5958264 1 Jan van Rijn 9954 Supervised Classification 6952 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1) 3993005 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "most_frequent" 6947 strategy_nominal "most_frequent" 6947 verbose 0 6947 categorical_features [] 6948 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 6948 handle_unknown "ignore" 6948 n_values "auto" 6948 sparse false 6948 threshold 0.0 6949 C 239.32272488507502 6953 cache_size 200 6953 class_weight null 6953 coef0 0.7876609335325613 6953 decision_function_shape null 6953 degree 3 6953 gamma 6.4707107254612195 6953 kernel "sigmoid" 6953 max_iter -1 6953 probability true 6953 random_state 17745 6953 shrinking false 6953 tol 1.3090148769668182e-05 6953 verbose false 6953 openml-pimp openml-python Sklearn_0.18.1. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12839958 description https://api.openml.org/data/download/12839958/description.xml -1 12839957 predictions https://api.openml.org/data/download/12839957/predictions.arff area_under_roc_curve 0.9963517992424245 [0.994279,1,1,1,0.999605,0.997001,0.999566,0.999961,0.997238,0.999961,0.999014,1,0.999803,0.985677,0.999527,1,1,0.991635,0.979088,0.972854,0.997672,0.999763,0.99633,1,0.994949,0.972656,0.982836,0.998658,0.999092,1,0.999882,1,0.999921,0.98986,0.999724,0.99929,0.993292,0.980903,0.999961,1,0.999211,1,1,0.999132,0.999369,0.999487,0.999803,0.996212,0.998224,0.99783,0.99637,0.998974,0.999132,0.988676,0.997514,0.988755,1,0.999803,0.993805,0.994397,0.999211,0.999645,0.996252,0.998658,0.999448,0.992819,0.987255,0.999921,0.994042,0.994397,0.995186,0.99858,0.993766,0.999921,0.988557,0.999803,0.999882,0.991596,1,0.999724,0.991517,0.998303,0.999211,0.995739,0.998619,0.999921,1,0.999527,0.999487,1,0.996173,0.999448,0.999132,0.998698,0.999527,0.997435,0.99929,0.998501,0.972972,0.99633] average_cost 0 f_measure 0.8236378372710488 [0.756757,0.967742,1,1,0.967742,0.827586,0.969697,0.967742,0.875,0.896552,0.875,0.941176,0.967742,0.714286,1,0.967742,1,0.4,0.352941,0.166667,0.83871,0.967742,0.727273,1,0.848485,0.4,0.411765,0.8125,0.903226,0.896552,0.969697,1,0.909091,0.533333,0.941176,0.848485,0.466667,0.457143,0.903226,1,0.833333,0.941176,0.967742,0.848485,0.967742,0.903226,0.9375,0.75,0.722222,0.903226,0.848485,0.814815,0.909091,0.758621,0.8125,0.5,1,0.969697,0.647059,0.705882,0.875,0.969697,0.777778,0.9375,0.903226,0.625,0.424242,1,0.8125,0.787879,0.758621,0.857143,0.484848,0.967742,0.764706,0.969697,0.933333,0.516129,1,0.9375,0.727273,0.903226,0.903226,0.645161,0.83871,0.866667,0.967742,0.848485,0.9375,1,0.774194,0.866667,0.909091,0.967742,0.967742,0.777778,0.882353,0.857143,0.363636,0.866667] kappa 0.8200757575757576 kb_relative_information_score 978.1231335845224 mean_absolute_error 0.01624905620579826 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 0.8304893847552515 [0.666667,1,1,1,1,0.923077,0.941176,1,0.875,1,0.875,0.888889,1,0.833333,1,1,1,0.428571,0.333333,0.15,0.866667,1,0.705882,1,0.823529,0.428571,0.388889,0.8125,0.933333,1,0.941176,1,0.882353,0.571429,0.888889,0.823529,0.5,0.421053,0.933333,1,0.75,0.888889,1,0.823529,1,0.933333,0.9375,0.75,0.65,0.933333,0.823529,1,0.882353,0.846154,0.8125,0.5,1,0.941176,0.611111,0.666667,0.875,0.941176,0.7,0.9375,0.933333,0.625,0.411765,1,0.8125,0.764706,0.846154,1,0.470588,1,0.722222,0.941176,1,0.533333,1,0.9375,0.705882,0.933333,0.933333,0.666667,0.866667,0.928571,1,0.823529,0.9375,1,0.8,0.928571,0.882353,1,1,0.7,0.833333,0.789474,0.352941,0.928571] predictive_accuracy 0.821875 prior_entropy 6.6438561897747395 recall 0.821875 [0.875,0.9375,1,1,0.9375,0.75,1,0.9375,0.875,0.8125,0.875,1,0.9375,0.625,1,0.9375,1,0.375,0.375,0.1875,0.8125,0.9375,0.75,1,0.875,0.375,0.4375,0.8125,0.875,0.8125,1,1,0.9375,0.5,1,0.875,0.4375,0.5,0.875,1,0.9375,1,0.9375,0.875,0.9375,0.875,0.9375,0.75,0.8125,0.875,0.875,0.6875,0.9375,0.6875,0.8125,0.5,1,1,0.6875,0.75,0.875,1,0.875,0.9375,0.875,0.625,0.4375,1,0.8125,0.8125,0.6875,0.75,0.5,0.9375,0.8125,1,0.875,0.5,1,0.9375,0.75,0.875,0.875,0.625,0.8125,0.8125,0.9375,0.875,0.9375,1,0.75,0.8125,0.9375,0.9375,0.9375,0.875,0.9375,0.9375,0.375,0.8125] relative_absolute_error 0.8206594043332441 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08326585154189667 root_relative_squared_error 0.8368532951936565 total_cost 0 area_under_roc_curve 0.9962861237162649 [0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,0.96519,0.987421,0.993711,1,1,1,0.993711,0.990506,1,1,1,1,1,1,1,0.977848,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.937107,0.993671,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,1,1,0.984177,1,0.990506,0.927215,1] area_under_roc_curve 0.9966023306265421 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.933544,1,1,1,0.984177,0.993671,0.993711,1,1,1,1,1,0.984177,0.981013,1,1,1,1,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,0.996835,0.993671,1,0.949686,1,0.993671,1,1,1,1,1,1,0.993671,1,0.996835,0.974684,1,0.993711,0.987421,0.996835,1,1,1,1,1,0.987342,1,1,0.990506,1,1,1,0.993671,0.996835,0.987421] area_under_roc_curve 0.9967229918000159 [1,1,1,1,1,1,0.993711,1,0.996835,1,1,1,1,1,0.996835,1,1,0.993671,0.981132,0.949367,1,1,0.987342,1,1,0.955696,0.996835,0.993711,1,1,1,1,1,0.987342,1,1,0.987421,0.968553,1,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.984177,1,1,1,0.974843,0.996835,1,1,1,0.987421,0.996835,0.993671,0.996835,1,1,0.993711,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1] area_under_roc_curve 0.9953812893081763 [1,1,1,1,1,0.993671,1,1,0.993671,1,0.996835,1,1,1,1,1,1,0.993671,0.91195,0.955696,1,1,1,1,0.981132,0.977848,0.984177,1,1,1,1,1,1,0.987342,1,1,1,0.949686,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.981013,1,0.987342,1,1,0.993711,0.993671,1,1,1,1,1,0.993671,0.974684,1,1,0.987342,0.974684,0.996835,0.981132,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,0.949686,0.984177] area_under_roc_curve 0.9963652376403154 [1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.949686,1,1,1,0.996835,1,0.990506,1,1,1,1,0.987342,0.993671,0.977848,1,1,1,1,1,1,0.974684,1,1,0.993671,0.981013,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.981132,1,1,0.990506,0.993671,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,1,1,1,0.939873,1,0.996835,0.981013,1,1,1,1,1,0.990506,0.987421,1,1,1,1,1,1,0.996835,1,1,0.996835,0.993711,1,1,0.993711,1] area_under_roc_curve 0.996284133428867 [0.958861,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.993711,0.955696,1,1,0.993671,1,0.993671,0.984177,0.990506,1,1,1,1,1,1,0.993671,1,1,0.993671,0.977848,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.974684,1,1,0.996835,1,0.993671,1,0.987421,1,1,0.987342,1,1,1,1,1,0.990506,1,1,0.984177,1,1,0.993671,1,1,0.981132,0.990506,1,0.996835,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,0.987421,0.993671] area_under_roc_curve 0.9960139519146562 [1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.987342,0.96519,0.996835,1,1,1,1,0.886792,0.930818,0.996835,1,1,0.996835,1,1,1,1,1,0.974684,0.990506,1,1,1,1,1,1,0.987421,1,1,0.993671,1,1,0.993711,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.981132,1,1,1,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.971519,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.939873,1] area_under_roc_curve 0.9973163462303957 [1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,0.993711,0.974684,1,0.996835,1,1,1,0.993671,0.962264,0.993711,1,0.993711,1,1,1,1,1,1,1,0.987342,0.990506,1,1,1,1,1,1,1,1,1,0.984177,1,1,0.974843,1,1,1,1,0.974684,1,1,0.993671,1,1,1,1,1,1,0.981132,0.949686,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1] area_under_roc_curve 0.9969986466045697 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1,0.993711,1,1,1,1,0.996835,0.993711,1,1,1,1,1,1,1,0.993711,1,1,0.996835,0.955696,1,1,1,1,1,0.993671,1,0.990506,1,1,0.993711,1,0.993671,1,1,0.936709,0.996835,0.949686,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.996835,1,1,0.987421,0.974684,1,1,1,1,0.987421,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9978293428071014 [0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.981132,0.971519,0.968553,0.996835,1,1,1,1,0.993711,0.993711,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,0.996835,1,1,1,1,0.990506,0.990506,1,1,0.987342,1,0.993711,0.993711,0.993671,1,1,0.993711,1,1,0.993671,1,0.996835,0.996835,1,1,1,1,1,0.987421,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.996835,1,1,0.993711,1,1,1] 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 0.8231555678364189 kappa 0.8231066887783305 kappa 0.8673352548663482 kappa 0.7978920775273359 kappa 0.78520097923083 kappa 0.7915103652517275 kappa 0.8041538340045803 kappa 0.8483591991470205 kappa 0.8357224657426056 kappa 0.8231416051478425 kb_relative_information_score 98.39121534575699 kb_relative_information_score 96.88988109487464 kb_relative_information_score 97.98894123451154 kb_relative_information_score 96.65566606291962 kb_relative_information_score 96.82273336444406 kb_relative_information_score 95.88744006954865 kb_relative_information_score 99.99322195086573 kb_relative_information_score 98.37124964639008 kb_relative_information_score 98.69507819455917 kb_relative_information_score 98.42770662065236 mean_absolute_error 0.01614855681354238 mean_absolute_error 0.016347424327254105 mean_absolute_error 0.016247465482642644 mean_absolute_error 0.016357837237370217 mean_absolute_error 0.016382474383441013 mean_absolute_error 0.016467932126510806 mean_absolute_error 0.015990778624482956 mean_absolute_error 0.01621486097106999 mean_absolute_error 0.016141529897960125 mean_absolute_error 0.016191702193708447 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 0.825 predictive_accuracy 0.86875 predictive_accuracy 0.8 predictive_accuracy 0.7875 predictive_accuracy 0.79375 predictive_accuracy 0.80625 predictive_accuracy 0.85 predictive_accuracy 0.8375 predictive_accuracy 0.825 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 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,0,1] recall 0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,0,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0] recall 0.86875 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.8 [1,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,0,0,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,0,0.5,1,1,0.5,0,0.5,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5] recall 0.7875 [1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0,1,0.5,1,1,0,1,1,1,0,1,1,0.5,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0,1,0,1,0.5,1,1,0,0,1,1,0.5,0,1,1,0,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1] recall 0.79375 [0.5,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,1,0,0.5,0,1,0.5,1,1,1,0.5,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0.5] recall 0.80625 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,0.5,0.5,0,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.85 [0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1] recall 0.8375 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0,0,1,1,1,1,0.5,1,1,1,1,0,1,0.5,0.5,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1] recall 0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,1,0,1,0.5,1,1,0,0,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1] relative_absolute_error 0.8155836774516341 relative_absolute_error 0.8256274912754584 relative_absolute_error 0.8205790647799301 relative_absolute_error 0.8261533958267772 relative_absolute_error 0.8273976961333831 relative_absolute_error 0.8317137437631708 relative_absolute_error 0.8076150820445923 relative_absolute_error 0.8189323722762607 relative_absolute_error 0.8152287827252575 relative_absolute_error 0.8177627370559809 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 0.08282349598750935 root_mean_squared_error 0.08361172874961299 root_mean_squared_error 0.08321558038696084 root_mean_squared_error 0.0838398814738061 root_mean_squared_error 0.08392140178034466 root_mean_squared_error 0.08436525315645162 root_mean_squared_error 0.0820910562752519 root_mean_squared_error 0.08301271047607231 root_mean_squared_error 0.08272813993796123 root_mean_squared_error 0.0830247838762835 root_relative_squared_error 0.8324074545941645 root_relative_squared_error 0.8403294919255684 root_relative_squared_error 0.8363480510763841 root_relative_squared_error 0.8426225130802532 root_relative_squared_error 0.8434418229880808 root_relative_squared_error 0.8479026971615042 root_relative_squared_error 0.8250461585120016 root_relative_squared_error 0.8343091317561718 root_relative_squared_error 0.8314490902370686 root_relative_squared_error 0.8344304739938816 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 1447.9941379999996 usercpu_time_millis 1449.9395399999996 usercpu_time_millis 1452.4993089999994 usercpu_time_millis 1458.7143750000005 usercpu_time_millis 1451.1835069999997 usercpu_time_millis 1445.731010000001 usercpu_time_millis 1446.9266679999996 usercpu_time_millis 1457.9320669999997 usercpu_time_millis 1465.8537609999998 usercpu_time_millis 1443.8201360000012 usercpu_time_millis_testing 162.2043259999999 usercpu_time_millis_testing 157.01114999999976 usercpu_time_millis_testing 154.5305569999993 usercpu_time_millis_testing 159.2038330000003 usercpu_time_millis_testing 158.97818100000018 usercpu_time_millis_testing 159.3702300000004 usercpu_time_millis_testing 163.9355069999997 usercpu_time_millis_testing 158.4522790000005 usercpu_time_millis_testing 159.5819469999995 usercpu_time_millis_testing 158.93166600000086 usercpu_time_millis_training 1285.7898119999998 usercpu_time_millis_training 1292.9283899999998 usercpu_time_millis_training 1297.968752 usercpu_time_millis_training 1299.5105420000002 usercpu_time_millis_training 1292.2053259999996 usercpu_time_millis_training 1286.3607800000007 usercpu_time_millis_training 1282.991161 usercpu_time_millis_training 1299.4797879999992 usercpu_time_millis_training 1306.2718140000004 usercpu_time_millis_training 1284.8884700000003