kappa 0.05366161616161616 kb_relative_information_score 97.72857835086705 mean_absolute_error 0.018737499999999657 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 0.063125 prior_entropy 6.6438561897747395 recall 0.063125 [0.125,0,0.0625,0.25,0,0.125,0.1875,0.0625,0.125,0.0625,0,0.125,0,0.125,0.25,0.0625,0.0625,0,0.125,0,0,0,0,0.0625,0.0625,0,0.0625,0.0625,0.0625,0.0625,0,0,0.125,0.125,0,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.125,0.0625,0.0625,0.125,0.0625,0,0.0625,0,0.0625,0.1875,0.0625,0,0,0,0.0625,0.0625,0.125,0.125,0.125,0.0625,0.125,0,0.0625,0,0.1875,0.0625,0.125,0,0.0625,0.0625,0,0,0.0625,0,0.125,0,0,0.0625,0,0,0,0,0.0625,0.125,0.0625,0.125,0,0.125,0,0,0.1875,0,0.125,0.125,0,0.0625,0.125] relative_absolute_error 0.9463383838383648 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.13688498822003695 root_relative_squared_error 1.3757458950244879 total_cost 0 area_under_roc_curve 0.5377358490566038 [0.5,0.5,0.5,0.556604,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,1,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.496855,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855] area_under_roc_curve 0.5220125786163522 [0.5,0.5,0.5,0.537736,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5283018867924528 [0.5,0.5,0.5,0.553459,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,0.496855,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.993711,0.5] area_under_roc_curve 0.5314465408805031 [0.5,0.5,0.5,0.553459,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.487421,0.5] area_under_roc_curve 0.5094339622641509 [0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.540881,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5] area_under_roc_curve 0.5408805031446541 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.572327,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,1,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.496855,0.5] area_under_roc_curve 0.5251572327044025 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,1,0.5,1,0.544025,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5314465408805031 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.59434,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,0.5,0.996855,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.490566,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5408805031446542 [0.996855,0.5,1,0.5,0.5,0.566038,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.493711,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.996855] area_under_roc_curve 0.5188679245283019 [1,0.5,0.5,0.5,0.5,0.550314,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5] 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 0.04402515723270441 kappa 0.05660377358490566 kappa 0.06289308176100629 kappa 0.01886792452830189 kappa 0.08176100628930816 kappa 0.050314465408805034 kappa 0.06289308176100629 kappa 0.08176100628930816 kappa 0.03773584905660377 kb_relative_information_score 12.679186802919867 kb_relative_information_score 7.668274789413733 kb_relative_information_score 9.672639594816184 kb_relative_information_score 10.674821997517387 kb_relative_information_score 3.659545178608888 kb_relative_information_score 13.681369205621065 kb_relative_information_score 8.67045719211495 kb_relative_information_score 10.674821997517402 kb_relative_information_score 13.681369205621063 kb_relative_information_score 6.666092386712528 mean_absolute_error 0.018375000000000013 mean_absolute_error 0.019000000000000013 mean_absolute_error 0.018750000000000013 mean_absolute_error 0.018625000000000013 mean_absolute_error 0.019500000000000014 mean_absolute_error 0.018250000000000013 mean_absolute_error 0.018875000000000013 mean_absolute_error 0.018625000000000013 mean_absolute_error 0.018250000000000013 mean_absolute_error 0.019125000000000014 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 0.05 predictive_accuracy 0.0625 predictive_accuracy 0.06875 predictive_accuracy 0.025 predictive_accuracy 0.0875 predictive_accuracy 0.05625 predictive_accuracy 0.06875 predictive_accuracy 0.0875 predictive_accuracy 0.04375 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 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1] recall 0.05 [0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0625 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0] recall 0.06875 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0] recall 0.025 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.0875 [0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,1,0,0,0,0,0,0] recall 0.05625 [0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0] recall 0.06875 [0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0] recall 0.0875 [1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1] recall 0.04375 [1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0] relative_absolute_error 0.9280303030303021 relative_absolute_error 0.9595959595959586 relative_absolute_error 0.946969696969696 relative_absolute_error 0.9406565656565649 relative_absolute_error 0.9848484848484839 relative_absolute_error 0.9217171717171708 relative_absolute_error 0.9532828282828274 relative_absolute_error 0.9406565656565649 relative_absolute_error 0.9217171717171708 relative_absolute_error 0.96590909090909 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 0.13784048752090228 root_mean_squared_error 0.13693063937629157 root_mean_squared_error 0.13647344063956185 root_mean_squared_error 0.13964240043768947 root_mean_squared_error 0.135092560861063 root_mean_squared_error 0.1373863166403409 root_mean_squared_error 0.13647344063956185 root_mean_squared_error 0.135092560861063 root_mean_squared_error 0.13829316685939336 root_relative_squared_error 1.3623731522826648 root_relative_squared_error 1.3853490243227224 root_relative_squared_error 1.3762047064079501 root_relative_squared_error 1.371609686212929 root_relative_squared_error 1.4034589305344736 root_relative_squared_error 1.357731322255748 root_relative_squared_error 1.3807844352271845 root_relative_squared_error 1.371609686212929 root_relative_squared_error 1.357731322255748 root_relative_squared_error 1.389898622856423 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 702.8529220000337 usercpu_time_millis 702.5134610000805 usercpu_time_millis 692.8443220000418 usercpu_time_millis 699.6538569999302 usercpu_time_millis 720.1322309999796 usercpu_time_millis 699.8506069999166 usercpu_time_millis 699.8914819999982 usercpu_time_millis 699.1975199999843 usercpu_time_millis 690.4358140000113 usercpu_time_millis 718.8510390000147 usercpu_time_millis_testing 51.82290900006592 usercpu_time_millis_testing 50.7097550000708 usercpu_time_millis_testing 52.8030770000214 usercpu_time_millis_testing 51.85547399992174 usercpu_time_millis_testing 54.41336599994884 usercpu_time_millis_testing 52.55848000001606 usercpu_time_millis_testing 54.638307000004716 usercpu_time_millis_testing 54.310954000015954 usercpu_time_millis_testing 53.59830400004739 usercpu_time_millis_testing 56.633098000020254 usercpu_time_millis_training 651.0300129999678 usercpu_time_millis_training 651.8037060000097 usercpu_time_millis_training 640.0412450000204 usercpu_time_millis_training 647.7983830000085 usercpu_time_millis_training 665.7188650000307 usercpu_time_millis_training 647.2921269999006 usercpu_time_millis_training 645.2531749999935 usercpu_time_millis_training 644.8865659999683 usercpu_time_millis_training 636.8375099999639 usercpu_time_millis_training 662.2179409999944