8701979 1 Jan van Rijn 9954 Supervised Classification 7707 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1) 6679398 axis 0 7660 categorical_features [] 7660 copy true 7660 fill_empty 0 7660 missing_values "NaN" 7660 strategy "median" 7660 strategy_nominal "most_frequent" 7660 verbose 0 7660 categorical_features [] 7661 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 7661 handle_unknown "ignore" 7661 n_values "auto" 7661 sparse true 7661 threshold 0.0 7662 copy true 7663 with_mean false 7663 with_std true 7663 C 4527.034977458508 7708 cache_size 200 7708 class_weight null 7708 coef0 -0.9935953968704252 7708 decision_function_shape null 7708 degree 1 7708 gamma 3.71214768222419e-05 7708 kernel "sigmoid" 7708 max_iter -1 7708 probability true 7708 random_state 21183 7708 shrinking true 7708 tol 1.861533522583847e-05 7708 verbose false 7708 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 18320859 description https://api.openml.org/data/download/18320859/description.xml -1 18320860 predictions https://api.openml.org/data/download/18320860/predictions.arff area_under_roc_curve 0.9966414141414144 [0.98765,0.999961,1,1,0.998146,0.995147,0.999842,0.999882,0.99779,0.999961,0.998935,0.999684,0.999842,0.980942,0.999724,0.999566,1,0.990767,0.986861,0.970604,0.99858,0.999487,0.996252,0.999803,0.998737,0.980035,0.98765,0.999487,0.998777,1,0.999842,1,1,0.991517,0.999684,0.999408,0.994831,0.985993,0.999882,0.999921,0.999092,0.999408,1,0.999053,0.997751,0.999921,0.999329,0.999014,0.997751,0.99637,0.995186,0.999053,0.998264,0.991319,0.996962,0.989899,1,0.999566,0.993884,0.995581,0.999014,0.99929,0.997554,0.999132,0.999369,0.995265,0.986703,1,0.998501,0.9942,0.996607,0.999527,0.995936,0.998619,0.988281,0.999448,0.999566,0.990372,1,1,0.995028,0.997869,0.998422,0.997277,0.999369,0.999842,0.999961,0.999566,0.999408,1,0.99854,0.999605,0.998777,0.998067,0.997514,0.998224,0.998185,0.998185,0.972064,0.998264] average_cost 0 f_measure 0.8289583523308767 [0.702703,0.9375,1,1,0.933333,0.827586,1,0.967742,0.875,0.933333,0.875,0.875,0.967742,0.625,0.967742,0.933333,1,0.4,0.451613,0.285714,0.83871,0.967742,0.769231,1,0.875,0.457143,0.5,0.848485,0.903226,0.933333,0.967742,1,0.969697,0.709677,0.875,0.875,0.628571,0.411765,0.914286,0.967742,0.777778,0.909091,1,0.875,0.9375,0.941176,0.857143,0.875,0.764706,0.8125,0.787879,0.827586,0.866667,0.685714,0.733333,0.625,1,0.9375,0.615385,0.727273,0.896552,0.903226,0.727273,0.9375,0.875,0.727273,0.5,1,0.83871,0.727273,0.774194,0.857143,0.666667,0.967742,0.736842,0.909091,0.9375,0.588235,1,1,0.75,0.866667,0.896552,0.533333,0.875,0.933333,0.933333,0.903226,0.967742,1,0.758621,0.740741,0.909091,0.903226,0.967742,0.823529,0.8,0.8,0.533333,0.903226] kappa 0.8244949494949495 kb_relative_information_score 991.9560905075335 mean_absolute_error 0.01604719109615556 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 0.8378592708722603 [0.619048,0.9375,1,1,1,0.923077,1,1,0.875,1,0.875,0.875,1,0.625,1,1,1,0.428571,0.466667,0.263158,0.866667,1,0.652174,1,0.875,0.421053,0.5,0.823529,0.933333,1,1,1,0.941176,0.733333,0.875,0.875,0.578947,0.388889,0.842105,1,0.7,0.882353,1,0.875,0.9375,0.888889,1,0.875,0.722222,0.8125,0.764706,0.923077,0.928571,0.631579,0.785714,0.625,1,0.9375,0.521739,0.705882,1,0.933333,0.705882,0.9375,0.875,0.705882,0.5,1,0.866667,0.705882,0.8,1,0.647059,1,0.636364,0.882353,0.9375,0.555556,1,1,0.75,0.928571,1,0.571429,0.875,1,1,0.933333,1,1,0.846154,0.909091,0.882353,0.933333,1,0.777778,0.736842,0.736842,0.571429,0.933333] predictive_accuracy 0.82625 prior_entropy 6.6438561897747395 recall 0.82625 [0.8125,0.9375,1,1,0.875,0.75,1,0.9375,0.875,0.875,0.875,0.875,0.9375,0.625,0.9375,0.875,1,0.375,0.4375,0.3125,0.8125,0.9375,0.9375,1,0.875,0.5,0.5,0.875,0.875,0.875,0.9375,1,1,0.6875,0.875,0.875,0.6875,0.4375,1,0.9375,0.875,0.9375,1,0.875,0.9375,1,0.75,0.875,0.8125,0.8125,0.8125,0.75,0.8125,0.75,0.6875,0.625,1,0.9375,0.75,0.75,0.8125,0.875,0.75,0.9375,0.875,0.75,0.5,1,0.8125,0.75,0.75,0.75,0.6875,0.9375,0.875,0.9375,0.9375,0.625,1,1,0.75,0.8125,0.8125,0.5,0.875,0.875,0.875,0.875,0.9375,1,0.6875,0.625,0.9375,0.875,0.9375,0.875,0.875,0.875,0.5,0.875] relative_absolute_error 0.8104641967755319 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08236385250624866 root_relative_squared_error 0.8277878637921205 total_cost 0 area_under_roc_curve 0.9962075073640634 [0.981132,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.981132,1,1,0.981013,0.974843,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,1,1,1,0.987421,1,1,1,1,0.996835,1,1,1,1,1,1,0.974684,1,1,0.962264,0.996835,1,1,1,1,1,1,0.962025,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,1,0.987342,1,0.993671,0.924051,1] area_under_roc_curve 0.9964819182389937 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.898734,1,1,1,0.971519,0.993671,0.993711,1,1,1,1,1,0.984177,0.971519,1,1,1,1,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.987342,1,1,0.981013,0.996835,1,0.987421,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835,1,0.974843] area_under_roc_curve 0.9969182887508957 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,1,0.933544,1,1,0.993671,1,1,0.96519,0.993671,1,1,1,1,1,1,0.984177,1,1,0.993711,1,1,1,0.996835,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.981132,0.984177,1,0.993711,1,0.987421,1,0.993671,1,1,1,0.984177,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.968553,1] area_under_roc_curve 0.9972352420189475 [1,1,1,1,0.996835,0.996835,1,1,0.996835,1,1,1,1,1,1,1,1,0.993671,0.949686,0.955696,1,1,0.996835,1,0.993711,0.993671,1,1,1,1,1,1,1,0.990506,1,1,1,0.981132,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.987342,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.984177,0.981013,1,0.981132,1,0.993711,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.996835,1,1,1] area_under_roc_curve 0.9968391748268448 [1,1,1,1,1,0.993671,1,1,1,1,0.993671,1,1,0.968553,1,1,1,0.996835,0.987421,0.990506,1,1,1,1,0.996835,0.996835,0.987342,1,1,1,1,1,1,0.981013,1,1,1,0.977848,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.993671,0.996835,1,0.996835,0.996835,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.939873,1,0.993671,1,1,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1,1,1,1,0.974684,0.993711,1,1,0.981132,1] area_under_roc_curve 0.9960863486187405 [0.914557,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.968354,1,1,0.996835,1,0.993671,0.987342,0.974684,1,1,1,1,1,1,0.996835,1,0.996835,0.996835,0.984177,1,1,0.996835,1,1,1,1,1,1,1,0.990506,0.996835,1,1,1,1,0.996835,0.990506,1,1,0.996835,1,0.996835,0.996835,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.993711,0.996835,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.949686,1] area_under_roc_curve 0.996367725499562 [0.996835,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,0.981013,1,1,0.984177,1,1,0.90566,0.962264,1,1,1,0.996835,1,1,1,1,1,0.977848,0.993671,1,1,1,1,1,1,0.981132,1,1,0.996835,1,1,1,1,1,1,0.993671,1,1,1,0.996835,1,1,1,1,0.996835,1,0.987421,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.968354,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.93038,1] area_under_roc_curve 0.9974380025475679 [0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.993671,0.996835,1,1,1,1,0.996835,0.987421,1,1,0.974843,1,1,1,1,1,1,1,0.990506,0.993671,1,1,0.996835,1,1,1,1,1,1,0.993671,1,0.981132,0.949686,1,0.996835,1,1,0.984177,1,1,0.996835,1,1,1,1,1,1,0.974843,0.937107,1,1,0.996835,1,1,1,1,1,1,1,0.974843,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.996835] area_under_roc_curve 0.9978285964493272 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.968553,1,1,0.987421,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.962025,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.990506,1,1,0.96519,0.996835,0.987421,1,1,1,1,1,1,1,1,1,1,0.990506,1,0.996835,1,1,0.993711,0.981013,1,1,1,1,0.993711,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9977492337393519 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.993711,0.971519,0.987421,0.996835,1,1,1,1,0.993711,0.993711,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.984177,1,1,1,0.993671,1,0.993711,0.993711,0.981013,1,1,1,1,1,0.993671,0.990506,1,0.993671,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.996835,1,1,0.993671,1,1,0.993671,1,1,0.993711,1,1,1] 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 0.8042002210642666 kappa 0.8357289527720739 kappa 0.8673195387774444 kappa 0.8041924914136829 kappa 0.816781836130306 kappa 0.7978681405448086 kappa 0.8230927183699257 kappa 0.8230717586193278 kappa 0.8610014215763703 kappa 0.8105462582886012 kb_relative_information_score 99.08627887593155 kb_relative_information_score 98.11772360862233 kb_relative_information_score 99.29579223228626 kb_relative_information_score 98.48123876168873 kb_relative_information_score 98.88331058928739 kb_relative_information_score 98.09360397515007 kb_relative_information_score 101.28338355795755 kb_relative_information_score 98.73202955919713 kb_relative_information_score 100.5443979925504 kb_relative_information_score 99.43833135486415 mean_absolute_error 0.015974382699601754 mean_absolute_error 0.01619140218661016 mean_absolute_error 0.016070778491462163 mean_absolute_error 0.016171482302059642 mean_absolute_error 0.016162402331315863 mean_absolute_error 0.016135095062707955 mean_absolute_error 0.015786191300774514 mean_absolute_error 0.01610473852137336 mean_absolute_error 0.015889334762181097 mean_absolute_error 0.015986103303469314 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 0.80625 predictive_accuracy 0.8375 predictive_accuracy 0.86875 predictive_accuracy 0.80625 predictive_accuracy 0.81875 predictive_accuracy 0.8 predictive_accuracy 0.825 predictive_accuracy 0.825 predictive_accuracy 0.8625 predictive_accuracy 0.8125 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 0.80625 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0,0.5,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0] recall 0.86875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1] recall 0.80625 [0.5,1,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0,1,1,0.5,0,0.5,0,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1] recall 0.81875 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,1,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0.5,0.5,1,1,0.5,1,1,1,0,1,0.5,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1] recall 0.8 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1] recall 0.825 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5] recall 0.8625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1] recall 0.8125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.8067870050303902 relative_absolute_error 0.8177475851823298 relative_absolute_error 0.8116554793667745 relative_absolute_error 0.8167415304070513 relative_absolute_error 0.8162829460260523 relative_absolute_error 0.814903791045855 relative_absolute_error 0.7972823889280045 relative_absolute_error 0.8133706323925927 relative_absolute_error 0.8024916546556097 relative_absolute_error 0.8073789547206711 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 0.08215710693843328 root_mean_squared_error 0.08292328151765775 root_mean_squared_error 0.0823646813702066 root_mean_squared_error 0.08288296843022996 root_mean_squared_error 0.08276106080527604 root_mean_squared_error 0.08294545181952424 root_mean_squared_error 0.08114186605538588 root_mean_squared_error 0.08252512425530006 root_mean_squared_error 0.08162997086828284 root_mean_squared_error 0.08228767889617207 root_relative_squared_error 0.825709992654204 root_relative_squared_error 0.8334103369063129 root_relative_squared_error 0.8277961941883352 root_relative_squared_error 0.8330051751331652 root_relative_squared_error 0.831779957402694 root_relative_squared_error 0.8336331568238283 root_relative_squared_error 0.815506437863606 root_relative_squared_error 0.8294087058554175 root_relative_squared_error 0.8204120758113206 root_relative_squared_error 0.8270222902056031 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 1885.99585799966 usercpu_time_millis 1682.90423200051 usercpu_time_millis 1695.6769790003818 usercpu_time_millis 1689.9952919993666 usercpu_time_millis 2156.827004999286 usercpu_time_millis 1726.3743560006333 usercpu_time_millis 1725.8494229999997 usercpu_time_millis 1709.2396539992478 usercpu_time_millis 1709.0661920001367 usercpu_time_millis 1683.5884259990053 usercpu_time_millis_testing 149.61012799994933 usercpu_time_millis_testing 155.4464150003696 usercpu_time_millis_testing 148.77296800023032 usercpu_time_millis_testing 149.18774599937024 usercpu_time_millis_testing 191.02034299976367 usercpu_time_millis_testing 148.14538700011326 usercpu_time_millis_testing 157.32700700027635 usercpu_time_millis_testing 148.55560099931608 usercpu_time_millis_testing 156.42353000021103 usercpu_time_millis_testing 148.77930299917352 usercpu_time_millis_training 1736.3857299997107 usercpu_time_millis_training 1527.4578170001405 usercpu_time_millis_training 1546.9040110001515 usercpu_time_millis_training 1540.8075459999964 usercpu_time_millis_training 1965.8066619995225 usercpu_time_millis_training 1578.22896900052 usercpu_time_millis_training 1568.5224159997233 usercpu_time_millis_training 1560.6840529999317 usercpu_time_millis_training 1552.6426619999256 usercpu_time_millis_training 1534.8091229998317