7449833 1 Jan van Rijn 9954 Supervised Classification 6952 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1) 5481726 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "median" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse true 6948 threshold 0.0 6949 C 4171.964235872395 6953 cache_size 200 6953 class_weight null 6953 coef0 -0.8150374086354486 6953 decision_function_shape null 6953 degree 1 6953 gamma 0.001070499412032553 6953 kernel "poly" 6953 max_iter -1 6953 probability true 6953 random_state 36465 6953 shrinking true 6953 tol 0.00012825979815764589 6953 verbose false 6953 openml-pimp openml-python Sklearn_0.18.1. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 15826439 description https://api.openml.org/data/download/15826439/description.xml -1 15826440 predictions https://api.openml.org/data/download/15826440/predictions.arff area_under_roc_curve 0.9457015467171713 [0.793561,0.953164,0.958807,0.999566,0.98185,0.989504,0.986861,0.9506,0.983665,0.999566,0.972222,0.955177,0.897175,0.920218,0.938092,0.810724,0.983191,0.919429,0.9433,0.908657,0.943419,0.932726,0.95636,0.983704,0.983033,0.952652,0.875829,0.953204,0.958097,0.999921,0.933712,1,0.87066,0.984257,0.954309,0.997869,0.956716,0.938999,0.991753,0.999842,0.873185,0.966738,0.999803,0.954506,0.98694,0.777738,0.992148,0.9448,0.929569,0.967921,0.889047,0.965199,0.940735,0.846117,0.975694,0.955414,1,0.958452,0.962161,0.925979,0.985756,0.89824,0.987216,0.958491,0.989899,0.961963,0.889126,0.999487,0.936119,0.862729,0.94843,0.996962,0.967606,0.945589,0.905895,0.965515,0.990412,0.927675,0.994752,0.961924,0.953362,0.975616,0.955769,0.972143,0.875395,0.958846,0.998422,0.899661,0.958412,0.869555,0.914931,0.999487,0.98035,0.872909,0.937027,0.943458,0.857086,0.971433,0.83211,0.945865] average_cost 0 kappa 0.25631313131313127 kb_relative_information_score 431.43917624358124 mean_absolute_error 0.019128743676096484 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 0.26375 prior_entropy 6.6438561897747395 recall 0.26375 [0,0,0.4375,1,0.625,0.1875,0.125,0.375,0.25,0.8125,0.4375,0,0,0,0.0625,0.0625,0.9375,0.125,0.125,0,0.0625,0.0625,0.0625,0.6875,0.625,0.125,0,0.125,0.3125,0.9375,0.375,1,0,0.4375,0.0625,1,0,0,0.5625,1,0,0.25,1,0.0625,0.375,0,0.1875,0,0.1875,0.0625,0,0.25,0,0,0.0625,0,1,0.1875,0.375,0,0.4375,0.375,0.1875,0,0.75,0.125,0,1,0,0,0.1875,0.1875,0.375,0.1875,0,0.0625,0.8125,0,0.875,0.4375,0.0625,0.375,0,0.375,0,0.1875,1,0,0.0625,0,0,1,0.1875,0,0,0.125,0,0,0,0] relative_absolute_error 0.9660981654594167 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09674107031643983 root_relative_squared_error 0.972284339566724 total_cost 0 area_under_roc_curve 0.9536683484595174 [0.81761,0.949367,0.993671,1,1,1,0.990506,1,0.993671,1,0.962025,0.955696,0.892405,0.879747,0.962025,0.792453,0.946203,0.924051,0.889241,0.893082,0.90566,1,0.981132,0.987421,0.987421,0.943038,0.89557,0.996835,0.984177,1,0.962025,1,0.873418,0.974684,0.968354,0.987421,0.949686,0.90566,1,1,0.930818,0.974843,1,0.981013,1,0.708861,0.993711,0.937107,0.968354,0.943038,0.863924,0.990506,0.987421,0.867089,0.987421,0.993711,1,0.987421,0.974843,0.946203,0.987421,0.937107,0.993671,0.990506,1,0.971519,0.905063,1,0.993711,0.874214,0.939873,1,0.977848,0.952532,0.987421,0.987342,0.996835,0.914557,1,0.962025,0.993671,0.977848,0.987421,0.962264,0.911392,0.968354,0.996835,0.962025,0.968354,0.805031,0.933544,1,0.987342,0.879747,0.962025,0.981013,0.792453,0.958861,0.882911,0.962264] area_under_roc_curve 0.9525657292413022 [0.798742,0.96519,0.984177,1,1,1,0.996835,0.974843,0.990506,1,0.984177,0.971519,0.943038,0.781646,0.958861,0.836478,0.962025,0.952532,0.952532,0.861635,0.949686,0.974843,0.955975,1,1,0.943038,0.879747,0.96519,0.962025,1,0.958861,1,0.892405,0.990506,0.96519,0.987421,0.962264,0.90566,0.987421,1,0.886792,0.974843,1,0.971519,1,0.794304,1,0.937107,0.974684,0.977848,0.873418,0.974684,1,0.838608,0.993711,0.981132,1,0.987421,0.955975,0.927215,0.993711,0.899371,0.987342,0.974684,1,0.974684,0.876582,1,0.761006,0.943396,0.933544,1,0.974684,0.949367,0.962264,0.981013,0.996835,0.939873,1,1,0.968354,0.974684,0.981132,0.955975,0.860759,0.974684,1,0.968354,0.974684,0.899371,0.974684,1,0.987342,0.829114,0.968354,0.971519,0.836478,0.971519,0.791139,0.993711] area_under_roc_curve 0.9577835164397739 [0.835443,0.955696,0.993671,1,0.996835,0.993671,0.981132,0.93038,0.981013,1,0.981013,0.971519,0.937107,0.993671,0.939873,0.867089,1,0.882911,0.974843,0.952532,0.893082,0.955975,0.870253,0.981132,0.993711,0.958861,0.867089,0.981132,0.990506,1,0.955975,1,0.867089,0.987342,0.949686,1,0.955975,0.855346,0.993711,1,0.89557,0.974843,1,0.981132,0.987342,0.767296,1,0.930818,0.981013,0.987342,0.958861,0.993711,0.993711,0.952532,1,0.974684,1,0.993671,0.930818,0.952532,1,0.943396,0.993671,0.955975,0.993671,0.974684,0.879747,1,0.955975,0.908228,0.971519,0.990506,0.962264,0.962025,0.943396,0.990506,0.990506,0.990506,1,0.962025,0.962264,0.974684,0.974684,0.962025,0.798742,0.955975,1,0.968354,0.933544,0.842767,0.905063,1,0.993711,0.882911,0.939873,0.937107,0.905063,0.974684,1,0.977848] area_under_roc_curve 0.9555305111058032 [0.851266,0.952532,1,1,1,0.977848,0.993711,0.981013,0.977848,1,0.977848,0.962025,0.899371,0.927215,0.955696,0.860759,0.996835,0.917722,0.855346,0.93038,0.974843,0.993711,0.984177,1,0.987421,0.946203,0.800633,0.974843,0.981013,1,0.993711,1,0.892405,0.993671,0.962264,1,0.987421,0.893082,1,1,0.886076,1,1,0.974843,1,0.754717,0.996835,0.937107,0.974684,0.993671,0.968354,0.987421,0.949686,0.889241,0.993711,0.927215,1,0.993671,0.949686,0.905063,0.981132,0.962264,0.987342,0.974843,0.996835,0.974684,0.93038,1,0.993711,0.870253,0.962025,0.996835,0.968553,0.984177,0.893082,0.987342,0.993671,0.93038,1,0.955696,0.943396,0.96519,0.984177,0.977848,0.987421,0.968553,1,0.93038,0.984177,0.861635,0.870253,1,0.974843,0.870253,0.974684,0.924528,0.879747,0.977848,0.691824,0.962025] area_under_roc_curve 0.9558927434121485 [0.857595,0.974843,0.977848,1,1,0.996835,0.993711,0.949367,0.974843,1,0.962025,0.977848,0.918239,0.899371,0.949686,0.803797,0.993671,0.924051,0.924528,0.863924,0.914557,0.981013,1,1,0.974684,0.949367,0.841772,0.993711,1,1,1,1,0.813291,0.977848,0.968553,1,0.920886,0.927215,1,1,0.920886,0.993671,1,0.968553,1,0.735849,0.993671,0.96519,0.993671,0.984177,0.949686,0.987421,1,0.962264,0.990506,0.96519,1,0.971519,0.962025,0.949686,0.990506,0.873418,0.987421,0.993711,0.996835,0.974684,0.924528,1,0.981013,0.920886,0.962025,1,0.968553,0.968553,0.835443,0.968553,0.974684,0.958861,1,0.943396,0.962264,0.981013,0.962025,0.962025,0.867925,0.981132,0.987421,0.949686,0.987342,0.927215,0.836478,0.996835,0.987421,0.880503,0.974684,0.924528,0.920886,0.987421,0.761006,0.927215] area_under_roc_curve 0.9531155461348618 [0.794304,0.962264,0.981013,1,1,0.971519,0.993711,0.962025,1,0.996835,0.981013,0.958861,0.886792,0.968553,0.955975,0.800633,0.981013,0.879747,0.91195,0.848101,0.939873,0.96519,0.993671,1,0.946203,0.949367,0.806962,1,0.993711,1,0.993711,1,0.863924,0.990506,0.955975,0.996835,0.949367,0.911392,0.990506,1,0.886076,0.977848,1,0.968553,0.993711,0.861635,1,0.949367,0.987342,0.987342,0.937107,0.993711,0.971519,0.893082,0.96519,0.958861,1,0.996835,0.968354,0.955975,0.981013,0.879747,1,0.987421,1,0.981013,0.811321,1,0.987342,0.867089,0.936709,0.990506,0.962264,0.924528,0.952532,0.955975,0.990506,0.89557,1,0.930818,0.924528,0.987342,0.974684,0.955696,0.930818,0.949686,1,0.974843,0.974684,0.927215,0.981132,0.996835,0.968553,0.937107,0.962025,0.955975,0.844937,0.974843,0.842767,0.936709] area_under_roc_curve 0.9540649132234691 [0.765823,0.955975,1,1,1,1,0.990506,0.952532,0.987421,1,0.974843,0.968553,0.924051,0.993711,0.968553,0.768987,1,0.899371,0.962025,0.860759,0.968354,0.993671,0.987342,0.981013,0.996835,0.861635,0.981132,0.968354,1,1,0.920886,1,0.90566,0.968553,0.96519,1,0.952532,0.949367,0.996835,1,0.889241,0.993671,1,0.984177,0.962264,0.825949,0.990506,0.927215,0.968553,0.974843,0.949686,0.977848,0.943038,0.842767,0.977848,0.939873,1,0.993671,0.962025,0.981132,0.996835,0.860759,0.987421,0.993671,0.990506,0.955975,0.90566,0.993671,0.974684,0.908228,0.962264,1,0.981013,0.962264,0.943038,0.962264,1,0.842767,1,0.987421,0.924051,0.962264,0.968354,0.981013,0.917722,0.971519,1,0.949686,0.987421,0.85443,0.918239,1,0.990506,0.836478,0.918239,0.981013,0.844937,0.955975,0.857595,0.962025] area_under_roc_curve 0.9566420866173075 [0.851266,0.949686,0.993711,1,1,0.993671,0.990506,0.968354,0.981132,1,0.962264,0.981132,0.917722,0.993711,0.949686,0.822785,1,0.861635,0.93038,0.920886,0.955696,0.984177,0.958861,0.987342,1,0.949686,0.90566,0.987342,0.899371,1,0.917722,1,0.893082,0.987421,0.971519,1,0.939873,0.917722,0.996835,1,0.870253,0.987342,1,0.971519,0.993711,0.825949,0.993671,0.955696,0.974843,0.962264,0.773585,0.968354,0.962025,0.842767,0.993671,0.955696,1,0.984177,0.962025,0.924528,0.993671,0.857595,0.987421,0.990506,0.996835,0.937107,0.842767,1,0.968354,0.968354,0.962264,1,0.990506,0.949686,0.927215,0.974843,1,1,1,0.962264,0.968354,0.981132,0.974684,0.974684,0.93038,0.974684,1,0.937107,0.981132,0.879747,0.955975,1,0.990506,0.930818,0.937107,0.952532,0.89557,0.968553,0.85443,0.955696] area_under_roc_curve 0.9560790840697393 [0.943396,0.946203,0.993711,1,1,0.987421,0.990506,0.993711,0.987342,1,0.974843,0.981132,0.936709,0.949367,0.946203,0.823899,1,0.918239,0.949367,0.886792,0.949367,0.981013,0.987421,0.990506,0.981013,0.962264,0.880503,0.984177,0.990506,1,0.971519,1,0.899371,0.987421,0.990506,1,0.943038,0.974684,0.996835,1,0.90566,0.990506,1,0.96519,0.990506,0.696203,1,0.962025,0.981132,0.974843,0.911392,0.981013,0.971519,0.825949,0.987342,0.893082,1,0.968553,0.981013,0.981013,0.993671,0.901899,0.996835,0.977848,0.993711,0.974843,0.851266,1,0.981013,0.861635,0.974843,0.987421,0.911392,0.952532,0.939873,0.958861,1,0.955975,0.993711,0.952532,0.974684,0.962264,0.962264,0.981132,0.939873,0.974684,1,0.892405,0.949686,0.860759,0.93038,0.996835,0.990506,0.882911,0.924528,0.924051,0.874214,0.981013,0.857595,0.981132] area_under_roc_curve 0.9555678289945064 [0.893082,0.933544,0.993711,1,1,1,0.990506,0.993711,0.981013,1,0.968553,0.981132,0.914557,0.968354,0.949367,0.773585,1,0.993711,0.924051,0.90566,0.920886,0.96519,1,0.984177,0.990506,0.955975,0.893082,0.984177,0.987342,1,1,1,0.849057,0.987421,0.96519,0.993671,0.955696,0.955696,1,1,0.886792,0.984177,1,0.987342,0.987342,0.825949,1,0.955696,0.968553,0.968553,0.949367,0.987342,0.949367,0.876582,0.993671,0.949686,1,0.987421,0.971519,0.908228,0.993671,0.917722,0.981013,0.977848,0.981132,0.974843,0.876582,1,1,0.880503,0.918239,1,0.987342,0.971519,0.886076,0.96519,1,0.949686,1,0.977848,0.987342,0.981132,0.924528,0.993711,0.892405,0.984177,0.996835,0.876582,0.974843,0.857595,0.876582,1,1,0.860759,0.968553,0.955696,0.792453,0.962025,0.797468,0.955975] 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 0.23710446467273516 kappa 0.2560778596477403 kappa 0.2622078587474875 kappa 0.256107171000788 kappa 0.24302160542501183 kappa 0.26842727631060315 kappa 0.26854260266414437 kappa 0.28101225905632854 kappa 0.26246946655109915 kappa 0.23710446467273516 kb_relative_information_score 42.74297940943447 kb_relative_information_score 42.4958569888955 kb_relative_information_score 43.472346239178435 kb_relative_information_score 43.20640523531138 kb_relative_information_score 43.5481760295377 kb_relative_information_score 43.347918651994036 kb_relative_information_score 43.951094100548524 kb_relative_information_score 43.657978148354566 kb_relative_information_score 42.49863953238876 kb_relative_information_score 42.51778190793809 mean_absolute_error 0.019099061636947783 mean_absolute_error 0.01913988182771717 mean_absolute_error 0.019099333347110288 mean_absolute_error 0.019127798980508842 mean_absolute_error 0.019163663299894787 mean_absolute_error 0.01913343635002555 mean_absolute_error 0.01908724685594671 mean_absolute_error 0.019127242733514377 mean_absolute_error 0.01916846319934621 mean_absolute_error 0.01914130852995302 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 0.24375 predictive_accuracy 0.2625 predictive_accuracy 0.26875 predictive_accuracy 0.2625 predictive_accuracy 0.25 predictive_accuracy 0.275 predictive_accuracy 0.275 predictive_accuracy 0.2875 predictive_accuracy 0.26875 predictive_accuracy 0.24375 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 0.24375 [0,0,0.5,1,0,0,0,1,0,1,0.5,0,0,0,0,1,1,0,0.5,0,0,0,0,1,0,0,0,0,0,1,0.5,1,0,0.5,0,1,0,0,1,1,0,1,1,0,0.5,0,0,0,0,0,0,0,0,0,1,0,1,1,0,0,1,0,0,0,1,0,0,1,0,0,0,0,0.5,0,0,0,0.5,0,1,0.5,0,0.5,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.2625 [0,0,0,1,0.5,0,0,1,0,1,1,0,0,0,0,0,1,0,0,0,0,1,0,1,1,0.5,0,0,0.5,1,0,1,0,0,0,1,0,0,1,1,0,1,1,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,1,1,0.5,0,1,0,0,1,0,0,0.5,0,0.5,0,0,0,1,0,0.5,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.26875 [0,0,0.5,1,0.5,0.5,1,0.5,0,1,0,0,0,0,0,0,1,0.5,0,0,0,0,0,1,0,0.5,0,1,0,1,0,1,0,0.5,0,1,0,0,1,1,0,1,1,0,0,0,0,0,0,0.5,0,1,0,0,0,0,1,0,1,0,0,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0.5,0,1,1,0,0,0,0,1,0,0,0,1,0,0,0,0] recall 0.2625 [0,0,0,1,0.5,0,1,0.5,0,0.5,0,0,0,0,0,0,0.5,0.5,0,0,0,0,0,1,0,0,0,1,0,1,1,1,0,0,1,1,0,0,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,1,0,0,0,1,0,0,1,0,0,0.5,0,0,0,0,0,1,0,1,0.5,1,0,0,0.5,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0] recall 0.25 [0,0,0,1,1,0,0,0,1,0.5,0.5,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,0,1,0,0,0.5,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0.5,0,0,0.5,0,0,1,0,0,0,0,0,0,0,0,1,0,0.5,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.275 [0,0,0.5,1,1,0,0,0,1,0.5,0.5,0,0,0,0,0,1,0,0,0,0.5,0,0,0,1,0,0,0,1,0.5,1,1,0,0.5,0,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0.5,0,0,0,0,0,1,0,0,0,0.5,0,1,0,1,0.5,0,1,1,0,0,0,0.5,0,1,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.275 [0,0,1,1,1,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0.5,0,0,0,0,1,1,0,1,0,1,0,1,0,0,0.5,1,0,0,1,0,1,0,0.5,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0.5,0,0,1,0,0,1,0,0,1,1,0.5,1,0,0,1,0,1,1,0,0,0,1,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0] recall 0.2875 [0,0,1,1,1,0,0,0,1,1,1,0,0,0,1,0,1,0,0.5,0,0,0,0,0.5,0.5,0,0,0,1,1,0.5,1,0,0,0,1,0,0,0.5,1,0,0,1,0,1,0,0,0,1,0,0,0.5,0,0,0,0,1,0,1,0,0,0.5,0,0,0.5,0,0,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0.5,0,0,1,0,1,0,0,1,0,0,0,0,0,0,0,0] recall 0.26875 [0,0,1,1,0.5,1,0,1,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0.5,1,0,0,0,0,1,0.5,1,0,1,0,1,0,0,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,1,1,0,0,0.5,0,1,0,1,1,0,1,0,0,0,0,0,0,0,0,1,0,1,0.5,0,1,0,0,0,0,1,0,0,0,0,1,0.5,0,0,0,0,0,0,0] recall 0.24375 [0,0,1,1,1,1,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,0,0,0,1,0,1,0,0,0,1,0,0,0,1,0,0,1,0,0.5,0,1,0,0,0,0,0,0,0,0,0,1,1,0.5,0,0.5,0,0,0,1,1,0,1,0,0,0,0,0.5,0,0,0,1,0,1,0,0,0,0,0,0,0,1,0,0,0,0,1,0.5,0,0,0,0,0,0,0] relative_absolute_error 0.9645990725731187 relative_absolute_error 0.9666606983695525 relative_absolute_error 0.9646127953085988 relative_absolute_error 0.9660504535610511 relative_absolute_error 0.9678617828229674 relative_absolute_error 0.9663351691932079 relative_absolute_error 0.9640023664619535 relative_absolute_error 0.9660223602785024 relative_absolute_error 0.9681042019871807 relative_absolute_error 0.9667327540380297 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 0.09666184944566406 root_mean_squared_error 0.09676182093588194 root_mean_squared_error 0.09661913620609729 root_mean_squared_error 0.09674514785431897 root_mean_squared_error 0.0968730914481951 root_mean_squared_error 0.0968002278393317 root_mean_squared_error 0.09656417522025137 root_mean_squared_error 0.09668817007670591 root_mean_squared_error 0.09688373224990725 root_mean_squared_error 0.09681282413066565 root_relative_squared_error 0.9714881398578501 root_relative_squared_error 0.972492891139018 root_relative_squared_error 0.971058855648082 root_relative_squared_error 0.972325320364341 root_relative_squared_error 0.973611201864998 root_relative_squared_error 0.9728788950423584 root_relative_squared_error 0.9705064769566912 root_relative_squared_error 0.9717526721530356 root_relative_squared_error 0.9737181459460519 root_relative_squared_error 0.9730054925335847 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 2047.2571459999997 usercpu_time_millis 1861.0418509999995 usercpu_time_millis 1866.4174409999994 usercpu_time_millis 1875.9406059999985 usercpu_time_millis 1875.7948499999984 usercpu_time_millis 1884.406870000003 usercpu_time_millis 1873.930950000002 usercpu_time_millis 1868.387245000001 usercpu_time_millis 1876.5130840000027 usercpu_time_millis 1878.0663570000015 usercpu_time_millis_testing 151.31527499999999 usercpu_time_millis_testing 145.52840099999997 usercpu_time_millis_testing 146.5025329999996 usercpu_time_millis_testing 145.22402899999776 usercpu_time_millis_testing 146.21023099999775 usercpu_time_millis_testing 147.49187500000005 usercpu_time_millis_testing 147.844340999999 usercpu_time_millis_testing 145.75469200000057 usercpu_time_millis_testing 143.5852329999996 usercpu_time_millis_testing 145.48404599999998 usercpu_time_millis_training 1895.9418709999998 usercpu_time_millis_training 1715.5134499999995 usercpu_time_millis_training 1719.9149079999997 usercpu_time_millis_training 1730.7165770000008 usercpu_time_millis_training 1729.5846190000007 usercpu_time_millis_training 1736.9149950000028 usercpu_time_millis_training 1726.086609000003 usercpu_time_millis_training 1722.6325530000004 usercpu_time_millis_training 1732.927851000003 usercpu_time_millis_training 1732.5823110000015