8958969 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) 6894573 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 1002.3609892875838 7650 cache_size 200 7650 class_weight null 7650 coef0 0.7484593228765275 7650 decision_function_shape "ovr" 7650 degree 3 7650 gamma 0.34682211793029805 7650 kernel "rbf" 7650 max_iter -1 7650 probability false 7650 random_state 1 7650 shrinking false 7650 tol 0.009859100450812775 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 18833194 description https://api.openml.org/data/download/18833194/description.xml -1 18833195 predictions https://api.openml.org/data/download/18833195/predictions.arff area_under_roc_curve 0.6265782828282828 [0.561553,0.562184,0.59375,0.498106,0.625,0.56029,0.625,0.53125,0.593119,0.71875,0.530619,0.625,0.718434,0.561553,0.505366,0.5625,0.65625,0.622475,0.591225,0.526831,0.65625,0.53125,0.65625,0.59375,0.655934,0.717172,0.590278,0.655934,0.625,0.78125,0.8125,0.5625,0.687184,0.779356,0.589331,0.874369,0.71654,0.62279,0.625,0.5625,0.593119,0.5625,0.75,0.749684,0.530934,0.65625,0.562184,0.53125,0.592172,0.624684,0.624684,0.593119,0.625,0.623737,0.561237,0.685606,0.59375,0.625,0.654987,0.592172,0.749369,0.780934,0.624053,0.5625,0.624684,0.624053,0.62279,0.59375,0.59375,0.592803,0.718119,0.5625,0.77904,0.5625,0.530934,0.593434,0.71875,0.592172,0.59375,0.59375,0.593434,0.749369,0.625,0.779987,0.687184,0.65625,0.5625,0.593434,0.59375,0.65625,0.8125,0.5625,0.59375,0.593434,0.5625,0.625,0.592803,0.624684,0.559659,0.623737] average_cost 0 f_measure 0.35354592294362325 [0.190476,0.210526,0.315789,0.018957,0.4,0.035556,0.4,0.117647,0.285714,0.608696,0.105263,0.4,0.583333,0.190476,0.02005,0.222222,0.47619,0.285714,0.222222,0.064516,0.47619,0.117647,0.47619,0.315789,0.454545,0.5,0.2,0.454545,0.4,0.72,0.769231,0.222222,0.521739,0.580645,0.181818,0.8,0.466667,0.296296,0.4,0.222222,0.285714,0.222222,0.666667,0.64,0.111111,0.47619,0.210526,0.117647,0.25,0.380952,0.380952,0.285714,0.4,0.333333,0.181818,0.428571,0.315789,0.4,0.4,0.25,0.615385,0.692308,0.347826,0.222222,0.380952,0.347826,0.296296,0.315789,0.315789,0.272727,0.56,0.222222,0.5625,0.222222,0.111111,0.3,0.608696,0.25,0.315789,0.315789,0.3,0.615385,0.4,0.62069,0.521739,0.47619,0.222222,0.3,0.315789,0.47619,0.769231,0.222222,0.315789,0.3,0.222222,0.4,0.272727,0.380952,0.148148,0.333333] kappa 0.25315656565656564 kb_relative_information_score 414.4182176044539 mean_absolute_error 0.01478749999999974 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] precision 0.7435332495011422 [0.4,0.666667,1,0.009852,1,0.019139,1,1,0.6,1,0.333333,1,0.875,0.4,0.010444,1,1,0.333333,0.272727,0.066667,1,1,1,1,0.833333,0.583333,0.214286,0.833333,1,1,1,1,0.857143,0.6,0.176471,0.857143,0.5,0.363636,1,1,0.6,1,1,0.888889,0.5,1,0.666667,1,0.375,0.8,0.8,0.6,1,0.5,0.333333,0.5,1,1,0.555556,0.375,0.8,0.9,0.571429,1,0.8,0.571429,0.363636,1,1,0.5,0.777778,1,0.5625,1,0.5,0.75,1,0.375,1,1,0.75,0.8,1,0.692308,0.857143,1,1,0.75,1,1,1,1,1,0.75,1,1,0.5,0.8,0.181818,0.5] predictive_accuracy 0.260625 prior_entropy 6.6438561897747395 recall 0.260625 [0.125,0.125,0.1875,0.25,0.25,0.25,0.25,0.0625,0.1875,0.4375,0.0625,0.25,0.4375,0.125,0.25,0.125,0.3125,0.25,0.1875,0.0625,0.3125,0.0625,0.3125,0.1875,0.3125,0.4375,0.1875,0.3125,0.25,0.5625,0.625,0.125,0.375,0.5625,0.1875,0.75,0.4375,0.25,0.25,0.125,0.1875,0.125,0.5,0.5,0.0625,0.3125,0.125,0.0625,0.1875,0.25,0.25,0.1875,0.25,0.25,0.125,0.375,0.1875,0.25,0.3125,0.1875,0.5,0.5625,0.25,0.125,0.25,0.25,0.25,0.1875,0.1875,0.1875,0.4375,0.125,0.5625,0.125,0.0625,0.1875,0.4375,0.1875,0.1875,0.1875,0.1875,0.5,0.25,0.5625,0.375,0.3125,0.125,0.1875,0.1875,0.3125,0.625,0.125,0.1875,0.1875,0.125,0.25,0.1875,0.25,0.125,0.25] relative_absolute_error 0.7468434343434198 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.12160386507015203 root_relative_squared_error 1.222164828771815 total_cost 0 area_under_roc_curve 0.6351803200382135 [0.5,0.5,0.5,0.698113,0.5,0.990566,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.993711,1,1,1,0.5,0.5,0.75,0.5,0.75,0.5,0.5,0.75,0.5,0.75,0.496835,0.5,0.996855,0.996855,0.993711,1,0.75,1,1,0.5,0.75,0.5,0.5,1,1,0.5,0.5,0.75,0.5,1,0.5,0.493711,0.493711,0.5,1,0.5,0.5,1,0.996855,0.5,0.5,1,0.75,0.5,1,1,0.996855,0.5,1,0.75,0.5,0.496855,0.5,0.5,0.5,0.75,0.5,0.5,0.996835,0.5,1,0.5,0.5,0.5,0.75,0.5,1,1,0.5,0.75,0.5,0.5,0.5,1,0.5,0.5,0.993711] area_under_roc_curve 0.6225818008120372 [0.493711,0.5,0.5,0.669811,0.5,1,0.5,1,0.5,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.484277,1,0.5,1,1,1,0.746835,0.496835,0.5,0.75,1,0.75,0.5,0.5,1,0.5,0.496855,0.496855,0.5,0.5,0.5,0.993711,1,0.75,0.5,0.5,0.75,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.496855,0.5,1,1,0.5,1,1,0.5,0.5,1,0.5,0.496835,1,1,0.5,0.75,1,0.75,0.5,0.5,0.75,0.5,0.5,0.75,0.5,0.5,0.75,0.5,0.5,0.75,0.75,0.5,0.5,0.5,0.5,0.75,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1] area_under_roc_curve 0.6320356659501631 [0.5,0.5,0.5,0.68239,0.5,0.5,1,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.496835,0.5,0.5,0.5,1,0.996855,0.746835,0.5,0.996855,0.5,0.75,1,0.5,0.75,0.5,0.487421,1,0.996855,1,1,0.5,0.5,0.5,1,0.5,0.5,1,0.5,0.5,0.5,0.75,0.5,0.996855,1,0.75,0.996855,1,1,0.5,0.493711,0.5,1,1,0.5,0.5,0.5,0.75,0.75,0.5,0.5,0.5,0.75,0.5,0.993711,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.75,0.5,0.5,1,1,1,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,1,0.5,0.75,0.996855,0.5] area_under_roc_curve 0.6351604171642384 [0.5,0.5,0.5,0.685535,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,0.5,0.493711,0.496835,1,0.5,0.75,1,1,0.746835,0.5,1,0.75,1,0.5,0.5,0.75,0.75,0.993711,0.5,0.5,0.493711,1,0.5,0.75,0.5,1,1,0.5,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,0.996855,0.746835,1,0.75,1,0.5,0.996855,1,0.5,1,0.75,0.5,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.5,1,0.5,0.5,0.75,0.5,0.75,0.5,1,0.5,0.75,0.496855,1,0.5,0.75,0.5,1,0.5,1,0.5,0.5,0.5,1,0.5,0.5,0.490566,0.5] area_under_roc_curve 0.613127935673911 [0.5,0.496855,0.5,0.5,1,0.5,1,0.5,1,0.75,0.5,0.5,0.5,0.493711,0.676101,0.5,0.75,0.746835,0.993711,0.5,0.75,0.5,0.75,0.5,0.5,0.75,0.5,1,0.5,0.5,1,0.5,0.5,0.746835,0.996855,1,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,1,0.5,0.5,0.5,0.5,0.746835,0.996855,0.5,0.75,0.496855,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,0.75,0.5,0.993711,0.5,0.5,0.5,0.75,0.5,0.5,1,1,0.75,0.75,0.746835,1,0.5,0.5,0.5,0.5,0.5,1,0.5,0.5,0.5,0.5,1,0.5,1,0.493711,0.5] area_under_roc_curve 0.6287914974922378 [0.5,1,0.5,0.5,1,0.5,1,0.5,1,0.5,0.5,0.5,0.496855,0.5,0.720126,0.5,0.5,0.746835,0.987421,0.5,0.5,0.5,0.5,0.5,0.5,0.746835,0.5,0.5,1,1,1,1,0.5,0.746835,0.977987,0.75,0.496835,0.5,0.5,0.5,0.5,0.5,0.5,0.996855,0.5,0.5,0.5,0.5,0.5,0.75,1,1,0.5,1,0.5,0.496835,1,0.5,0.5,0.996855,0.75,0.75,0.996855,1,0.5,0.5,0.996855,0.5,0.5,0.5,0.75,0.5,0.996855,0.5,0.5,1,0.75,0.5,0.5,0.5,0.996855,0.496835,0.5,0.746835,0.5,1,1,0.996855,0.5,0.75,1,0.5,1,1,0.5,1,0.5,0.496855,0.493711,0.5] area_under_roc_curve 0.6351604171642384 [0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.496855,0.5,0.5,1,0.75,1,0.679245,0.5,1,1,0.5,0.5,0.5,0.5,0.75,0.5,0.5,0.5,0.993711,0.5,0.5,0.75,0.5,0.5,1,0.996855,0.5,1,0.496835,0.496835,0.75,0.5,0.5,0.5,0.75,1,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.75,0.5,0.5,1,0.5,0.5,0.5,0.996855,0.746835,0.5,0.996855,0.5,0.5,0.5,0.993711,0.5,0.5,0.5,1,0.5,0.75,1,0.5,0.5,1,0.996855,0.5,0.5,0.5,0.5,0.75,1,1,0.5,0.5,0.5,0.5,1,1,0.5,0.5,0.996855,1,0.5,0.5,1,0.5,0.5] area_under_roc_curve 0.65088368760449 [0.5,1,1,0.5,1,0.5,0.5,0.5,0.996855,0.75,0.5,1,0.75,0.996855,0.732704,0.5,1,0.993711,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,0.984277,0.5,0.5,0.75,1,1,1,1,0.5,1,0.996835,0.746835,0.5,1,0.5,0.5,0.75,0.5,1,0.5,0.5,0.5,0.990566,0.5,0.496855,0.5,0.5,0.987421,0.5,0.75,0.5,0.75,0.746835,0.493711,0.75,0.75,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,1,0.5,1,1,0.5,0.996855,1,0.490566,1,1,0.5,0.5,0.5,0.75,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,1,1,0.5,0.5,0.5,0.75,0.5] area_under_roc_curve 0.6351604171642387 [0.996855,0.5,1,0.5,0.5,0.704403,0.5,0.5,0.5,1,0.496855,1,0.5,0.5,0.5,1,1,0.493711,0.5,0.493711,0.75,0.5,0.5,0.5,0.5,0.5,0.990566,0.75,0.75,1,1,0.5,0.496855,0.996855,0.5,1,0.75,0.496835,0.5,0.5,0.5,0.5,0.75,0.75,0.5,0.75,0.5,0.5,0.996855,1,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,0.5,0.75,0.75,0.5,1,0.996855,0.496835,1,0.5,0.996855,0.996855,0.5,0.496835,0.5,0.5,0.5,1,0.996855,0.5,0.5,0.5,1,1,0.996855,0.75,0.75,0.5,0.5,1,0.5,0.75,0.5,0.75,0.5,0.5,0.5,0.996855,0.75,0.5,0.996855] area_under_roc_curve 0.591155162805509 [1,0.5,0.5,0.5,0.5,0.660377,0.5,0.5,0.5,0.5,0.996855,1,0.75,0.5,0.5,0.5,1,0.493711,0.5,0.490566,0.5,0.5,0.5,0.5,0.75,0.996855,0.5,0.5,0.5,0.5,0.75,0.5,1,0.996855,0.5,0.75,0.496835,0.75,0.5,0.5,0.5,0.5,0.75,1,0.5,0.75,0.996855,0.5,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.496855,0.5,0.5,0.5,0.5,0.75,0.75,0.5,0.5,0.496855,0.993711,0.5,0.5,0.5,0.996855,0.496855,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.5,0.75,0.5,1,0.996855,0.5,0.5,0.5,0.5,1,0.5,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.5,0.496835,0.996855] 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 0.26992368814412715 kappa 0.24462978991266032 kappa 0.2636299268350248 kappa 0.2698662470495673 kappa 0.22574553466047684 kappa 0.2572777340676633 kappa 0.2697513377400063 kappa 0.3012275731822474 kappa 0.2698087969155717 kappa 0.18187539332913782 kb_relative_information_score 43.74684128665785 kb_relative_information_score 39.73811167585295 kb_relative_information_score 42.74465888395661 kb_relative_information_score 43.746841286657855 kb_relative_information_score 36.73156446774922 kb_relative_information_score 41.74247648125538 kb_relative_information_score 43.7468412866579 kb_relative_information_score 48.757753300164076 kb_relative_information_score 43.74684128665785 kb_relative_information_score 29.716287648840638 mean_absolute_error 0.01450000000000001 mean_absolute_error 0.01500000000000001 mean_absolute_error 0.01462500000000001 mean_absolute_error 0.01450000000000001 mean_absolute_error 0.01537500000000001 mean_absolute_error 0.01475000000000001 mean_absolute_error 0.01450000000000001 mean_absolute_error 0.013875000000000009 mean_absolute_error 0.01450000000000001 mean_absolute_error 0.01625000000000001 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 0.275 predictive_accuracy 0.25 predictive_accuracy 0.26875 predictive_accuracy 0.275 predictive_accuracy 0.23125 predictive_accuracy 0.2625 predictive_accuracy 0.275 predictive_accuracy 0.30625 predictive_accuracy 0.275 predictive_accuracy 0.1875 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 0.275 [0,0,0,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0.5,0,0.5,0,0,0.5,0,0.5,0,0,1,1,1,1,0.5,1,1,0,0.5,0,0,1,1,0,0,0.5,0,1,0,0,0,0,1,0,0,1,1,0,0,1,0.5,0,1,1,1,0,1,0.5,0,0,0,0,0,0.5,0,0,1,0,1,0,0,0,0.5,0,1,1,0,0.5,0,0,0,1,0,0,1] recall 0.25 [0,0,0,1,0,1,0,1,0,1,0,0,1,0,0,1,0,0,0,0,1,0,1,1,1,0.5,0,0,0.5,1,0.5,0,0,1,0,0,0,0,0,0,1,1,0.5,0,0,0.5,0,0,0,0,1,0,0,0,0,0,0,1,1,0,1,1,0,0,1,0,0,1,1,0,0.5,1,0.5,0,0,0.5,0,0,0.5,0,0,0.5,0,0,0.5,0.5,0,0,0,0,0.5,0,0,0,0,0,0,0,0,1] recall 0.26875 [0,0,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,1,1,0.5,0,1,0,0.5,1,0,0.5,0,0,1,1,1,1,0,0,0,1,0,0,1,0,0,0,0.5,0,1,1,0.5,1,1,1,0,0,0,1,1,0,0,0,0.5,0.5,0,0,0,0.5,0,1,0,0,0,1,0,0,0,0,0.5,0,0,1,1,1,0,0,0,0,1,0,0,0,1,0,0.5,1,0] recall 0.275 [0,0,0,1,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0.5,1,1,0.5,0,1,0.5,1,0,0,0.5,0.5,1,0,0,0,1,0,0.5,0,1,1,0,1,0,0,0,0,0,1,1,0,1,0.5,1,0.5,1,0,1,1,0,1,0.5,0,0,0,1,0,0,0,1,0,1,0,0,0.5,0,0.5,0,1,0,0.5,0,1,0,0.5,0,1,0,1,0,0,0,1,0,0,0,0] recall 0.23125 [0,0,0,0,1,0,1,0,1,0.5,0,0,0,0,1,0,0.5,0.5,1,0,0.5,0,0.5,0,0,0.5,0,1,0,0,1,0,0,0.5,1,1,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0.5,1,0,0.5,0,0,0,0,1,0,0,0,0.5,0,1,0,0,0,0.5,0,0,1,1,0.5,0.5,0.5,1,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0] recall 0.2625 [0,1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,0,0.5,1,0,0,0,0,0,0,0.5,0,0,1,1,1,1,0,0.5,1,0.5,0,0,0,0,0,0,0,1,0,0,0,0,0,0.5,1,1,0,1,0,0,1,0,0,1,0.5,0.5,1,1,0,0,1,0,0,0,0.5,0,1,0,0,1,0.5,0,0,0,1,0,0,0.5,0,1,1,1,0,0.5,1,0,1,1,0,1,0,0,0,0] recall 0.275 [0,0,1,0,1,0,0,0,0,0,0,1,0.5,1,1,0,1,1,0,0,0,0,0.5,0,0,0,1,0,0,0.5,0,0,1,1,0,1,0,0,0.5,0,0,0,0.5,1,0,0,0,0,1,1,0,0,0.5,0,0,1,0,0,0,1,0.5,0,1,0,0,0,1,0,0,0,1,0,0.5,1,0,0,1,1,0,0,0,0,0.5,1,1,0,0,0,0,1,1,0,0,1,1,0,0,1,0,0] recall 0.30625 [0,1,1,0,1,0,0,0,1,0.5,0,1,0.5,1,1,0,1,1,0,0,0,0,0,0,0.5,0,1,0,0,0.5,1,1,1,1,0,1,1,0.5,0,1,0,0,0.5,0,1,0,0,0,1,0,0,0,0,1,0,0.5,0,0.5,0.5,0,0.5,0.5,1,0,0,0,0,0,0,0,1,0,1,1,0,1,1,0,1,1,0,0,0,0.5,0,0,0,0,1,0,1,0,0,1,1,0,0,0,0.5,0] recall 0.275 [1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,1,1,0,0,0,0.5,0,0,0,0,0,1,0.5,0.5,1,1,0,0,1,0,1,0.5,0,0,0,0,0,0.5,0.5,0,0.5,0,0,1,1,0,0,0,0,0,0,0,0,0.5,0,0,0.5,0.5,0,1,1,0,1,0,1,1,0,0,0,0,0,1,1,0,0,0,1,1,1,0.5,0.5,0,0,1,0,0.5,0,0.5,0,0,0,1,0.5,0,1] recall 0.1875 [1,0,0,0,0,1,0,0,0,0,1,1,0.5,0,0,0,1,0,0,0,0,0,0,0,0.5,1,0,0,0,0,0.5,0,1,1,0,0.5,0,0.5,0,0,0,0,0.5,1,0,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0.5,0.5,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0.5,0,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,1] relative_absolute_error 0.7323232323232315 relative_absolute_error 0.7575757575757568 relative_absolute_error 0.7386363636363629 relative_absolute_error 0.7323232323232315 relative_absolute_error 0.7765151515151507 relative_absolute_error 0.7449494949494943 relative_absolute_error 0.7323232323232315 relative_absolute_error 0.700757575757575 relative_absolute_error 0.7323232323232315 relative_absolute_error 0.8207070707070698 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 0.12041594578792299 root_mean_squared_error 0.12247448713915894 root_mean_squared_error 0.12093386622447828 root_mean_squared_error 0.12041594578792299 root_mean_squared_error 0.12399596767637248 root_mean_squared_error 0.12144957801491123 root_mean_squared_error 0.12041594578792299 root_mean_squared_error 0.1177921898938975 root_mean_squared_error 0.12041594578792299 root_mean_squared_error 0.12747548783981966 root_relative_squared_error 1.2102257907706577 root_relative_squared_error 1.230914909793327 root_relative_squared_error 1.215431087010994 root_relative_squared_error 1.2102257907706577 root_relative_squared_error 1.246206364544132 root_relative_squared_error 1.2206141855225954 root_relative_squared_error 1.2102257907706577 root_relative_squared_error 1.1838560518556092 root_relative_squared_error 1.2102257907706577 root_relative_squared_error 1.2811768579763452 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 755.9901780000473 usercpu_time_millis 781.0241049996876 usercpu_time_millis 759.1164890000073 usercpu_time_millis 767.3240390001865 usercpu_time_millis 757.5608660001762 usercpu_time_millis 733.2190049999099 usercpu_time_millis 761.4960490000158 usercpu_time_millis 738.8752270001078 usercpu_time_millis 741.2427440001466 usercpu_time_millis 766.5057770000203 usercpu_time_millis_testing 53.03024600016215 usercpu_time_millis_testing 54.644212999846786 usercpu_time_millis_testing 54.14012300002469 usercpu_time_millis_testing 55.22279299998445 usercpu_time_millis_testing 53.65292400006183 usercpu_time_millis_testing 51.41062699999566 usercpu_time_millis_testing 58.35140199997113 usercpu_time_millis_testing 52.29110100003709 usercpu_time_millis_testing 56.25451100013379 usercpu_time_millis_testing 57.151742000087324 usercpu_time_millis_training 702.9599319998852 usercpu_time_millis_training 726.3798919998408 usercpu_time_millis_training 704.9763659999826 usercpu_time_millis_training 712.1012460002021 usercpu_time_millis_training 703.9079420001144 usercpu_time_millis_training 681.8083779999142 usercpu_time_millis_training 703.1446470000446 usercpu_time_millis_training 686.5841260000707 usercpu_time_millis_training 684.9882330000128 usercpu_time_millis_training 709.354034999933