8805409 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) 6780490 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 60.849852722106306 7708 cache_size 200 7708 class_weight null 7708 coef0 -0.6280163651261268 7708 decision_function_shape null 7708 degree 2 7708 gamma 0.05419516065575978 7708 kernel "rbf" 7708 max_iter -1 7708 probability true 7708 random_state 3213 7708 shrinking true 7708 tol 0.011216976979368841 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 18526809 description https://api.openml.org/data/download/18526809/description.xml -1 18526810 predictions https://api.openml.org/data/download/18526810/predictions.arff area_under_roc_curve 0.9959655145202017 [0.992977,0.999724,1,0.998303,0.997554,0.990412,0.999921,0.999921,0.998067,0.987374,0.998935,0.999408,0.999527,0.950047,0.999448,0.998698,1,0.988123,0.987413,0.976681,0.997554,0.999842,0.995857,1,0.99929,0.980982,0.990136,0.999211,0.999369,0.999882,0.999724,0.993845,0.999921,0.990609,0.99858,0.999014,0.994476,0.985006,0.99925,0.999448,0.997948,0.998027,1,0.99858,0.999566,0.999448,0.998146,0.999171,0.998343,0.99854,0.996607,0.998027,0.997514,0.993608,0.995975,0.99203,1,0.999921,0.996133,0.993056,0.999408,0.999448,0.995068,0.999763,0.999605,0.994673,0.987176,1,0.997159,0.996843,0.996567,0.998816,0.995186,0.99929,0.977549,0.999961,0.999724,0.98548,1,0.999211,0.99349,0.996883,0.997396,0.996567,0.999527,0.999882,1,0.998816,0.998974,0.999803,0.999487,0.998974,0.998067,0.998935,0.999211,0.998619,0.995265,0.998185,0.973682,0.998698] average_cost 0 f_measure 0.8280520629202008 [0.83871,0.967742,0.933333,0.7,0.903226,0.628571,1,0.967742,0.740741,0.933333,0.9375,0.866667,0.933333,0.8125,0.666667,0.9375,1,0.5625,0.444444,0.342857,0.8125,0.933333,0.833333,0.967742,0.9375,0.4,0.484848,0.8,0.903226,0.967742,0.967742,0.967742,0.969697,0.588235,0.875,0.875,0.516129,0.451613,0.903226,0.9375,0.787879,0.909091,1,0.83871,0.909091,0.967742,0.848485,0.909091,0.787879,0.866667,0.733333,0.787879,0.827586,0.758621,0.823529,0.533333,0.967742,0.9375,0.705882,0.8,0.827586,0.933333,0.75,0.9375,0.909091,0.628571,0.482759,1,0.909091,0.8,0.75,0.875,0.705882,0.9375,0.764706,0.967742,0.903226,0.666667,0.967742,0.9375,0.857143,0.83871,0.866667,0.642857,0.83871,0.903226,1,0.83871,0.903226,0.967742,0.83871,0.903226,0.896552,0.903226,0.967742,0.903226,0.727273,0.882353,0.625,0.9375] kappa 0.8238636363636365 kb_relative_information_score 954.1779227924285 mean_absolute_error 0.01616910191304953 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 0.8367688750373972 [0.866667,1,1,0.583333,0.933333,0.578947,1,1,0.909091,1,0.9375,0.928571,1,0.8125,0.517241,0.9375,1,0.5625,0.4,0.315789,0.8125,1,0.75,1,0.9375,0.428571,0.470588,0.736842,0.933333,1,1,1,0.941176,0.555556,0.875,0.875,0.533333,0.466667,0.933333,0.9375,0.764706,0.882353,1,0.866667,0.882353,1,0.823529,0.882353,0.764706,0.928571,0.785714,0.764706,0.923077,0.846154,0.777778,0.571429,1,0.9375,0.666667,0.736842,0.923077,1,0.75,0.9375,0.882353,0.578947,0.538462,1,0.882353,0.736842,0.75,0.875,0.666667,0.9375,0.722222,1,0.933333,0.647059,1,0.9375,0.789474,0.866667,0.928571,0.75,0.866667,0.933333,1,0.866667,0.933333,1,0.866667,0.933333,1,0.933333,1,0.933333,0.705882,0.833333,0.625,0.9375] predictive_accuracy 0.825625 prior_entropy 6.6438561897747395 recall 0.825625 [0.8125,0.9375,0.875,0.875,0.875,0.6875,1,0.9375,0.625,0.875,0.9375,0.8125,0.875,0.8125,0.9375,0.9375,1,0.5625,0.5,0.375,0.8125,0.875,0.9375,0.9375,0.9375,0.375,0.5,0.875,0.875,0.9375,0.9375,0.9375,1,0.625,0.875,0.875,0.5,0.4375,0.875,0.9375,0.8125,0.9375,1,0.8125,0.9375,0.9375,0.875,0.9375,0.8125,0.8125,0.6875,0.8125,0.75,0.6875,0.875,0.5,0.9375,0.9375,0.75,0.875,0.75,0.875,0.75,0.9375,0.9375,0.6875,0.4375,1,0.9375,0.875,0.75,0.875,0.75,0.9375,0.8125,0.9375,0.875,0.6875,0.9375,0.9375,0.9375,0.8125,0.8125,0.5625,0.8125,0.875,1,0.8125,0.875,0.9375,0.8125,0.875,0.8125,0.875,0.9375,0.875,0.75,0.9375,0.625,0.9375] relative_absolute_error 0.8166213087398738 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08275325568367717 root_relative_squared_error 0.831701512979098 total_cost 0 area_under_roc_curve 0.9964433564206671 [0.974843,1,1,1,0.996835,0.993711,1,1,1,1,1,1,1,1,1,0.987421,1,0.984177,0.984177,1,1,1,1,1,0.993711,0.987342,0.996835,1,1,1,1,1,1,0.993671,0.996835,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.993711,0.993711,1,1,1,1,1,0.993711,0.996835,1,1,1,0.971519,1,1,0.993711,1,1,1,1,0.993711,1,1,0.936709,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.996835,1,0.990506,1,0.993671,0.946203,1] area_under_roc_curve 0.9945854231351007 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.778481,1,1,1,0.974684,0.993671,0.974843,1,1,1,1,1,0.993671,0.971519,1,1,1,1,1,1,1,1,0.993711,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.974843,1,1,1,0.993671,1,1,1,1,1,1,0.990506,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,0.955696,0.996835,0.987421,0.993711,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.987421,1,1,0.981132] area_under_roc_curve 0.9969158008916488 [1,1,1,1,1,0.981013,1,1,0.996835,1,1,1,1,1,1,1,1,0.977848,1,0.936709,1,1,0.990506,1,1,0.96519,1,1,1,1,1,1,1,0.993671,0.993711,1,1,0.993711,1,1,0.993671,1,1,1,1,1,0.984177,1,0.993671,1,1,1,1,1,1,1,1,1,0.987421,0.971519,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,0.993711,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1] area_under_roc_curve 0.9975924986067988 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.990506,0.968553,0.984177,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.990506,1,0.993711,1,0.962264,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.990506,1,1,1,1,1,1,1,1,1,0.996835,0.990506,1,1,0.990506,0.990506,1,0.993711,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,0.993671,0.949686,1] area_under_roc_curve 0.9965657590956132 [1,1,1,1,1,0.996835,1,0.996835,1,1,0.993671,1,1,0.90566,1,1,1,0.990506,0.987421,0.984177,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.981013,1,1,1,0.987342,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.981132,0.981132,1,1,0.977848,0.984177,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,0.993671,1,1,1,0.993711,0.955696,1,1,1,1,1,1,1,0.996835,0.993671,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.996835,1,0.987421,1] area_under_roc_curve 0.9975089065361036 [0.968354,1,1,1,1,0.990506,1,1,1,1,1,1,0.987421,1,1,1,1,0.996835,1,0.984177,1,1,0.996835,1,1,0.996835,0.984177,1,1,1,1,1,1,0.984177,1,1,1,0.990506,1,1,0.993671,1,1,1,1,1,1,1,1,0.996835,1,1,0.987342,1,1,0.996835,1,1,1,0.993711,0.996835,1,0.993711,1,1,0.977848,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993671,0.993671,0.993671,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9963279197516121 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.993671,0.990506,0.981013,1,1,1,1,0.899371,0.968553,1,1,1,0.996835,1,1,1,1,1,0.968354,0.984177,1,0.993711,0.996835,0.996835,1,1,1,0.996835,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,1,1,0.987421,0.993711,1,1,1,0.996835,1,1,1,1,1,0.911392,1] area_under_roc_curve 0.9975131358968234 [0.977848,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,1,1,0.993711,0.977848,0.984177,0.990506,1,1,1,1,1,1,1,0.993711,0.996835,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.996835,1,1,1,0.990506,1,1,0.993671,0.981132,1,1,1,1,1,0.974843,0.968553,1,1,0.993671,1,1,1,1,0.996835,1,1,0.974843,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9977892882732267 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.987421,1,0.962264,1,1,1,1,1,0.981132,0.993711,1,1,1,1,1,1,0.993711,0.996835,1,1,0.962025,1,1,1,1,1,0.993671,1,1,1,1,0.993711,1,0.996835,1,1,0.981013,1,0.987421,1,1,0.996835,1,1,1,1,1,1,1,0.981013,1,0.996835,1,1,0.987421,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9978290940211766 [1,1,1,1,1,0.993711,1,1,1,0.993711,1,1,1,0.977848,1,1,1,0.993711,0.987342,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.993711,1,1,0.984177,1,1,1,0.984177,1,0.987421,0.993711,0.990506,1,0.987342,1,0.987421,1,0.993671,1,1,1,1,1,1,1,1,0.981132,1,0.993711,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,1,1,1,1] 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 0.8041770302814956 kappa 0.8294377763739735 kappa 0.8546947800679143 kappa 0.835761380236093 kappa 0.8104564839677776 kappa 0.8104714522624971 kappa 0.8167673656359831 kappa 0.8230927183699257 kappa 0.8357289527720739 kappa 0.8168324648665719 kb_relative_information_score 94.47900583021577 kb_relative_information_score 95.0613757559406 kb_relative_information_score 95.70330250209004 kb_relative_information_score 96.08845506420317 kb_relative_information_score 95.15783892622076 kb_relative_information_score 93.85711705043533 kb_relative_information_score 97.321329166946 kb_relative_information_score 96.62861049216691 kb_relative_information_score 95.90636192577155 kb_relative_information_score 93.97452607843863 mean_absolute_error 0.01623070936577581 mean_absolute_error 0.016148748896868435 mean_absolute_error 0.016086926399699622 mean_absolute_error 0.016160971071113604 mean_absolute_error 0.016110633101369183 mean_absolute_error 0.016338429775721176 mean_absolute_error 0.015883783306600494 mean_absolute_error 0.01616392753135485 mean_absolute_error 0.01617252150439363 mean_absolute_error 0.01639436817759826 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 0.83125 predictive_accuracy 0.85625 predictive_accuracy 0.8375 predictive_accuracy 0.8125 predictive_accuracy 0.8125 predictive_accuracy 0.81875 predictive_accuracy 0.825 predictive_accuracy 0.8375 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 [1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,0,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1] recall 0.83125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,0,1,0.5,0] recall 0.85625 [1,1,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,0,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1] recall 0.8375 [0.5,1,0.5,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,1,0,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1] recall 0.8125 [1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0,1,1,1,0,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1] recall 0.8125 [0.5,1,1,0.5,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1] recall 0.81875 [1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0,1,1,0,1,0.5,1,1,0,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,0.5,1,1,0,1] recall 0.825 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,0.5,0.5,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.8375 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,0.5,1,1,1,1,0,1,0.5,1,0.5,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1] recall 0.81875 [1,1,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1] relative_absolute_error 0.819732796251302 relative_absolute_error 0.8155933786297176 relative_absolute_error 0.8124710302878583 relative_absolute_error 0.8162106601572513 relative_absolute_error 0.8136683384529877 relative_absolute_error 0.8251732209960178 relative_absolute_error 0.8022112781111348 relative_absolute_error 0.8163599763310517 relative_absolute_error 0.8167940153734142 relative_absolute_error 0.8279983928079915 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 0.08310490539091595 root_mean_squared_error 0.08266345627708173 root_mean_squared_error 0.08238787904055041 root_mean_squared_error 0.08274101464761259 root_mean_squared_error 0.082439125068401 root_mean_squared_error 0.08366711731522974 root_mean_squared_error 0.08144748170535443 root_mean_squared_error 0.0826400145899226 root_mean_squared_error 0.08271421950732563 root_mean_squared_error 0.08370424471256491 root_relative_squared_error 0.8352357255140963 root_relative_squared_error 0.8307989949849357 root_relative_squared_error 0.8280293395475496 root_relative_squared_error 0.8315784859376697 root_relative_squared_error 0.8285443815062662 root_relative_squared_error 0.8408861679553463 root_relative_squared_error 0.81857799071514 root_relative_squared_error 0.8305633971644517 root_relative_squared_error 0.831309184645134 root_relative_squared_error 0.8412593123383865 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 2917.3655120000603 usercpu_time_millis 2719.486181000093 usercpu_time_millis 2775.2773929998966 usercpu_time_millis 2732.8544560002683 usercpu_time_millis 2723.7836209999386 usercpu_time_millis 2871.991871999853 usercpu_time_millis 2743.1068159999086 usercpu_time_millis 2744.7597110001425 usercpu_time_millis 2733.072975000141 usercpu_time_millis 2788.3124799998313 usercpu_time_millis_testing 148.25410100002046 usercpu_time_millis_testing 148.0700940001043 usercpu_time_millis_testing 148.21897799993167 usercpu_time_millis_testing 148.12539100012145 usercpu_time_millis_testing 147.59436099984669 usercpu_time_millis_testing 146.93276999992122 usercpu_time_millis_testing 147.36382299997786 usercpu_time_millis_testing 147.9809770000884 usercpu_time_millis_testing 147.59312800015323 usercpu_time_millis_testing 156.78921499988974 usercpu_time_millis_training 2769.11141100004 usercpu_time_millis_training 2571.4160869999887 usercpu_time_millis_training 2627.058414999965 usercpu_time_millis_training 2584.729065000147 usercpu_time_millis_training 2576.189260000092 usercpu_time_millis_training 2725.059101999932 usercpu_time_millis_training 2595.7429929999307 usercpu_time_millis_training 2596.778734000054 usercpu_time_millis_training 2585.479846999988 usercpu_time_millis_training 2631.5232649999416