8958817 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) 6894421 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 5807.557411431184 7650 cache_size 200 7650 class_weight null 7650 coef0 0.8751857897866393 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 1.6856958053396478 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking true 7650 tol 0.03167693541608487 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 18832894 description https://api.openml.org/data/download/18832894/description.xml -1 18832895 predictions https://api.openml.org/data/download/18832895/predictions.arff area_under_roc_curve 0.5274621212121214 [0.562184,0.5,0.53125,0.44476,0.5,0.473485,0.59375,0.53125,0.562184,0.53125,0.5,0.5625,0.5,0.5625,0.450442,0.53125,0.53125,0.49779,0.56029,0.498422,0.499684,0.5,0.5,0.53125,0.561869,0.499684,0.529356,0.53125,0.53125,0.53125,0.5,0.5,0.562184,0.562184,0.498737,0.530619,0.530303,0.530934,0.53125,0.53125,0.53125,0.53125,0.53125,0.5625,0.53125,0.53125,0.5625,0.53125,0.498422,0.53125,0.5,0.53125,0.59375,0.529987,0.5,0.499684,0.5,0.53125,0.530619,0.560922,0.5625,0.5625,0.561869,0.5625,0.5,0.530934,0.498422,0.59375,0.53125,0.5625,0.5,0.53125,0.530303,0.5,0.5,0.53125,0.5,0.561237,0.5,0.5,0.530934,0.499684,0.5,0.499684,0.5,0.53125,0.5625,0.53125,0.562184,0.5,0.562184,0.5,0.5,0.59375,0.5,0.5625,0.562184,0.5,0.528725,0.561869] average_cost 0 kappa 0.054924242424242424 kb_relative_information_score 99.7329431562696 mean_absolute_error 0.018712499999999656 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 0.064375 prior_entropy 6.6438561897747395 recall 0.064375 [0.125,0,0.0625,0.25,0,0.125,0.1875,0.0625,0.125,0.0625,0,0.125,0,0.125,0.25,0.0625,0.0625,0,0.125,0,0,0,0,0.0625,0.125,0,0.0625,0.0625,0.0625,0.0625,0,0,0.125,0.125,0,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.0625,0.125,0.0625,0.0625,0.125,0.0625,0,0.0625,0,0.0625,0.1875,0.0625,0,0,0,0.0625,0.0625,0.125,0.125,0.125,0.125,0.125,0,0.0625,0,0.1875,0.0625,0.125,0,0.0625,0.0625,0,0,0.0625,0,0.125,0,0,0.0625,0,0,0,0,0.0625,0.125,0.0625,0.125,0,0.125,0,0,0.1875,0,0.125,0.125,0,0.0625,0.125] relative_absolute_error 0.9450757575757385 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.13679364020304327 root_relative_squared_error 1.374827812910212 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 0.5345911949685533 [0.5,0.5,0.5,0.556604,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.487421,0.5] area_under_roc_curve 0.5094339622641509 [0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.544025,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5] area_under_roc_curve 0.5408805031446542 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.575472,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,1,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.496855,0.5] 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 0.5345911949685533 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.597484,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,0.5,0.996855,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.490566,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5] 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 0.0691823899371069 kappa 0.01886792452830189 kappa 0.08176100628930816 kappa 0.050314465408805034 kappa 0.0691823899371069 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 11.677004400218607 kb_relative_information_score 3.659545178608888 kb_relative_information_score 13.681369205621065 kb_relative_information_score 8.67045719211495 kb_relative_information_score 11.677004400218621 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 0.018500000000000013 mean_absolute_error 0.019500000000000014 mean_absolute_error 0.018250000000000013 mean_absolute_error 0.018875000000000013 mean_absolute_error 0.018500000000000013 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 0.075 predictive_accuracy 0.025 predictive_accuracy 0.0875 predictive_accuracy 0.05625 predictive_accuracy 0.075 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 0.075 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0] 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 0.075 [0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0] 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 0.9343434343434334 relative_absolute_error 0.9848484848484839 relative_absolute_error 0.9217171717171708 relative_absolute_error 0.9532828282828274 relative_absolute_error 0.9343434343434334 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 0.13601470508735447 root_mean_squared_error 0.13964240043768947 root_mean_squared_error 0.135092560861063 root_mean_squared_error 0.1373863166403409 root_mean_squared_error 0.13601470508735447 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 1.366999220441207 root_relative_squared_error 1.4034589305344736 root_relative_squared_error 1.357731322255748 root_relative_squared_error 1.3807844352271845 root_relative_squared_error 1.366999220441207 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 733.0131659998642 usercpu_time_millis 744.2477290001079 usercpu_time_millis 734.8117369997453 usercpu_time_millis 747.1421290001672 usercpu_time_millis 753.0745290002869 usercpu_time_millis 766.8125169998348 usercpu_time_millis 769.331623999733 usercpu_time_millis 747.6681810001082 usercpu_time_millis 751.7420289998427 usercpu_time_millis 768.7103770001613 usercpu_time_millis_testing 53.663534999941476 usercpu_time_millis_testing 56.735308000043005 usercpu_time_millis_testing 55.838835999793446 usercpu_time_millis_testing 55.9154560000934 usercpu_time_millis_testing 56.30015400015509 usercpu_time_millis_testing 61.01693699997668 usercpu_time_millis_testing 71.49306499991326 usercpu_time_millis_testing 57.829569999967134 usercpu_time_millis_testing 53.81076199978452 usercpu_time_millis_testing 58.454981000068074 usercpu_time_millis_training 679.3496309999227 usercpu_time_millis_training 687.5124210000649 usercpu_time_millis_training 678.9729009999519 usercpu_time_millis_training 691.2266730000738 usercpu_time_millis_training 696.7743750001318 usercpu_time_millis_training 705.7955799998581 usercpu_time_millis_training 697.8385589998197 usercpu_time_millis_training 689.8386110001411 usercpu_time_millis_training 697.9312670000581 usercpu_time_millis_training 710.2553960000932