8703133 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) 6680552 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 7534.946171736372 7708 cache_size 200 7708 class_weight null 7708 coef0 -0.7977402015139905 7708 decision_function_shape null 7708 degree 4 7708 gamma 6.694931259883326e-05 7708 kernel "rbf" 7708 max_iter -1 7708 probability true 7708 random_state 35419 7708 shrinking false 7708 tol 0.00532286869278853 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 18323155 description https://api.openml.org/data/download/18323155/description.xml -1 18323156 predictions https://api.openml.org/data/download/18323156/predictions.arff area_under_roc_curve 0.9965593434343434 [0.989781,0.999961,1,1,0.998303,0.994673,0.999842,0.999921,0.997869,0.999961,0.998935,0.999605,0.999724,0.981376,0.999645,0.999645,1,0.990254,0.983665,0.973919,0.998264,0.999448,0.997238,0.999842,0.998343,0.974905,0.991832,0.999369,0.998777,1,0.999842,1,1,0.989702,0.999684,0.999171,0.993766,0.98327,0.999842,0.999961,0.999211,0.999448,1,0.999053,0.997751,0.999803,0.999487,0.999092,0.997475,0.996567,0.994594,0.99925,0.998382,0.990491,0.997159,0.993253,1,0.999566,0.992779,0.996528,0.999211,0.999369,0.997435,0.999369,0.999408,0.994949,0.988084,1,0.998461,0.994121,0.996094,0.999487,0.996725,0.998343,0.988715,0.999605,0.999566,0.990846,1,1,0.994989,0.99783,0.998027,0.995305,0.999211,0.999842,0.999961,0.999329,0.999605,1,0.999171,0.999527,0.998895,0.997751,0.997396,0.997909,0.997672,0.998422,0.966738,0.998343] average_cost 0 f_measure 0.8305549091831095 [0.764706,0.9375,1,1,0.933333,0.827586,1,0.967742,0.875,0.933333,0.909091,0.875,0.9375,0.740741,0.967742,0.933333,1,0.645161,0.368421,0.266667,0.774194,0.967742,0.787879,1,0.875,0.424242,0.545455,0.848485,0.933333,0.896552,0.967742,1,1,0.5,0.848485,0.875,0.516129,0.484848,0.914286,0.967742,0.777778,0.909091,1,0.875,0.9375,0.941176,0.857143,0.83871,0.764706,0.8125,0.75,0.827586,0.866667,0.727273,0.733333,0.5,1,0.9375,0.684211,0.742857,0.896552,0.848485,0.774194,0.9375,0.909091,0.684211,0.580645,1,0.866667,0.685714,0.823529,0.933333,0.625,0.967742,0.756757,0.909091,0.9375,0.647059,1,1,0.774194,0.875,0.875,0.482759,0.848485,0.967742,0.933333,0.875,0.967742,0.967742,0.8125,0.903226,0.875,0.903226,0.967742,0.777778,0.8,0.823529,0.482759,0.866667] kappa 0.827020202020202 kb_relative_information_score 990.4569244729369 mean_absolute_error 0.016059689472586246 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 0.8378992988435714 [0.722222,0.9375,1,1,1,0.923077,1,1,0.875,1,0.882353,0.875,0.9375,0.909091,1,1,1,0.666667,0.318182,0.285714,0.8,1,0.764706,1,0.875,0.411765,0.529412,0.823529,1,1,1,1,1,0.5,0.823529,0.875,0.533333,0.470588,0.842105,1,0.7,0.882353,1,0.875,0.9375,0.888889,1,0.866667,0.722222,0.8125,0.75,0.923077,0.928571,0.705882,0.785714,0.5,1,0.9375,0.590909,0.684211,1,0.823529,0.8,0.9375,0.882353,0.590909,0.6,1,0.928571,0.631579,0.777778,1,0.625,1,0.666667,0.882353,0.9375,0.611111,1,1,0.8,0.875,0.875,0.538462,0.823529,1,1,0.875,1,1,0.8125,0.933333,0.875,0.933333,1,0.7,0.736842,0.777778,0.538462,0.928571] predictive_accuracy 0.82875 prior_entropy 6.6438561897747395 recall 0.82875 [0.8125,0.9375,1,1,0.875,0.75,1,0.9375,0.875,0.875,0.9375,0.875,0.9375,0.625,0.9375,0.875,1,0.625,0.4375,0.25,0.75,0.9375,0.8125,1,0.875,0.4375,0.5625,0.875,0.875,0.8125,0.9375,1,1,0.5,0.875,0.875,0.5,0.5,1,0.9375,0.875,0.9375,1,0.875,0.9375,1,0.75,0.8125,0.8125,0.8125,0.75,0.75,0.8125,0.75,0.6875,0.5,1,0.9375,0.8125,0.8125,0.8125,0.875,0.75,0.9375,0.9375,0.8125,0.5625,1,0.8125,0.75,0.875,0.875,0.625,0.9375,0.875,0.9375,0.9375,0.6875,1,1,0.75,0.875,0.875,0.4375,0.875,0.9375,0.875,0.875,0.9375,0.9375,0.8125,0.875,0.875,0.875,0.9375,0.875,0.875,0.875,0.4375,0.8125] relative_absolute_error 0.8110954279083948 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08238646492355677 root_relative_squared_error 0.8280151271370113 total_cost 0 area_under_roc_curve 0.9966015842687682 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.993711,1,0.990506,0.981013,0.987421,0.993711,1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,0.990506,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.974684,1,1,0.968553,0.996835,1,1,1,1,1,1,0.955696,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.990506,0.987421,1,0.933544,1] area_under_roc_curve 0.996522221558793 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.905063,1,1,1,0.981013,0.993671,0.993711,1,1,0.993711,1,1,0.971519,0.971519,1,1,1,1,1,1,0.996835,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,0.993711,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.981013,0.996835,1,0.981132,0.996835,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835,1,0.974843] area_under_roc_curve 0.9968767415014727 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,1,0.936709,1,1,0.996835,1,1,0.933544,1,1,1,1,1,1,1,0.984177,1,1,0.993711,1,1,1,0.993671,0.987421,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.981132,0.984177,1,1,1,0.993711,1,0.990506,1,1,1,0.984177,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1] area_under_roc_curve 0.9966428827322664 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.987342,0.943396,0.958861,1,1,0.996835,1,0.993711,0.981013,1,1,1,1,1,1,1,0.990506,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.981013,1,1,0.993711,1,1,1,1,1,1,0.996835,0.993671,1,1,0.977848,0.974684,1,0.981132,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1] area_under_roc_curve 0.9965632712363665 [1,1,1,1,1,0.993671,1,1,1,1,0.993671,1,1,0.968553,1,1,1,0.990506,0.987421,0.987342,1,1,1,1,0.996835,0.993671,0.993671,1,1,1,1,1,1,0.977848,1,1,0.993671,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987421,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.943038,1,0.993671,1,1,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1,1,1,1,0.974684,0.993711,1,1,0.962264,1] area_under_roc_curve 0.9962828894992436 [0.924051,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,1,0.958861,1,1,1,1,0.993671,0.990506,0.990506,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,0.971519,1,1,0.996835,1,1,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,0.990506,1,1,0.993671,1,0.996835,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1] area_under_roc_curve 0.995695505931056 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.968354,1,1,0.990506,1,1,0.893082,0.974843,0.996835,1,1,0.996835,1,1,0.987421,1,1,0.974684,0.993671,1,1,1,1,1,1,0.981132,0.996835,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.996835,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.971519,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.886076,1] area_under_roc_curve 0.9977124134224982 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987342,1,0.996835,1,1,1,0.993671,0.993711,1,1,0.974843,1,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,0.993671,1,0.987421,0.968553,1,0.996835,1,1,0.984177,1,1,0.993671,1,1,1,1,1,1,0.974843,0.955975,1,1,0.996835,1,1,1,1,1,1,1,0.981132,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835] area_under_roc_curve 0.9974332756149986 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.987421,0.987342,0.968553,1,1,0.993711,1,1,0.987421,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.946203,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.990506,1,1,0.962025,0.996835,0.993711,1,1,1,1,1,1,1,1,1,1,0.987342,1,0.996835,1,1,0.993711,0.990506,1,1,1,1,0.993711,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9978278500915533 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.974684,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,0.993671,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,0.996835,1,1,1,0.984177,1,1,1,0.987342,1,0.993711,0.993711,0.993671,1,1,1,1,1,0.993671,0.990506,1,0.993671,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.990506,1,1,0.993711,0.993671,1,1] 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 0.8168180023687327 kappa 0.829397361977727 kappa 0.8799747315224258 kappa 0.8105163429654192 kappa 0.8104789355233545 kappa 0.810493900272415 kappa 0.8231206569804169 kappa 0.8230717586193278 kappa 0.867330016583748 kappa 0.7979080323662917 kb_relative_information_score 99.23163325094708 kb_relative_information_score 97.78060472329955 kb_relative_information_score 99.19989924245236 kb_relative_information_score 98.09876993290241 kb_relative_information_score 98.53271685930025 kb_relative_information_score 98.06650663049149 kb_relative_information_score 101.18654562168499 kb_relative_information_score 98.85194016475212 kb_relative_information_score 99.97356562157576 kb_relative_information_score 99.53474242552863 mean_absolute_error 0.01595449194044634 mean_absolute_error 0.016224921238366115 mean_absolute_error 0.016085702749693575 mean_absolute_error 0.0162031521775977 mean_absolute_error 0.01618029525333008 mean_absolute_error 0.01613717815809463 mean_absolute_error 0.015778633493217058 mean_absolute_error 0.016087651925587365 mean_absolute_error 0.01595453866472584 mean_absolute_error 0.01599032912480385 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 0.81875 predictive_accuracy 0.83125 predictive_accuracy 0.88125 predictive_accuracy 0.8125 predictive_accuracy 0.8125 predictive_accuracy 0.8125 predictive_accuracy 0.825 predictive_accuracy 0.825 predictive_accuracy 0.86875 predictive_accuracy 0.8 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 0.81875 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.83125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,0,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,0] recall 0.88125 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1] recall 0.8125 [0.5,1,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,0,1,0,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5] recall 0.8125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,0.5,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1] recall 0.8125 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.825 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5] recall 0.86875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1] recall 0.8 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.8057824212346623 relative_absolute_error 0.8194404665841458 relative_absolute_error 0.8124092297825025 relative_absolute_error 0.8183410190705895 relative_absolute_error 0.8171866289560633 relative_absolute_error 0.8150089978835657 relative_absolute_error 0.7969006814756077 relative_absolute_error 0.8125076730094615 relative_absolute_error 0.8057847810467584 relative_absolute_error 0.8075923800405971 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 0.08200606124643277 root_mean_squared_error 0.08306491980239945 root_mean_squared_error 0.0823812481226794 root_mean_squared_error 0.08302032250356708 root_mean_squared_error 0.0828518355231612 root_mean_squared_error 0.08285911355394533 root_mean_squared_error 0.08108329949836843 root_mean_squared_error 0.08242500822113438 root_mean_squared_error 0.08188217953293275 root_mean_squared_error 0.08226993947282879 root_relative_squared_error 0.8241919263312788 root_relative_squared_error 0.8348338552288516 root_relative_squared_error 0.827962696315447 root_relative_squared_error 0.834385635511002 root_relative_squared_error 0.8326922776441346 root_relative_squared_error 0.8327654246057214 root_relative_squared_error 0.8149178218184852 root_relative_squared_error 0.8284025018529144 root_relative_squared_error 0.8229468682644125 root_relative_squared_error 0.8268440022927941 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 1668.8545209999575 usercpu_time_millis 1451.081803001216 usercpu_time_millis 1452.2847709995403 usercpu_time_millis 1475.4322299995692 usercpu_time_millis 1455.9621730004437 usercpu_time_millis 1471.4262260004034 usercpu_time_millis 1471.2415379999584 usercpu_time_millis 1476.1985140012257 usercpu_time_millis 1468.6595450020832 usercpu_time_millis 1464.3790280006215 usercpu_time_millis_testing 146.67451599962078 usercpu_time_millis_testing 145.5810890001885 usercpu_time_millis_testing 145.8024719995592 usercpu_time_millis_testing 153.91620499940473 usercpu_time_millis_testing 145.98325800034218 usercpu_time_millis_testing 153.2208589997026 usercpu_time_millis_testing 145.565925999108 usercpu_time_millis_testing 153.80578500116826 usercpu_time_millis_testing 145.23772500069754 usercpu_time_millis_testing 145.53971299937984 usercpu_time_millis_training 1522.1800050003367 usercpu_time_millis_training 1305.5007140010275 usercpu_time_millis_training 1306.4822989999811 usercpu_time_millis_training 1321.5160250001645 usercpu_time_millis_training 1309.9789150001016 usercpu_time_millis_training 1318.2053670007008 usercpu_time_millis_training 1325.6756120008504 usercpu_time_millis_training 1322.3927290000574 usercpu_time_millis_training 1323.4218200013856 usercpu_time_millis_training 1318.8393150012416