8802955 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) 6778036 axis 0 7660 categorical_features [] 7660 copy true 7660 fill_empty 0 7660 missing_values "NaN" 7660 strategy "mean" 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 3019.783311634322 7708 cache_size 200 7708 class_weight null 7708 coef0 -0.1652226628397302 7708 decision_function_shape null 7708 degree 2 7708 gamma 0.052618247267007 7708 kernel "poly" 7708 max_iter -1 7708 probability true 7708 random_state 13487 7708 shrinking false 7708 tol 0.05794386554168139 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 18521915 description https://api.openml.org/data/download/18521915/description.xml -1 18521916 predictions https://api.openml.org/data/download/18521916/predictions.arff area_under_roc_curve 0.9964599116161612 [0.988479,1,1,0.999961,0.998343,0.994989,0.999803,0.999645,0.99779,0.999961,0.998816,0.999566,0.999645,0.973761,0.999408,0.999566,1,0.990964,0.983862,0.974708,0.998264,0.999527,0.996607,0.999329,0.998698,0.976957,0.992227,0.99929,0.99854,1,0.999724,1,1,0.990136,0.99925,0.998895,0.993213,0.983941,0.999684,0.999842,0.999014,0.998658,1,0.998777,0.996883,0.999921,0.99925,0.999329,0.997435,0.996725,0.9942,0.999014,0.998027,0.991872,0.996883,0.993963,1,0.999448,0.992858,0.996725,0.998698,0.999448,0.997633,0.99925,0.999369,0.994239,0.986111,0.999921,0.998264,0.993608,0.996883,0.999408,0.996291,0.998343,0.989386,0.999487,0.999448,0.990885,0.999961,1,0.995818,0.997593,0.998106,0.995502,0.999369,0.999921,0.999961,0.999211,0.999329,1,0.99925,0.999605,0.998816,0.997711,0.996646,0.997711,0.998343,0.99854,0.967764,0.99779] average_cost 0 f_measure 0.8308628869769268 [0.705882,0.967742,0.967742,0.967742,0.933333,0.827586,1,0.903226,0.875,0.933333,0.882353,0.875,0.9375,0.714286,0.967742,0.933333,1,0.645161,0.424242,0.266667,0.8,0.967742,0.764706,1,0.909091,0.388889,0.516129,0.848485,0.933333,0.967742,0.967742,0.967742,0.967742,0.516129,0.848485,0.875,0.5625,0.516129,0.941176,0.896552,0.777778,0.909091,1,0.848485,0.9375,0.941176,0.857143,0.909091,0.764706,0.83871,0.787879,0.785714,0.8125,0.705882,0.774194,0.545455,1,0.9375,0.702703,0.742857,0.896552,0.848485,0.774194,0.9375,0.909091,0.615385,0.529412,0.969697,0.83871,0.705882,0.823529,0.933333,0.709677,0.967742,0.756757,0.9375,0.903226,0.685714,1,1,0.774194,0.875,0.866667,0.533333,0.875,0.967742,0.967742,0.903226,0.933333,0.967742,0.8125,0.866667,0.875,0.875,0.9375,0.8,0.8,0.848485,0.5,0.903226] kappa 0.827020202020202 kb_relative_information_score 991.0624149126379 mean_absolute_error 0.015935068880324615 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 0.8382305024192392 [0.666667,1,1,1,1,0.923077,1,0.933333,0.875,1,0.833333,0.875,0.9375,0.833333,1,1,1,0.666667,0.411765,0.285714,0.857143,1,0.722222,1,0.882353,0.35,0.533333,0.823529,1,1,1,1,1,0.533333,0.823529,0.875,0.5625,0.533333,0.888889,1,0.7,0.882353,1,0.823529,0.9375,0.888889,1,0.882353,0.722222,0.866667,0.764706,0.916667,0.8125,0.666667,0.8,0.529412,1,0.9375,0.619048,0.684211,1,0.823529,0.8,0.9375,0.882353,0.521739,0.5,0.941176,0.866667,0.666667,0.777778,1,0.733333,1,0.666667,0.9375,0.933333,0.631579,1,1,0.8,0.875,0.928571,0.571429,0.875,1,1,0.933333,1,1,0.8125,0.928571,0.875,0.875,0.9375,0.736842,0.736842,0.823529,0.5,0.933333] predictive_accuracy 0.82875 prior_entropy 6.6438561897747395 recall 0.82875 [0.75,0.9375,0.9375,0.9375,0.875,0.75,1,0.875,0.875,0.875,0.9375,0.875,0.9375,0.625,0.9375,0.875,1,0.625,0.4375,0.25,0.75,0.9375,0.8125,1,0.9375,0.4375,0.5,0.875,0.875,0.9375,0.9375,0.9375,0.9375,0.5,0.875,0.875,0.5625,0.5,1,0.8125,0.875,0.9375,1,0.875,0.9375,1,0.75,0.9375,0.8125,0.8125,0.8125,0.6875,0.8125,0.75,0.75,0.5625,1,0.9375,0.8125,0.8125,0.8125,0.875,0.75,0.9375,0.9375,0.75,0.5625,1,0.8125,0.75,0.875,0.875,0.6875,0.9375,0.875,0.9375,0.875,0.75,1,1,0.75,0.875,0.8125,0.5,0.875,0.9375,0.9375,0.875,0.875,0.9375,0.8125,0.8125,0.875,0.875,0.9375,0.875,0.875,0.875,0.5,0.875] relative_absolute_error 0.8048014586022518 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08202253718892395 root_relative_squared_error 0.8243575157837353 total_cost 0 area_under_roc_curve 0.9963657352121646 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.987342,1,0.981132,1,0.990506,0.984177,0.987421,1,1,1,1,1,0.996835,0.993671,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993711,1,1,0.993711,0.993711,1,1,1,1,1,1,1,0.981013,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,0.962264,0.996835,1,1,1,1,1,1,0.955696,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,0.981132,0.996835,0.943038,1] area_under_roc_curve 0.9964040482445664 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.892405,1,1,1,0.984177,0.996835,0.987421,1,0.993711,0.993711,1,1,0.977848,0.971519,1,1,1,1,1,1,0.996835,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,0.987421,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.981013,0.996835,1,0.987421,0.996835,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,1,0.974843] area_under_roc_curve 0.9970745263115992 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.936709,1,1,0.993671,1,1,0.939873,1,1,1,1,1,1,1,0.984177,1,1,1,1,1,1,0.993671,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.981132,0.981013,1,1,1,0.993711,1,0.993671,1,1,1,0.987342,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1] area_under_roc_curve 0.9972364859485708 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.943396,0.974684,1,1,0.996835,1,0.993711,1,1,1,1,1,1,1,1,0.987342,1,1,1,0.962264,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,0.984177,1,1,0.993711,1,1,1,1,1,1,0.996835,0.996835,1,1,0.977848,0.984177,1,0.981132,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1] area_under_roc_curve 0.9962498009712603 [1,1,1,1,1,0.996835,1,1,1,1,0.990506,1,1,0.918239,1,1,1,0.990506,0.987421,0.990506,1,1,1,1,1,0.993671,0.993671,1,1,1,1,1,1,0.977848,1,1,0.993671,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.949367,1,0.993671,1,1,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1,1,1,1,0.971519,0.993711,1,1,0.930818,1] area_under_roc_curve 0.9964013115993946 [0.924051,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,1,0.955696,1,1,1,1,0.993671,0.987342,0.987342,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,0.981013,1,1,0.996835,1,1,0.993711,1,1,1,1,0.990506,0.996835,1,1,1,1,1,0.993671,1,1,0.993671,1,0.996835,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1] area_under_roc_curve 0.9954984674787036 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.996835,0.977848,0.996835,1,0.990506,1,1,0.886792,0.974843,0.993671,1,1,0.996835,1,1,1,1,1,0.974684,0.993671,1,1,1,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.996835,1,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.870253,1] area_under_roc_curve 0.9971215468513653 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,0.990506,1,0.996835,1,1,1,0.993671,0.993711,1,1,0.974843,1,1,1,1,1,1,1,0.981013,0.987342,1,1,1,1,1,1,1,1,1,0.993671,1,0.987421,0.949686,1,0.996835,1,1,0.987342,1,1,0.987342,1,1,1,1,1,1,0.974843,0.924528,1,1,0.996835,1,1,1,1,1,1,1,0.968553,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835] area_under_roc_curve 0.997156874452671 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.987421,0.990506,0.974843,0.996835,1,0.981132,0.993671,1,0.987421,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.952532,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.990506,1,1,0.968354,0.990506,0.993711,1,1,0.996835,1,0.996835,1,1,1,1,1,0.987342,1,1,1,1,0.993711,0.984177,1,1,1,1,0.993711,1,1,1,0.993711,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1] area_under_roc_curve 0.9977487361675028 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.974684,0.987421,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,0.993671,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.981013,1,1,1,0.993671,1,0.993711,0.993711,0.981013,1,1,1,1,1,0.990506,0.990506,1,0.990506,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1,1,0.993711,1,1,1] 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 0.8041924914136829 kappa 0.8104415133085854 kappa 0.8799747315224258 kappa 0.8294445102451735 kappa 0.8294040990403981 kappa 0.8167963043392427 kappa 0.8041615667074664 kappa 0.8230647709320694 kappa 0.8546890424481737 kappa 0.8168469250809189 kb_relative_information_score 99.50202625488626 kb_relative_information_score 97.64557858315702 kb_relative_information_score 98.95037302853531 kb_relative_information_score 98.13553921848037 kb_relative_information_score 98.7029710567152 kb_relative_information_score 98.35833134678577 kb_relative_information_score 102.08301426396366 kb_relative_information_score 98.76309865605027 kb_relative_information_score 99.70598000645357 kb_relative_information_score 99.21550249761218 mean_absolute_error 0.015811771294932064 mean_absolute_error 0.016133921059792847 mean_absolute_error 0.01604050487404044 mean_absolute_error 0.016108232685283677 mean_absolute_error 0.016074738434251237 mean_absolute_error 0.015976428230886113 mean_absolute_error 0.015522369697436565 mean_absolute_error 0.016001665541914935 mean_absolute_error 0.015828814180214847 mean_absolute_error 0.015852242804493242 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 0.8125 predictive_accuracy 0.88125 predictive_accuracy 0.83125 predictive_accuracy 0.83125 predictive_accuracy 0.81875 predictive_accuracy 0.80625 predictive_accuracy 0.825 predictive_accuracy 0.85625 predictive_accuracy 0.81875 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 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.8125 [1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,0] recall 0.88125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1] recall 0.83125 [0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1] recall 0.83125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0.5,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1] recall 0.81875 [0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.80625 [1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,0.5,1,1,0,0,0.5,1,1,0.5,0,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5] recall 0.85625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1] recall 0.81875 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.7985743078248504 relative_absolute_error 0.8148444979693343 relative_absolute_error 0.8101265087899199 relative_absolute_error 0.8135471053173561 relative_absolute_error 0.8118554764773339 relative_absolute_error 0.8068903146912164 relative_absolute_error 0.7839580655270979 relative_absolute_error 0.8081649263593388 relative_absolute_error 0.799435059606809 relative_absolute_error 0.8006183234592532 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 0.0815739624779738 root_mean_squared_error 0.08278870001997765 root_mean_squared_error 0.08224210754067088 root_mean_squared_error 0.08273175235331741 root_mean_squared_error 0.0824743392641087 root_mean_squared_error 0.08237585615305026 root_mean_squared_error 0.08019371289967235 root_mean_squared_error 0.08214783044696346 root_mean_squared_error 0.08166994741677569 root_mean_squared_error 0.08199574685744497 root_relative_squared_error 0.8198491703089966 root_relative_squared_error 0.8320577419622858 root_relative_squared_error 0.8265642808498898 root_relative_squared_error 0.8314853963774425 root_relative_squared_error 0.8288982974894681 root_relative_squared_error 0.827908504981687 root_relative_squared_error 0.8059771401021115 root_relative_squared_error 0.8256167604070028 root_relative_squared_error 0.8208138552409093 root_relative_squared_error 0.8240882628215386 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 1352.8822900000002 usercpu_time_millis 1184.9075080000002 usercpu_time_millis 1220.9892 usercpu_time_millis 1187.0360069999997 usercpu_time_millis 1184.2086080000006 usercpu_time_millis 1187.002196 usercpu_time_millis 1179.4310950000017 usercpu_time_millis 1170.707032000001 usercpu_time_millis 1187.738492000001 usercpu_time_millis 1166.5155980000018 usercpu_time_millis_testing 139.0018660000001 usercpu_time_millis_testing 137.9063700000005 usercpu_time_millis_testing 148.20443699999953 usercpu_time_millis_testing 142.80118199999947 usercpu_time_millis_testing 139.5386710000004 usercpu_time_millis_testing 136.78012199999932 usercpu_time_millis_testing 139.89520700000037 usercpu_time_millis_testing 139.41233400000107 usercpu_time_millis_testing 141.356033000001 usercpu_time_millis_testing 138.39433600000106 usercpu_time_millis_training 1213.8804240000002 usercpu_time_millis_training 1047.0011379999996 usercpu_time_millis_training 1072.7847630000006 usercpu_time_millis_training 1044.2348250000002 usercpu_time_millis_training 1044.6699370000001 usercpu_time_millis_training 1050.2220740000005 usercpu_time_millis_training 1039.5358880000015 usercpu_time_millis_training 1031.294698 usercpu_time_millis_training 1046.3824590000002 usercpu_time_millis_training 1028.1212620000008