8814279 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) 6789329 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 20481.038842503924 7708 cache_size 200 7708 class_weight null 7708 coef0 -0.3408960988676617 7708 decision_function_shape null 7708 degree 5 7708 gamma 0.01822101335315657 7708 kernel "rbf" 7708 max_iter -1 7708 probability true 7708 random_state 18241 7708 shrinking false 7708 tol 2.62294297866565e-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 18544478 description https://api.openml.org/data/download/18544478/description.xml -1 18544479 predictions https://api.openml.org/data/download/18544479/predictions.arff area_under_roc_curve 0.996863557449495 [0.991872,0.999882,1,0.999014,0.998027,0.995107,1,0.999921,0.999092,0.999724,0.999132,0.999487,0.999842,0.96658,1,0.99925,1,0.991004,0.987255,0.975694,0.998343,1,0.997711,1,0.999527,0.979877,0.99199,0.999408,0.999092,0.999961,0.999882,0.999605,1,0.990333,0.999448,0.99929,0.994555,0.98402,0.999684,0.999921,0.998895,0.999487,1,0.999092,0.999605,0.999961,0.998698,0.999369,0.998185,0.998698,0.996528,0.998856,0.998658,0.993056,0.99783,0.994279,1,0.999882,0.995068,0.997238,0.999645,0.999605,0.996567,0.999605,0.999763,0.995541,0.987571,1,0.998698,0.995699,0.996883,0.999605,0.996528,0.99929,0.983428,0.999842,0.999921,0.989938,1,0.999803,0.995818,0.998224,0.998461,0.996686,0.999566,0.999921,1,0.99925,0.999487,1,0.999684,0.999566,0.998935,0.999171,0.99854,0.999211,0.998658,0.998382,0.972814,0.999132] average_cost 0 f_measure 0.8461614030193089 [0.742857,0.967742,1,0.967742,0.933333,0.848485,1,1,0.866667,0.933333,0.909091,0.903226,0.9375,0.8125,0.914286,0.933333,1,0.6,0.4,0.193548,0.727273,0.967742,0.857143,1,0.9375,0.424242,0.545455,0.848485,0.933333,0.967742,0.967742,0.967742,1,0.580645,0.875,0.875,0.516129,0.625,0.9375,1,0.8,0.909091,1,0.848485,0.9375,0.9375,0.9375,0.909091,0.8,0.8125,0.8125,0.866667,0.903226,0.758621,0.733333,0.580645,1,0.9375,0.666667,0.727273,0.896552,0.933333,0.774194,0.875,0.909091,0.702703,0.551724,1,0.903226,0.742857,0.787879,0.9375,0.764706,0.967742,0.8,0.9375,0.9375,0.685714,0.967742,0.969697,0.848485,0.848485,0.903226,0.571429,0.875,0.967742,0.967742,0.875,0.903226,0.967742,0.83871,0.903226,0.903226,0.9375,0.967742,0.903226,0.823529,0.787879,0.545455,0.9375] kappa 0.8434343434343434 kb_relative_information_score 953.3023229363815 mean_absolute_error 0.016574375527005854 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 0.8509766001542318 [0.684211,1,1,1,1,0.823529,1,1,0.928571,1,0.882353,0.933333,0.9375,0.8125,0.842105,1,1,0.642857,0.368421,0.2,0.705882,1,0.789474,1,0.9375,0.411765,0.529412,0.823529,1,1,1,1,1,0.6,0.875,0.875,0.533333,0.625,0.9375,1,0.736842,0.882353,1,0.823529,0.9375,0.9375,0.9375,0.882353,0.736842,0.8125,0.8125,0.928571,0.933333,0.846154,0.785714,0.6,1,0.9375,0.6,0.705882,1,1,0.8,0.875,0.882353,0.619048,0.615385,1,0.933333,0.684211,0.764706,0.9375,0.722222,1,0.736842,0.9375,0.9375,0.631579,1,0.941176,0.823529,0.823529,0.933333,0.666667,0.875,1,1,0.875,0.933333,1,0.866667,0.933333,0.933333,0.9375,1,0.933333,0.777778,0.764706,0.529412,0.9375] predictive_accuracy 0.845 prior_entropy 6.6438561897747395 recall 0.845 [0.8125,0.9375,1,0.9375,0.875,0.875,1,1,0.8125,0.875,0.9375,0.875,0.9375,0.8125,1,0.875,1,0.5625,0.4375,0.1875,0.75,0.9375,0.9375,1,0.9375,0.4375,0.5625,0.875,0.875,0.9375,0.9375,0.9375,1,0.5625,0.875,0.875,0.5,0.625,0.9375,1,0.875,0.9375,1,0.875,0.9375,0.9375,0.9375,0.9375,0.875,0.8125,0.8125,0.8125,0.875,0.6875,0.6875,0.5625,1,0.9375,0.75,0.75,0.8125,0.875,0.75,0.875,0.9375,0.8125,0.5,1,0.875,0.8125,0.8125,0.9375,0.8125,0.9375,0.875,0.9375,0.9375,0.75,0.9375,1,0.875,0.875,0.875,0.5,0.875,0.9375,0.9375,0.875,0.875,0.9375,0.8125,0.875,0.875,0.9375,0.9375,0.875,0.875,0.8125,0.5625,0.9375] relative_absolute_error 0.8370896730811022 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08429589221791786 root_relative_squared_error 0.8472055935002212 total_cost 0 area_under_roc_curve 0.9969175423931216 [0.981132,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.993671,0.981013,0.993711,1,1,1,1,1,0.996835,0.993671,1,1,1,1,1,1,0.993671,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,0.968553,0.996835,1,1,1,1,1,1,0.949367,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.990506,1,0.993671,0.936709,1] area_under_roc_curve 0.9962841334288672 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.851266,1,1,1,0.974684,0.993671,0.981132,1,1,1,1,1,0.987342,0.974684,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,0.987421,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974684,0.996835,1,0.993711,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.981132] area_under_roc_curve 0.9971526450919512 [1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,0.936709,1,1,0.993671,1,1,0.949367,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.990506,1,0.996835,1,1,1,1,1,1,1,1,1,0.987421,0.981013,1,1,1,0.993711,1,0.996835,1,1,1,0.990506,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1] area_under_roc_curve 0.9977099255632516 [1,1,1,1,1,0.996835,1,1,0.993671,1,1,1,1,1,1,1,1,0.990506,0.962264,0.977848,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.968553,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.987342,1,1,1,1,1,1,1,1,1,0.996835,0.990506,1,1,0.987342,0.987342,1,0.987421,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.981132,1] area_under_roc_curve 0.9968016081522169 [1,1,1,1,1,0.996835,1,1,1,1,0.993671,1,1,0.91195,1,1,1,0.993671,0.987421,0.987342,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.981013,1,1,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987421,1,1,0.984177,0.984177,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,0.996835,1,1,1,1,0.943038,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.981013,1,1,1,0.987421,1] area_under_roc_curve 0.9973897380781782 [0.949367,1,1,0.996835,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,1,1,0.996835,0.996835,0.981013,1,1,1,1,1,1,0.993671,1,1,1,0.981013,1,1,0.996835,1,1,1,1,1,1,1,0.996835,0.996835,1,1,0.996835,1,1,0.996835,1,1,1,1,0.996835,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.996835,1,1,0.996835,1,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1] area_under_roc_curve 0.9963667303558633 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,0.981013,0.993671,1,1,1,1,0.899371,0.962264,0.996835,1,1,0.996835,1,1,1,1,1,0.971519,0.993671,1,0.993711,1,0.996835,1,1,1,0.996835,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.996835,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.901899,1] area_under_roc_curve 0.9979487600509511 [0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.987342,0.990506,0.993671,1,1,1,1,0.993711,1,1,0.993711,0.996835,1,1,1,1,1,1,0.987342,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,0.981132,1,1,1,1,0.990506,1,1,0.993671,0.987421,1,1,1,1,1,0.981132,0.955975,1,1,0.993671,1,1,1,1,1,1,1,0.968553,1,1,0.996835,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.997789039487302 [1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.993671,0.955975,1,1,1,1,1,0.987421,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.949367,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,0.974684,0.996835,0.993711,1,1,0.996835,1,1,1,1,1,1,1,0.987342,1,0.996835,1,1,0.993711,0.990506,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9981045000398054 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.977848,1,1,1,1,0.977848,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.987342,1,1,1,0.984177,1,0.993711,0.993711,0.987342,1,0.996835,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.968553,1,0.993711,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1] 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 0.8231346229767075 kappa 0.8483591991470205 kappa 0.8673404927353128 kappa 0.8610288601997711 kappa 0.842047069973148 kappa 0.848365187174222 kappa 0.8357354392892399 kappa 0.8294040990403981 kappa 0.8673352548663482 kappa 0.8105387803433984 kb_relative_information_score 95.15870122602348 kb_relative_information_score 94.76287244744604 kb_relative_information_score 95.58350032906873 kb_relative_information_score 95.1937791912942 kb_relative_information_score 94.83037893275365 kb_relative_information_score 94.4046321453603 kb_relative_information_score 97.02550829891511 kb_relative_information_score 95.5714471907994 kb_relative_information_score 96.04578371831414 kb_relative_information_score 94.72571945640522 mean_absolute_error 0.016579291203344507 mean_absolute_error 0.016617454798199757 mean_absolute_error 0.01655557039766469 mean_absolute_error 0.01664164607445823 mean_absolute_error 0.016563951398932915 mean_absolute_error 0.01665084103584489 mean_absolute_error 0.01638955066895524 mean_absolute_error 0.01657653538687985 mean_absolute_error 0.01651035986106454 mean_absolute_error 0.016658554444713935 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 0.825 predictive_accuracy 0.85 predictive_accuracy 0.86875 predictive_accuracy 0.8625 predictive_accuracy 0.84375 predictive_accuracy 0.85 predictive_accuracy 0.8375 predictive_accuracy 0.83125 predictive_accuracy 0.86875 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 0.825 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0,0,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,0] recall 0.86875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1] recall 0.8625 [0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1] recall 0.84375 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1] recall 0.85 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.83125 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.86875 [1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1] recall 0.8125 [1,1,1,1,1,1,1,1,0.5,0,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.8373379395628525 relative_absolute_error 0.8392653938484712 relative_absolute_error 0.8361399190739729 relative_absolute_error 0.840487175477687 relative_absolute_error 0.8365632019663074 relative_absolute_error 0.8409515674669124 relative_absolute_error 0.8277550842906675 relative_absolute_error 0.8371987569131224 relative_absolute_error 0.8338565586396218 relative_absolute_error 0.8413411335714095 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 0.08433716222534791 root_mean_squared_error 0.08449293104882048 root_mean_squared_error 0.08415484972472892 root_mean_squared_error 0.08459066239714515 root_mean_squared_error 0.08424939849579732 root_mean_squared_error 0.08472449745364191 root_mean_squared_error 0.08340416306031244 root_mean_squared_error 0.08431401779255125 root_mean_squared_error 0.08396867396582659 root_mean_squared_error 0.08471419825716611 root_relative_squared_error 0.8476203726812536 root_relative_squared_error 0.8491859082615373 root_relative_squared_error 0.8457880631080882 root_relative_squared_error 0.850168145269563 root_relative_squared_error 0.8467383140111885 root_relative_squared_error 0.8515132381974289 root_relative_squared_error 0.8382433782565945 root_relative_squared_error 0.84738776237952 root_relative_squared_error 0.8439169263282738 root_relative_squared_error 0.8514097273781792 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 3128.989972999989 usercpu_time_millis 2949.378288999924 usercpu_time_millis 2925.6524370000534 usercpu_time_millis 3038.746557999957 usercpu_time_millis 2822.3780090002037 usercpu_time_millis 2896.139919999996 usercpu_time_millis 3077.3225160000948 usercpu_time_millis 3005.644826999969 usercpu_time_millis 2846.3847559996793 usercpu_time_millis 3122.6647020000655 usercpu_time_millis_testing 202.01508900004228 usercpu_time_millis_testing 207.25608599991574 usercpu_time_millis_testing 147.47216099999605 usercpu_time_millis_testing 163.94307399991703 usercpu_time_millis_testing 199.765626000044 usercpu_time_millis_testing 199.7279790000448 usercpu_time_millis_testing 184.93297300005906 usercpu_time_millis_testing 200.82710800011228 usercpu_time_millis_testing 161.4060059998792 usercpu_time_millis_testing 200.42024899998978 usercpu_time_millis_training 2926.9748839999465 usercpu_time_millis_training 2742.122203000008 usercpu_time_millis_training 2778.1802760000573 usercpu_time_millis_training 2874.80348400004 usercpu_time_millis_training 2622.6123830001598 usercpu_time_millis_training 2696.411940999951 usercpu_time_millis_training 2892.3895430000357 usercpu_time_millis_training 2804.817718999857 usercpu_time_millis_training 2684.9787499998 usercpu_time_millis_training 2922.2444530000757