8840313 1 Jan van Rijn 9956 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) 6815363 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 1.2042258822932679 7708 cache_size 200 7708 class_weight null 7708 coef0 -0.2988054219348222 7708 decision_function_shape null 7708 degree 4 7708 gamma 0.07571286384067279 7708 kernel "rbf" 7708 max_iter -1 7708 probability true 7708 random_state 42135 7708 shrinking true 7708 tol 0.0017223817756778597 7708 verbose false 7708 openml-pimp openml-python Sklearn_0.18.1. study_71 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 18596300 description https://api.openml.org/data/download/18596300/description.xml -1 18596301 predictions https://api.openml.org/data/download/18596301/predictions.arff area_under_roc_curve 0.986785846432165 [0.992677,0.998658,0.998934,0.986734,0.947331,0.992814,0.967743,0.969007,0.999013,0.998697,0.999013,0.972165,0.999684,0.999961,0.990524,0.999882,0.989893,0.983733,0.982707,0.986418,0.999842,0.94133,0.981167,0.99392,0.947923,0.984681,0.920602,0.935052,0.999368,0.998737,0.989932,0.999921,0.936434,0.999842,0.985471,0.994354,0.998776,0.999724,0.997789,0.996289,1,0.947213,0.993328,0.983023,0.987326,0.999368,0.946936,0.999684,0.973981,0.997671,0.997236,0.997118,0.997907,0.994907,0.992775,0.945633,0.999961,0.994354,0.999882,0.997631,1,0.999447,0.994394,0.996447,0.999408,0.993051,0.999803,0.991985,0.999566,0.996131,0.998618,0.978719,0.999763,0.945396,0.998618,0.99925,0.996762,0.946265,0.998421,0.996841,0.999882,0.991748,0.958307,0.99771,0.947213,0.999684,0.975008,0.99925,0.999645,0.999763,0.9497,0.980693,0.997789,0.999566,0.973981,0.993801,0.998065,0.986418,0.999842,0.999329] average_cost 0 f_measure 0.804060767374762 [0.866667,0.896552,0.903226,0.360656,0.714286,0.8,0.8,0.5625,0.896552,0.9375,0.875,0.333333,0.866667,0.896552,0.8,0.967742,0.705882,0.875,0.896552,0.375,0.903226,0.536585,0.933333,0.967742,0.409091,0.848485,0.857143,0.529412,0.933333,0.9375,0.933333,0.933333,0.709677,0.866667,0.857143,0.6,0.875,0.903226,0.827586,0.827586,0.933333,0.666667,0.705882,0.606061,0.551724,0.896552,0.540541,0.903226,0.827586,0.785714,0.774194,0.857143,0.875,0.866667,0.787879,0.571429,0.967742,0.727273,0.933333,0.814815,0.896552,0.896552,0.56,0.8,0.903226,0.8,0.903226,0.8125,0.967742,0.866667,0.848485,0.451613,0.857143,0.896552,0.903226,0.933333,0.83871,0.933333,0.866667,0.866667,0.896552,0.529412,0.529412,0.903226,0.774194,0.933333,0.6,0.875,0.967742,0.875,0.866667,0.8125,0.83871,0.903226,0.848485,0.827586,0.848485,0.903226,0.896552,0.866667] kappa 0.7845875052148519 kb_relative_information_score 893.894484462557 mean_absolute_error 0.016045072004553036 mean_prior_absolute_error 0.019799992711748222 number_of_instances 1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] precision 0.8394431308226693 [0.866667,1,0.933333,0.244444,0.833333,0.857143,0.857143,0.5625,1,0.9375,0.875,0.357143,0.928571,1,0.857143,1,0.666667,0.875,1,0.234375,0.933333,0.44,1,1,0.321429,0.823529,1,0.5,1,0.9375,1,1,0.733333,0.928571,1,0.5,0.875,0.933333,0.923077,0.923077,1,0.647059,0.666667,0.588235,0.615385,1,0.47619,0.933333,0.923077,0.916667,0.8,1,0.875,0.928571,0.764706,0.666667,1,0.705882,1,1,1,1,0.411765,0.857143,0.933333,0.857143,0.933333,0.8125,1,0.928571,0.823529,0.466667,1,1,0.933333,1,0.866667,1,0.928571,0.928571,1,0.5,0.5,0.933333,0.8,1,0.642857,0.875,1,0.875,0.928571,0.8125,0.866667,0.933333,0.823529,0.923077,0.823529,0.933333,1,0.928571] predictive_accuracy 0.7867417135709819 prior_entropy 6.6438309601245775 recall 0.7867417135709819 [0.866667,0.8125,0.875,0.6875,0.625,0.75,0.75,0.5625,0.8125,0.9375,0.875,0.3125,0.8125,0.8125,0.75,0.9375,0.75,0.875,0.8125,0.9375,0.875,0.6875,0.875,0.9375,0.5625,0.875,0.75,0.5625,0.875,0.9375,0.875,0.875,0.6875,0.8125,0.75,0.75,0.875,0.875,0.75,0.75,0.875,0.6875,0.75,0.625,0.5,0.8125,0.625,0.875,0.75,0.6875,0.75,0.75,0.875,0.8125,0.8125,0.5,0.9375,0.75,0.875,0.6875,0.8125,0.8125,0.875,0.75,0.875,0.75,0.875,0.8125,0.9375,0.8125,0.875,0.4375,0.75,0.8125,0.875,0.875,0.8125,0.875,0.8125,0.8125,0.8125,0.5625,0.5625,0.875,0.75,0.875,0.5625,0.875,0.9375,0.875,0.8125,0.8125,0.8125,0.875,0.875,0.75,0.875,0.875,0.8125,0.8125] relative_absolute_error 0.81035747023446 root_mean_prior_squared_error 0.09949872432040595 root_mean_squared_error 0.08258946124898091 root_relative_squared_error 0.8300554787318296 total_cost 0 area_under_roc_curve 0.9934743451954462 [1,1,1,1,1,0.996835,0.943038,1,1,1,1,0.990506,1,1,0.987342,1,0.993671,1,1,0.996835,1,0.810127,1,0.974684,0.974684,1,1,1,1,0.993711,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.927215,1,0.993671,0.996835,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,1,0.996835,0.996835,1,1,1,0.987342,0.996835,1,1,0.971519,0.996835,1,1,0.984177,0.981013,0.993711,1,1,1] area_under_roc_curve 0.992190858609983 [1,0.993711,1,1,0.987342,0.984177,1,0.924528,0.996835,0.996835,1,0.962025,1,1,0.996835,1,0.981013,1,1,0.990506,1,0.939873,1,1,0.936709,0.987342,0.874214,0.996835,1,0.996835,1,1,1,1,1,0.987342,1,1,0.996835,0.996835,1,0.993711,0.962264,0.993671,1,1,0.974684,1,1,1,1,1,0.993711,1,0.993711,0.996835,1,1,1,1,1,1,1,0.987421,1,0.993671,1,0.943396,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,0.754717,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.990506,1,1,1,1] area_under_roc_curve 0.9971556305230476 [1,1,1,0.993671,1,1,1,1,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,0.96519,1,1,0.993711,1,1,0.996835,1,1,1,1,1,1,1,0.993711,1,1,1,0.981132,1,1,1,0.996835,0.974684,1,0.987342,1,0.996835,1,1,0.996835,0.996835,1,0.987421,1,1,0.993711,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.977848,1,1,1,0.996835,1,1,1,0.993671,1,0.981013,1,1,0.987421,1,0.981013,1,1,1,1,0.996835,1,1,0.993671,1,1,1,1,1] area_under_roc_curve 0.9955721081124113 [1,1,0.996835,0.996835,1,1,0.993671,0.952532,1,1,1,0.993711,1,1,0.990506,1,0.990506,1,0.981013,1,1,0.955696,1,1,0.987421,1,1,0.939873,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993711,0.981132,0.990506,0.990506,1,1,1,1,1,1,1,0.990506,0.984177,0.981013,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.990506,0.987342,1,1,1,1,0.987342,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.993711,1,1,1,1,0.987421] area_under_roc_curve 0.9961281446540882 [1,1,1,1,1,1,1,0.96519,1,1,1,0.987421,1,1,0.930818,1,0.977848,1,0.990506,1,1,0.993711,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.990506,0.993671,0.984177,1,0.993671,1,1,1,0.987342,1,1,1,0.987342,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.996835,1,0.996835,0.987421,1,1,1,0.911392,1,1,1,1,1,1,0.993711,1,1,1,1,1,1] area_under_roc_curve 0.9964533078576544 [1,1,1,0.974843,0.968553,1,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,1,0.805031,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.993671,1,1,1,1,1,0.993671,0.981132,1,1,0.993671,1,1,0.990506,1,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.993711,0.984177,1,0.955696,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.996835,1] area_under_roc_curve 0.9931287815460552 [1,1,1,1,1,0.977848,0.987421,0.981013,1,1,0.993671,0.952532,1,1,1,1,1,1,1,1,1,0.987421,0.981132,1,0.987342,1,1,0.899371,1,1,1,1,0.977848,1,0.958861,1,1,0.996835,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.990506,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,0.860759,1,1,1,1,1,1,1,0.974843,0.962025,1,1,1,1,1,1,1,1,0.874214,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9877853574556166 [0.924528,1,0.993671,1,0.993711,0.990506,1,1,1,1,1,0.996835,1,1,1,1,0.993711,0.936709,1,0.889241,1,1,1,1,0.822785,1,0.927215,0.993711,1,1,1,1,0.708861,1,1,0.993671,0.996835,0.996835,1,1,1,0.987342,0.996835,0.987421,1,1,0.993711,1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,0.990506,1,1,0.993711,0.993711,1,1,1,1,0.993711,0.974684,0.990506,0.990506,1,1,0.993671,1,0.981013,1,0.924528,1,1,1,1,1,0.996835,1,1,0.981013,1,1,1,1] area_under_roc_curve 0.9971195565639676 [1,1,1,0.993671,1,1,1,1,0.996835,1,1,0.996835,1,1,0.993671,1,1,1,1,1,1,0.971519,1,1,0.996835,1,1,1,1,1,1,0.996835,0.968553,1,0.987421,1,1,1,1,1,1,0.993671,0.996835,0.893082,0.993711,1,1,1,0.958861,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,0.993711,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,1] area_under_roc_curve 0.9936741820932957 [1,1,1,0.984076,0.761146,1,0.980892,1,1,0.993631,1,0.996815,1,1,1,1,0.993671,1,1,1,1,1,1,1,0.980892,1,1,0.993631,1,1,1,1,1,1,1,1,1,1,0.993631,1,1,0.93949,1,0.987342,1,1,0.936709,1,0.993631,1,0.996815,1,1,1,1,1,1,0.996815,1,1,1,1,1,1,1,0.996815,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993631,1,0.990446,1,1,1,1,1,1,1,0.993671,1,1,0.949045,1,1,1,1,1] 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 0.8104864181933038 kappa 0.7725747226280255 kappa 0.7347542924807579 kappa 0.7410287789664838 kappa 0.7852603323727944 kappa 0.8231206569804169 kappa 0.8041228970855383 kappa 0.753671245855045 kappa 0.8104265402843602 kappa 0.8092076316947322 kb_relative_information_score 93.95543741491046 kb_relative_information_score 86.42791673831712 kb_relative_information_score 88.15064481368145 kb_relative_information_score 84.6276818903979 kb_relative_information_score 90.30510262146616 kb_relative_information_score 94.31936460737025 kb_relative_information_score 89.62279804527205 kb_relative_information_score 84.192568343562 kb_relative_information_score 89.91242297278866 kb_relative_information_score 92.38054701479099 mean_absolute_error 0.015655397728398204 mean_absolute_error 0.01637627969935384 mean_absolute_error 0.01616267879326037 mean_absolute_error 0.016510509109563025 mean_absolute_error 0.015870589179556208 mean_absolute_error 0.01546643578492039 mean_absolute_error 0.016024712609975678 mean_absolute_error 0.016407863434654318 mean_absolute_error 0.01609747487556935 mean_absolute_error 0.01587773296125837 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.01980002942907592 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.019800029429075917 mean_prior_absolute_error 0.01980002942907591 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.01979995585638609 mean_prior_absolute_error 0.019799955856386102 mean_prior_absolute_error 0.01979995631910742 number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1] number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1] number_of_instances 160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1] number_of_instances 160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1] number_of_instances 160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2] number_of_instances 160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2] number_of_instances 159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2] predictive_accuracy 0.8125 predictive_accuracy 0.775 predictive_accuracy 0.7375 predictive_accuracy 0.74375 predictive_accuracy 0.7875 predictive_accuracy 0.825 predictive_accuracy 0.80625 predictive_accuracy 0.75625 predictive_accuracy 0.8125 predictive_accuracy 0.8113207547169812 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 prior_entropy 6.6438309601245775 recall 0.8125 [1,1,1,1,0.5,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,0,0,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0,0.5,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1] recall 0.775 [1,0,1,1,0.5,0,1,0,0.5,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0,0.5,0,1,0.5,1,1,1,1,1,1,0,1,1,0.5,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,1,0,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0,1,1,0] recall 0.7375 [1,1,1,0.5,1,1,0.5,1,1,1,1,0,1,0.5,1,1,1,1,0.5,1,0.5,0,1,1,1,0.5,1,0.5,1,1,1,0,1,0.5,1,1,1,1,1,0,0.5,1,1,0.5,0,0.5,1,0.5,0.5,0,1,0,0.5,1,1,0.5,1,0,0,1,0.5,1,1,1,1,0.5,0.5,0,0,1,1,0.5,1,1,0.5,0.5,1,1,1,0.5,1,0.5,1,1,0,0.5,0,1,0.5,1,1,1,1,1,1,1,1,1,1,1] recall 0.74375 [1,0,0.5,1,1,0,0.5,0,1,1,1,0,0.5,0.5,0.5,1,0.5,1,0.5,1,1,0.5,1,1,1,1,1,0,1,1,1,1,0.5,0.5,1,1,1,0.5,0,1,1,1,0,1,0.5,1,1,0.5,1,1,1,1,0.5,0.5,0.5,0,1,1,1,1,1,0,1,1,1,0,1,1,1,1,0.5,0,1,1,1,0.5,0.5,1,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0] recall 0.7875 [0.5,1,1,1,1,1,1,0,0,1,1,0,0,1,0,1,0,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,0.5,0.5,0.5,0.5,1,1,1,0,1,1,0,0.5,0,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,0.5,1] recall 0.825 [1,1,1,0,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,0,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,0,1,1,0,1,0.5,0.5,1,1,0.5,1,0.5,1] recall 0.80625 [1,1,1,0,0,0.5,1,0.5,1,1,0.5,0.5,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,1,1,0,1,1,1,1,1,0,1,1,1,0,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.75625 [0,1,0.5,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,0.5,0,1,1,1,0,1,0.5,0,0,1,1,1,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,0.5,0,0,1,0,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,0,1,1,1,1] recall 0.8125 [1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,0,1,0.5,1,1,1,1,0.5,0.5,0,1,1,1,1,0.5,0,1,0,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,0.5,0.5,1,1,1,1,0,1,0,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1] recall 0.8113207547169812 [1,0.5,1,0.5,0.5,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,0,0,1,0,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,1,1,0.5] relative_absolute_error 0.7906754777550273 relative_absolute_error 0.8270836039923063 relative_absolute_error 0.8162956954763827 relative_absolute_error 0.8338628570580657 relative_absolute_error 0.8015437167103698 relative_absolute_error 0.7811348619715226 relative_absolute_error 0.8093307240787214 relative_absolute_error 0.828681818972959 relative_absolute_error 0.8130055941704241 relative_absolute_error 0.8019074742066974 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949890883178135 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.09949853911503082 root_mean_prior_squared_error 0.0994985414402977 root_mean_squared_error 0.08076803026735173 root_mean_squared_error 0.08392492096508512 root_mean_squared_error 0.08324286948514131 root_mean_squared_error 0.08474274328926158 root_mean_squared_error 0.08186532801028534 root_mean_squared_error 0.08022914240661659 root_mean_squared_error 0.08230859384150782 root_mean_squared_error 0.08428398425616036 root_mean_squared_error 0.08269768865578117 root_mean_squared_error 0.08170470061325082 root_relative_squared_error 0.8117478997071501 root_relative_squared_error 0.8434757923523913 root_relative_squared_error 0.8366209284352712 root_relative_squared_error 0.8516952023316416 root_relative_squared_error 0.8227761386679288 root_relative_squared_error 0.8063348780816092 root_relative_squared_error 0.8272341943267167 root_relative_squared_error 0.8470876558169279 root_relative_squared_error 0.8311447523885142 root_relative_squared_error 0.8211648073482187 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 3185.515450000821 usercpu_time_millis 2944.6028439997463 usercpu_time_millis 3114.7359770002367 usercpu_time_millis 2940.0636200007284 usercpu_time_millis 2943.1089860008797 usercpu_time_millis 2953.1565590004902 usercpu_time_millis 2955.902421999781 usercpu_time_millis 2949.3383369990624 usercpu_time_millis 2932.0318490008503 usercpu_time_millis 2971.5897850001056 usercpu_time_millis_testing 149.04952899996715 usercpu_time_millis_testing 147.89844599908974 usercpu_time_millis_testing 157.1253109996178 usercpu_time_millis_testing 146.36559700011276 usercpu_time_millis_testing 147.08510200034652 usercpu_time_millis_testing 148.66423800049233 usercpu_time_millis_testing 160.29180100122176 usercpu_time_millis_testing 146.2222619993554 usercpu_time_millis_testing 145.25549199970555 usercpu_time_millis_testing 156.04171700033476 usercpu_time_millis_training 3036.465921000854 usercpu_time_millis_training 2796.7043980006565 usercpu_time_millis_training 2957.610666000619 usercpu_time_millis_training 2793.6980230006156 usercpu_time_millis_training 2796.023884000533 usercpu_time_millis_training 2804.492320999998 usercpu_time_millis_training 2795.610620998559 usercpu_time_millis_training 2803.116074999707 usercpu_time_millis_training 2786.776357001145 usercpu_time_millis_training 2815.548067999771