8956150 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) 6891766 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 3074.23836316206 7650 cache_size 200 7650 class_weight null 7650 coef0 0.8293006657184324 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.9509306147786704 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.02075881998712856 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 18827588 description https://api.openml.org/data/download/18827588/description.xml -1 18827589 predictions https://api.openml.org/data/download/18827589/predictions.arff area_under_roc_curve 0.5363005050505051 [0.562184,0.5,0.53125,0.453914,0.5,0.476326,0.625,0.53125,0.562184,0.5625,0.5,0.59375,0.53125,0.5625,0.457386,0.53125,0.5625,0.52904,0.558712,0.498106,0.530934,0.5,0.5625,0.53125,0.561869,0.499369,0.560606,0.530934,0.53125,0.5625,0.5,0.53125,0.5625,0.560922,0.529356,0.530619,0.530303,0.530619,0.59375,0.53125,0.530934,0.53125,0.53125,0.5625,0.53125,0.53125,0.5625,0.53125,0.498422,0.53125,0.530934,0.530934,0.593434,0.529987,0.499684,0.499369,0.5,0.53125,0.530303,0.592172,0.59375,0.5625,0.561869,0.5625,0.5,0.530934,0.498422,0.59375,0.53125,0.5625,0.499684,0.5625,0.529672,0.5,0.5,0.53125,0.5625,0.560922,0.5,0.5,0.562184,0.499684,0.5,0.530934,0.53125,0.53125,0.5625,0.53125,0.562184,0.530934,0.562184,0.5625,0.5,0.59375,0.5,0.5625,0.561553,0.53125,0.528093,0.561237] average_cost 0 kappa 0.07260101010101011 kb_relative_information_score 127.79405043190425 mean_absolute_error 0.018362499999999664 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 0.081875 prior_entropy 6.6438561897747395 recall 0.081875 [0.125,0,0.0625,0.25,0,0.125,0.25,0.0625,0.125,0.125,0,0.1875,0.0625,0.125,0.25,0.0625,0.125,0.0625,0.125,0,0.0625,0,0.125,0.0625,0.125,0,0.125,0.0625,0.0625,0.125,0,0.0625,0.125,0.125,0.0625,0.0625,0.0625,0.0625,0.1875,0.0625,0.0625,0.0625,0.0625,0.125,0.0625,0.0625,0.125,0.0625,0,0.0625,0.0625,0.0625,0.1875,0.0625,0,0,0,0.0625,0.0625,0.1875,0.1875,0.125,0.125,0.125,0,0.0625,0,0.1875,0.0625,0.125,0,0.125,0.0625,0,0,0.0625,0.125,0.125,0,0,0.125,0,0,0.0625,0.0625,0.0625,0.125,0.0625,0.125,0.0625,0.125,0.125,0,0.1875,0,0.125,0.125,0.0625,0.0625,0.125] relative_absolute_error 0.9273989898989713 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.13550830232867528 root_relative_squared_error 1.3619096812189648 total_cost 0 area_under_roc_curve 0.5471698113207546 [0.5,0.5,0.5,0.578616,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.493711,1,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.493711,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566] area_under_roc_curve 0.5345911949685535 [0.5,0.5,0.5,0.553459,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.996855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.496855,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5440251572327043 [0.5,0.5,0.5,0.591195,0.5,0.5,1,0.5,0.5,0.75,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,0.496855,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.996855,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.990566,0.5] area_under_roc_curve 0.5440251572327044 [0.5,0.5,0.5,0.572327,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.496855,0.5,1,0.5,0.5,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.487421,0.5] area_under_roc_curve 0.5188679245283019 [0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.559748,0.5,0.5,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,1,0.493711,0.5] area_under_roc_curve 0.5503144654088051 [0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.597484,0.5,0.5,0.5,0.981132,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,1,1,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.496855,0.5] area_under_roc_curve 0.5314465408805031 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,1,0.5,1,0.562893,0.5,1,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,1,0.5,0.5,0.5,0.5,0.5,1,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5408805031446541 [0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.610063,0.5,0.5,0.493711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5,0.5,1,1,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.490566,0.5,0.5,0.5,0.5,0.987421,0.5,0.5,0.5,0.5,0.5,0.493711,0.5,0.5,1,0.5,0.5,0.5,0.493711,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,1,0.487421,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5] area_under_roc_curve 0.5471698113207547 [0.996855,0.5,1,0.5,0.5,0.575472,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.490566,0.5,0.5,1,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.996855] area_under_roc_curve 0.5220125786163522 [1,0.5,0.5,0.5,0.5,0.569182,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.487421,0.5,0.487421,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.990566,0.5,0.5,0.5] 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 0.09433962264150943 kappa 0.0691823899371069 kappa 0.08801446597743623 kappa 0.0880503144654088 kappa 0.03773584905660377 kappa 0.10062893081761005 kappa 0.06289308176100629 kappa 0.08176100628930816 kappa 0.09433962264150943 kappa 0.04402515723270441 kb_relative_information_score 15.685734011023504 kb_relative_information_score 11.677004400218607 kb_relative_information_score 14.683551608322295 kb_relative_information_score 14.683551608322277 kb_relative_information_score 6.666092386712543 kb_relative_information_score 16.687916413724732 kb_relative_information_score 10.6748219975174 kb_relative_information_score 13.681369205621065 kb_relative_information_score 15.685734011023506 kb_relative_information_score 7.668274789413723 mean_absolute_error 0.018000000000000013 mean_absolute_error 0.018500000000000013 mean_absolute_error 0.018125000000000013 mean_absolute_error 0.018125000000000013 mean_absolute_error 0.019125000000000014 mean_absolute_error 0.017875000000000012 mean_absolute_error 0.018625000000000013 mean_absolute_error 0.018250000000000013 mean_absolute_error 0.018000000000000013 mean_absolute_error 0.019000000000000013 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 0.1 predictive_accuracy 0.075 predictive_accuracy 0.09375 predictive_accuracy 0.09375 predictive_accuracy 0.04375 predictive_accuracy 0.10625 predictive_accuracy 0.06875 predictive_accuracy 0.0875 predictive_accuracy 0.1 predictive_accuracy 0.05 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 0.1 [0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,1,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1] recall 0.075 [0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0] recall 0.09375 [0,0,0,1,0,0,1,0,0,0.5,0,0,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,1,0,0,0,1,0,0,1,0] recall 0.09375 [0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,1,0,0,0,0] recall 0.04375 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0] recall 0.10625 [0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,0,1,0,0,1,0,0,0,0,0,0] recall 0.06875 [0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0] recall 0.0875 [0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0] recall 0.1 [1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1] recall 0.05 [1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0] relative_absolute_error 0.9090909090909082 relative_absolute_error 0.9343434343434334 relative_absolute_error 0.9154040404040396 relative_absolute_error 0.9154040404040396 relative_absolute_error 0.96590909090909 relative_absolute_error 0.9027777777777769 relative_absolute_error 0.9406565656565649 relative_absolute_error 0.9217171717171708 relative_absolute_error 0.9090909090909082 relative_absolute_error 0.9595959595959586 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 0.13416407864998742 root_mean_squared_error 0.13601470508735447 root_mean_squared_error 0.13462912017836265 root_mean_squared_error 0.13462912017836265 root_mean_squared_error 0.13829316685939336 root_mean_squared_error 0.13369741957120942 root_mean_squared_error 0.13647344063956185 root_mean_squared_error 0.135092560861063 root_mean_squared_error 0.13416407864998742 root_mean_squared_error 0.13784048752090228 root_relative_squared_error 1.3483997249264836 root_relative_squared_error 1.366999220441207 root_relative_squared_error 1.3530735681433144 root_relative_squared_error 1.3530735681433144 root_relative_squared_error 1.389898622856423 root_relative_squared_error 1.3437096247164246 root_relative_squared_error 1.371609686212929 root_relative_squared_error 1.357731322255748 root_relative_squared_error 1.3483997249264836 root_relative_squared_error 1.3853490243227224 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 678.4705440000067 usercpu_time_millis 676.223068000013 usercpu_time_millis 674.6407870000155 usercpu_time_millis 680.3581580000042 usercpu_time_millis 678.2000129999943 usercpu_time_millis 688.2561339999995 usercpu_time_millis 676.3054280000063 usercpu_time_millis 687.461153000001 usercpu_time_millis 702.4159200000071 usercpu_time_millis 696.0041459999928 usercpu_time_millis_testing 49.603500000003464 usercpu_time_millis_testing 49.34652100000392 usercpu_time_millis_testing 49.777013000010584 usercpu_time_millis_testing 49.7630499999957 usercpu_time_millis_testing 49.44797000000278 usercpu_time_millis_testing 49.18016199999897 usercpu_time_millis_testing 50.115306999998666 usercpu_time_millis_testing 52.123249000004535 usercpu_time_millis_testing 51.94908200000725 usercpu_time_millis_testing 53.10445799999286 usercpu_time_millis_training 628.8670440000033 usercpu_time_millis_training 626.876547000009 usercpu_time_millis_training 624.8637740000049 usercpu_time_millis_training 630.5951080000085 usercpu_time_millis_training 628.7520429999915 usercpu_time_millis_training 639.0759720000005 usercpu_time_millis_training 626.1901210000076 usercpu_time_millis_training 635.3379039999965 usercpu_time_millis_training 650.4668379999998 usercpu_time_millis_training 642.899688