8822007 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) 6797057 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 100.96042593806108 7708 cache_size 200 7708 class_weight null 7708 coef0 0.6212776532352724 7708 decision_function_shape null 7708 degree 2 7708 gamma 0.40523663474210453 7708 kernel "poly" 7708 max_iter -1 7708 probability true 7708 random_state 19708 7708 shrinking true 7708 tol 0.002082747574074004 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 18559868 description https://api.openml.org/data/download/18559868/description.xml -1 18559870 predictions https://api.openml.org/data/download/18559870/predictions.arff area_under_roc_curve 0.9965194917929294 [0.987847,1,1,0.999921,0.998501,0.994989,0.999803,0.999605,0.997514,0.999961,0.998895,0.999527,0.999487,0.975892,0.999329,0.999527,1,0.991675,0.984375,0.975339,0.998461,0.999566,0.996449,0.999329,0.998619,0.977036,0.992109,0.99929,0.998698,1,0.999724,1,1,0.990017,0.999053,0.998816,0.99349,0.984296,0.999724,0.999882,0.999211,0.998698,1,0.998935,0.997001,0.999921,0.999369,0.99929,0.997554,0.996646,0.994673,0.999132,0.998067,0.992345,0.996883,0.994042,1,0.999448,0.993371,0.996765,0.998816,0.999527,0.997633,0.999171,0.999369,0.994318,0.986111,0.999961,0.998027,0.993963,0.996646,0.999487,0.996094,0.998343,0.989347,0.999527,0.999448,0.991083,0.999961,1,0.995739,0.997317,0.997948,0.995265,0.999329,0.999921,0.999961,0.99925,0.999329,1,0.99925,0.999605,0.998816,0.997593,0.996843,0.997869,0.998224,0.998224,0.968592,0.997948] average_cost 0 f_measure 0.8283829966477344 [0.648649,0.967742,0.967742,0.967742,0.933333,0.8,1,0.903226,0.83871,0.933333,0.882353,0.875,0.967742,0.714286,0.967742,0.903226,1,0.645161,0.4,0.258065,0.827586,0.967742,0.787879,1,0.875,0.388889,0.545455,0.848485,0.933333,0.933333,0.967742,0.967742,0.967742,0.551724,0.875,0.875,0.5625,0.516129,0.941176,0.896552,0.756757,0.909091,1,0.848485,0.9375,0.941176,0.857143,0.903226,0.764706,0.83871,0.787879,0.785714,0.8125,0.685714,0.689655,0.571429,1,0.9375,0.702703,0.742857,0.896552,0.823529,0.733333,0.903226,0.909091,0.682927,0.424242,0.969697,0.83871,0.727273,0.823529,0.933333,0.709677,0.967742,0.756757,0.909091,0.903226,0.685714,1,1,0.774194,0.848485,0.866667,0.533333,0.875,0.967742,0.933333,0.903226,0.933333,1,0.8125,0.903226,0.903226,0.875,0.967742,0.8,0.8,0.848485,0.516129,0.903226] kappa 0.8238636363636365 kb_relative_information_score 987.4846452116352 mean_absolute_error 0.01598940095097364 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 0.8374369419967718 [0.571429,1,1,1,1,0.857143,1,0.933333,0.866667,1,0.833333,0.875,1,0.833333,1,0.933333,1,0.666667,0.368421,0.266667,0.923077,1,0.764706,1,0.875,0.35,0.529412,0.823529,1,1,1,1,1,0.615385,0.875,0.875,0.5625,0.533333,0.888889,1,0.666667,0.882353,1,0.823529,0.9375,0.888889,1,0.933333,0.722222,0.866667,0.764706,0.916667,0.8125,0.631579,0.769231,0.526316,1,0.9375,0.619048,0.684211,1,0.777778,0.785714,0.933333,0.882353,0.56,0.411765,0.941176,0.866667,0.705882,0.777778,1,0.733333,1,0.666667,0.882353,0.933333,0.631579,1,1,0.8,0.823529,0.928571,0.571429,0.875,1,1,0.933333,1,1,0.8125,0.933333,0.933333,0.875,1,0.736842,0.736842,0.823529,0.533333,0.933333] predictive_accuracy 0.825625 prior_entropy 6.6438561897747395 recall 0.825625 [0.75,0.9375,0.9375,0.9375,0.875,0.75,1,0.875,0.8125,0.875,0.9375,0.875,0.9375,0.625,0.9375,0.875,1,0.625,0.4375,0.25,0.75,0.9375,0.8125,1,0.875,0.4375,0.5625,0.875,0.875,0.875,0.9375,0.9375,0.9375,0.5,0.875,0.875,0.5625,0.5,1,0.8125,0.875,0.9375,1,0.875,0.9375,1,0.75,0.875,0.8125,0.8125,0.8125,0.6875,0.8125,0.75,0.625,0.625,1,0.9375,0.8125,0.8125,0.8125,0.875,0.6875,0.875,0.9375,0.875,0.4375,1,0.8125,0.75,0.875,0.875,0.6875,0.9375,0.875,0.9375,0.875,0.75,1,1,0.75,0.875,0.8125,0.5,0.875,0.9375,0.875,0.875,0.875,1,0.8125,0.875,0.875,0.875,0.9375,0.875,0.875,0.875,0.5,0.875] relative_absolute_error 0.8075455025744247 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.082246122932365 root_relative_squared_error 0.8266046370548463 total_cost 0 area_under_roc_curve 0.9965232167024919 [1,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993671,1,0.981132,1,0.990506,0.984177,0.987421,1,1,1,1,1,0.996835,0.993671,1,1,1,1,1,1,0.993671,1,0.993711,1,0.993711,1,1,1,0.993711,1,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,0.962264,0.996835,1,1,1,1,1,1,0.958861,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.987421,0.993671,0.936709,1] area_under_roc_curve 0.9964040482445664 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.892405,1,1,1,0.984177,0.996835,0.987421,1,0.993711,0.993711,1,1,0.981013,0.971519,1,1,1,1,1,1,0.996835,0.996835,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,1,1,0.987421,1,0.996835,1,1,1,1,1,1,0.993671,1,1,0.984177,0.996835,1,0.981132,0.996835,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,1,0.974843] area_under_roc_curve 0.997114580845474 [1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.996835,1,0.939873,1,1,0.993671,1,1,0.946203,1,1,1,1,1,1,1,0.984177,1,1,0.993711,1,1,1,0.996835,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.981132,0.981013,1,1,1,0.987421,1,0.993671,1,1,1,0.987342,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1] area_under_roc_curve 0.9971966802006209 [1,1,1,1,1,0.993671,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,0.943396,0.971519,1,1,0.996835,1,0.993711,0.990506,1,1,1,1,1,1,1,0.987342,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,0.984177,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,0.977848,0.984177,1,0.981132,1,0.993711,1,1,0.996835,1,1,1,1,0.993671,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1] area_under_roc_curve 0.9962097464373855 [1,1,1,1,1,0.996835,1,1,1,1,0.990506,1,1,0.918239,1,1,1,0.990506,0.987421,0.990506,1,1,1,1,1,0.993671,0.990506,1,1,1,1,1,1,0.977848,1,1,0.993671,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,0.993711,1,1,1,1,1,0.996835,1,1,1,1,1,0.943038,1,0.993671,1,1,1,1,1,1,0.990506,0.993711,1,1,1,1,1,1,1,1,1,0.971519,0.993711,1,1,0.943396,1] area_under_roc_curve 0.996401311599395 [0.920886,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,1,0.958861,1,1,1,1,0.993671,0.990506,0.987342,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,0.981013,0.996835,1,0.996835,1,1,0.993711,1,1,1,1,0.990506,0.996835,1,1,1,1,1,0.990506,1,1,1,1,0.996835,1,0.993711,1,1,0.981013,1,1,0.996835,1,1,1,1,1,0.993671,1,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1] area_under_roc_curve 0.9954191047687285 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.996835,0.968354,0.996835,1,0.990506,1,1,0.886792,0.974843,0.993671,1,1,0.996835,1,1,0.993711,1,1,0.971519,0.993671,1,1,1,1,1,1,0.968553,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.987342,1,1,1,1,0.996835,1,0.987421,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.879747,1] area_under_roc_curve 0.9973581422657432 [1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,0.990506,0.993671,0.996835,1,1,1,0.993671,0.993711,1,1,0.974843,1,1,1,1,1,1,1,0.981013,0.993671,1,1,1,1,1,1,1,1,1,0.993671,1,0.987421,0.962264,1,1,1,1,0.987342,1,1,0.993671,1,1,1,1,1,1,0.974843,0.924528,1,1,0.996835,1,1,1,1,1,1,1,0.974843,1,1,0.993671,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835] area_under_roc_curve 0.9972354908048722 [1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.993711,0.990506,0.974843,0.996835,1,0.981132,0.993671,1,0.993711,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.949367,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,0.993671,1,1,0.968354,0.990506,0.993711,1,1,1,1,0.996835,1,1,1,1,1,0.984177,1,1,1,1,0.993711,0.984177,1,1,1,1,0.993711,1,1,1,0.993711,1,0.987421,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1] area_under_roc_curve 0.9979465209776294 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,0.974684,0.987421,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,0.993671,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.981013,1,1,1,0.993671,1,0.993711,0.993711,0.987342,1,1,1,1,1,0.990506,0.993671,1,0.990506,1,1,1,1,1,0.968553,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1] 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 0.7978840991631139 kappa 0.8041306322315681 kappa 0.8862873613140126 kappa 0.8167963043392427 kappa 0.8104639684106614 kappa 0.8104789355233545 kappa 0.8167963043392427 kappa 0.829397361977727 kappa 0.86101788605046 kappa 0.8042156785347754 kb_relative_information_score 99.27015798054921 kb_relative_information_score 97.31326375738969 kb_relative_information_score 98.61704285342583 kb_relative_information_score 97.65466671206897 kb_relative_information_score 98.20652834633488 kb_relative_information_score 97.89161415705898 kb_relative_information_score 101.4630590086461 kb_relative_information_score 98.46131294915652 kb_relative_information_score 99.54318125068492 kb_relative_information_score 99.063818196321 mean_absolute_error 0.01585401026969977 mean_absolute_error 0.016180679521380033 mean_absolute_error 0.016081312683333775 mean_absolute_error 0.016179295614184335 mean_absolute_error 0.01613901358324094 mean_absolute_error 0.0160399197114303 mean_absolute_error 0.015615275152466537 mean_absolute_error 0.01605691953028753 mean_absolute_error 0.0158548861575848 mean_absolute_error 0.015892697286128153 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 0.8 predictive_accuracy 0.80625 predictive_accuracy 0.8875 predictive_accuracy 0.81875 predictive_accuracy 0.8125 predictive_accuracy 0.8125 predictive_accuracy 0.81875 predictive_accuracy 0.83125 predictive_accuracy 0.8625 predictive_accuracy 0.80625 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 0.8 [1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0,1,0.5,0,1,0,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0,1] recall 0.80625 [1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0,0,0,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,1,0.5,0,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,0.5,0] recall 0.8875 [1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,0,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.81875 [0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,0,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1] recall 0.8125 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,1,1,1,0,1,1,1,0.5,1,1,0,0,0.5,1,0,0.5,1,1,1,1,1,1,0,1,1,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1] recall 0.8125 [0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,0,0.5,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1] recall 0.81875 [1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,0.5,1,1,0,0,0.5,1,1,0.5,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.83125 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5] recall 0.8625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1] recall 0.80625 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,0,1,1] relative_absolute_error 0.800707589378775 relative_absolute_error 0.8172060364333337 relative_absolute_error 0.8121875092592802 relative_absolute_error 0.8171361421305205 relative_absolute_error 0.8151016961232784 relative_absolute_error 0.810096955122741 relative_absolute_error 0.7886502602255814 relative_absolute_error 0.8109555318327021 relative_absolute_error 0.8007518261406453 relative_absolute_error 0.8026614790973801 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 0.0817345815562507 root_mean_squared_error 0.083002188176649 root_mean_squared_error 0.08243410820885724 root_mean_squared_error 0.08302773909384205 root_mean_squared_error 0.08274771299751546 root_mean_squared_error 0.08263635250742676 root_mean_squared_error 0.08057091214850998 root_mean_squared_error 0.08235821931904566 root_mean_squared_error 0.08177885576900638 root_mean_squared_error 0.0821405774739815 root_relative_squared_error 0.8214634527842004 root_relative_squared_error 0.8342033786679326 root_relative_squared_error 0.8284939601707131 root_relative_squared_error 0.8344601750478684 root_relative_squared_error 0.8316458068871918 root_relative_squared_error 0.8305265918505427 root_relative_squared_error 0.8097681351918032 root_relative_squared_error 0.8277312481305263 root_relative_squared_error 0.8219084253648035 root_relative_squared_error 0.8255438652858035 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 1613.250608996168 usercpu_time_millis 1484.151386001031 usercpu_time_millis 1469.8956880019978 usercpu_time_millis 1479.9038669989386 usercpu_time_millis 1488.370927003416 usercpu_time_millis 1534.3791450031858 usercpu_time_millis 1509.4643669981451 usercpu_time_millis 1508.931525000662 usercpu_time_millis 1493.5414469982788 usercpu_time_millis 1497.737485999096 usercpu_time_millis_testing 154.3751829995017 usercpu_time_millis_testing 157.7925179990416 usercpu_time_millis_testing 151.53443700182834 usercpu_time_millis_testing 151.80838699961896 usercpu_time_millis_testing 158.33522400134825 usercpu_time_millis_testing 180.82855800093967 usercpu_time_millis_testing 153.9169909992779 usercpu_time_millis_testing 153.71242000037455 usercpu_time_millis_testing 151.57906799868215 usercpu_time_millis_testing 153.53087399853393 usercpu_time_millis_training 1458.8754259966663 usercpu_time_millis_training 1326.3588680019893 usercpu_time_millis_training 1318.3612510001694 usercpu_time_millis_training 1328.0954799993197 usercpu_time_millis_training 1330.0357030020677 usercpu_time_millis_training 1353.5505870022462 usercpu_time_millis_training 1355.5473759988672 usercpu_time_millis_training 1355.2191050002875 usercpu_time_millis_training 1341.9623789995967 usercpu_time_millis_training 1344.206612000562