5986382 1 Jan van Rijn 9954 Supervised Classification 6969 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1) 4021115 bootstrap true 6902 class_weight null 6902 criterion "gini" 6902 max_depth null 6902 max_features 0.6253824636308909 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 12 6902 min_samples_split 8 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 49297 6902 verbose 0 6902 warm_start false 6902 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "mean" 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 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12896059 description https://api.openml.org/data/download/12896059/description.xml -1 12896060 predictions https://api.openml.org/data/download/12896060/predictions.arff area_under_roc_curve 0.9945241477272724 [0.987098,0.999092,0.999921,1,0.999329,0.991911,0.999053,0.999211,0.996567,0.999921,0.997988,0.999684,0.998777,0.986821,0.999645,0.999408,0.999921,0.988636,0.986387,0.969973,0.998422,0.999763,0.994831,1,0.998422,0.970447,0.984651,0.998343,0.997277,0.999763,0.99925,0.999961,0.998067,0.989978,0.999171,0.996015,0.991517,0.987058,0.996962,0.999527,0.998461,0.999014,0.999132,0.997001,0.997159,0.999645,0.99637,0.997672,0.995186,0.995778,0.997633,0.991872,0.995147,0.981416,0.994594,0.981968,1,0.998737,0.990215,0.984138,0.999882,0.999014,0.989702,0.995502,0.996449,0.995068,0.985401,0.999171,0.977667,0.993411,0.992109,0.997869,0.99562,0.999961,0.970841,0.994437,0.999053,0.989938,0.998895,0.996686,0.990057,0.993726,0.997475,0.995896,0.993095,0.997001,0.999961,0.994831,0.99858,1,0.99925,0.998895,0.99712,0.990254,0.995226,0.998146,0.996094,0.992819,0.968158,0.99925] average_cost 0 f_measure 0.7087541219516079 [0.444444,0.736842,1,1,0.909091,0.592593,0.9375,0.83871,0.6875,0.888889,0.777778,0.833333,0.722222,0.434783,0.941176,0.814815,0.820513,0.648649,0.5,0.24,0.722222,0.875,0.727273,1,0.733333,0.285714,0.214286,0.709677,0.823529,0.875,0.903226,0.903226,0.848485,0.5,0.882353,0.619048,0.588235,0.466667,0.8,0.914286,0.736842,0.833333,0.7,0.742857,0.666667,0.875,0.684211,0.785714,0.666667,0.75,0.866667,0.571429,0.787879,0.615385,0.666667,0.516129,0.969697,0.83871,0.181818,0.518519,0.941176,0.744186,0.5625,0.777778,0.717949,0.702703,0.516129,0.689655,0.285714,0.6,0.545455,0.764706,0.611111,0.967742,0.363636,0.666667,0.848485,0.608696,0.8,0.666667,0.380952,0.594595,0.727273,0.6,0.722222,0.774194,0.941176,0.628571,0.864865,0.969697,0.820513,0.75,0.758621,0.72,0.903226,0.833333,0.75,0.642857,0.2,0.777778] kappa 0.7209595959595959 kb_relative_information_score 1040.4699185819597 mean_absolute_error 0.015379164182494364 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 0.7332730231441529 [0.545455,0.636364,1,1,0.882353,0.727273,0.9375,0.866667,0.6875,0.8,0.7,0.75,0.65,0.714286,0.888889,1,0.695652,0.571429,0.45,0.333333,0.65,0.875,0.705882,1,0.785714,0.6,0.25,0.733333,0.777778,0.875,0.933333,0.933333,0.823529,0.583333,0.833333,0.5,0.555556,0.5,0.857143,0.842105,0.636364,0.75,0.583333,0.684211,0.818182,0.875,0.590909,0.916667,0.647059,0.75,0.928571,0.526316,0.764706,0.8,0.647059,0.533333,0.941176,0.866667,0.333333,0.636364,0.888889,0.592593,0.5625,0.7,0.608696,0.619048,0.533333,0.769231,0.6,0.642857,1,0.722222,0.55,1,0.666667,1,0.823529,1,0.666667,1,0.8,0.52381,0.705882,0.5,0.65,0.8,0.888889,0.578947,0.761905,0.941176,0.695652,0.625,0.846154,1,0.933333,0.75,0.75,0.75,0.5,0.7] predictive_accuracy 0.72375 prior_entropy 6.6438561897747395 recall 0.72375 [0.375,0.875,1,1,0.9375,0.5,0.9375,0.8125,0.6875,1,0.875,0.9375,0.8125,0.3125,1,0.6875,1,0.75,0.5625,0.1875,0.8125,0.875,0.75,1,0.6875,0.1875,0.1875,0.6875,0.875,0.875,0.875,0.875,0.875,0.4375,0.9375,0.8125,0.625,0.4375,0.75,1,0.875,0.9375,0.875,0.8125,0.5625,0.875,0.8125,0.6875,0.6875,0.75,0.8125,0.625,0.8125,0.5,0.6875,0.5,1,0.8125,0.125,0.4375,1,1,0.5625,0.875,0.875,0.8125,0.5,0.625,0.1875,0.5625,0.375,0.8125,0.6875,0.9375,0.25,0.5,0.875,0.4375,1,0.5,0.25,0.6875,0.75,0.75,0.8125,0.75,1,0.6875,1,1,1,0.9375,0.6875,0.5625,0.875,0.9375,0.75,0.5625,0.125,0.875] relative_absolute_error 0.7767254637623402 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08112955705184337 root_relative_squared_error 0.8153827277233219 total_cost 0 area_under_roc_curve 0.9934365297348936 [1,0.996835,1,1,1,1,1,1,0.993671,1,0.993671,0.996835,1,0.968354,1,0.993711,1,0.993671,0.962025,0.993711,1,1,0.993711,1,0.993711,0.990506,0.962025,1,1,1,0.990506,1,0.990506,0.993671,1,0.981132,1,0.993711,1,1,1,1,1,0.993671,1,1,1,1,1,0.962025,0.996835,1,1,0.984177,1,1,1,1,0.987421,0.990506,1,1,1,0.993671,1,1,0.990506,1,1,0.993711,0.984177,1,1,1,1,1,1,0.987342,1,1,0.993671,1,0.993711,1,0.974684,0.993671,1,1,0.996835,1,1,1,1,0.990506,1,0.993671,1,0.993671,0.860759,1] area_under_roc_curve 0.9932434718573362 [0.981132,1,1,1,1,0.987421,0.996835,1,1,1,1,0.996835,0.996835,0.955696,1,1,1,0.962025,0.990506,0.981132,1,1,1,1,1,0.949367,0.987342,1,1,1,1,1,1,0.996835,1,0.974843,0.974843,1,0.993711,1,1,1,1,0.993671,1,1,1,1,0.993671,1,1,0.952532,1,1,0.993711,0.968553,1,1,1,0.943038,1,1,0.993671,0.987342,1,0.996835,0.990506,1,0.955975,1,1,1,1,1,1,1,1,0.993671,1,0.987342,0.96519,0.990506,1,0.993711,1,1,1,0.996835,1,1,0.996835,1,1,0.968354,1,1,1,0.981013,0.993671,1] area_under_roc_curve 0.9953370054135817 [0.993671,1,1,1,1,0.993671,0.993711,1,0.996835,1,1,1,1,0.993671,1,1,1,0.993671,1,0.898734,1,0.993711,0.993671,1,1,0.990506,1,1,1,1,1,1,1,0.981013,1,1,0.993711,0.968553,1,1,0.996835,1,1,1,0.993671,1,0.993671,1,0.990506,1,0.996835,1,1,1,1,1,1,1,0.974843,0.984177,1,0.993711,1,1,0.990506,0.990506,0.981013,1,0.987421,0.984177,0.996835,1,1,1,1,1,1,0.987342,0.993671,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.984177,1,1,1,0.993671,0.974843,1] area_under_roc_curve 0.9959308574158104 [0.990506,0.996835,1,1,1,0.984177,1,1,0.993671,1,1,1,1,0.993671,1,1,1,1,0.937107,0.996835,1,1,1,1,0.993711,0.981013,0.974684,1,1,1,1,1,1,0.990506,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.936709,1,0.993671,1,1,1,0.990506,1,1,0.993671,1,0.993671,1,0.984177,0.993671,1,1,0.996835,0.996835,0.993711,1,0.987421,0.993671,1,0.990506,1,1,0.993711,1,1,0.993671,0.993711,1,1,1,1,1,1,1,0.987421,1,1,0.987421,0.987342,0.993671,1,1] area_under_roc_curve 0.9933220882095377 [1,1,1,1,1,1,1,1,1,1,0.996835,1,0.993711,0.974843,1,1,1,0.996835,0.993711,0.987342,0.996835,1,1,1,1,0.987342,0.984177,1,1,1,1,1,1,0.974684,1,1,1,0.962025,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.996835,1,0.984177,0.987342,1,0.996835,0.993671,1,1,1,0.987421,1,0.993671,1,0.968553,1,0.962025,0.987342,0.996835,1,0.993711,1,0.857595,1,1,0.987342,1,1,1,1,0.993671,0.993671,0.968553,0.993711,1,1,1,1,1,0.990506,1,0.981132,0.958861,1,0.996835,1,0.987421,0.996835] area_under_roc_curve 0.9954937405461346 [0.968354,1,1,1,1,0.984177,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.943038,1,1,0.996835,1,1,0.996835,0.977848,1,1,1,1,1,0.993671,0.993671,0.987421,0.996835,0.981013,1,0.990506,1,0.996835,1,1,1,1,1,1,0.996835,1,0.993671,1,1,0.996835,1,0.993671,0.984177,1,1,0.987342,0.993711,1,1,0.987421,1,1,0.996835,1,1,0.984177,1,0.977848,0.990506,1,1,0.981013,0.987421,1,1,1,1,0.993711,0.993671,1,0.993671,1,1,1,1,0.993671,1,1,1,0.987421,1,1,1,1,0.981132,1,1] area_under_roc_curve 0.996290601862909 [1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,0.993711,1,0.996835,1,1,1,0.946203,0.990506,1,0.993671,1,0.996835,0.930818,0.987421,0.993671,1,1,1,1,1,0.968553,1,1,1,1,1,1,1,0.996835,1,1,0.974843,0.996835,0.990506,0.996835,1,1,1,1,1,1,0.990506,0.993671,1,1,0.993671,1,1,1,1,0.993671,1,1,0.974843,0.996835,0.990506,1,0.993711,1,0.996835,1,1,0.993711,1,0.993711,1,1,0.974684,1,1,0.996835,1,1,1,0.968553,1,1,1,1,0.993671,1,1,1,1,1,1,1] area_under_roc_curve 0.9943538034392165 [1,1,1,1,1,0.996835,1,1,0.993711,1,0.993711,1,1,1,0.993711,1,1,0.987421,0.968354,0.993671,0.996835,1,1,1,1,0.993711,0.987421,1,0.949686,0.996835,1,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,1,1,0.993671,0.996835,1,0.987421,1,0.993711,0.996835,0.984177,1,0.996835,0.958861,1,1,0.977848,0.974843,1,0.996835,0.993711,1,1,0.949686,0.993711,1,0.955696,0.987342,1,1,1,1,0.996835,1,1,0.987421,1,1,0.984177,0.987421,0.981013,1,1,0.981013,1,0.981132,1,1,1,1,1,0.993711,1,0.993671,0.981013,0.993711,0.981013,1] area_under_roc_curve 0.9952641111376485 [0.981132,1,1,1,1,0.993711,1,1,0.996835,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,0.949686,1,1,0.91195,0.993711,1,1,1,1,1,1,0.993711,1,1,1,0.984177,1,1,0.993711,1,0.996835,0.993671,1,1,1,1,0.993711,1,1,0.993671,1,0.958861,0.993671,0.968553,1,1,1,0.987342,1,1,1,1,1,1,0.987342,1,0.990506,1,1,0.987421,0.993671,1,0.990506,0.974684,1,1,1,1,0.993671,0.974843,1,0.993711,1,1,1,0.996835,1,1,1,1,1,0.993671,1,0.996835,0.993711,0.993671,0.943038,1] area_under_roc_curve 0.9958584607117269 [0.949686,1,0.993711,1,1,0.993711,1,0.981132,1,1,1,1,0.996835,0.993671,1,1,1,0.993711,0.993671,1,1,1,1,1,1,0.90566,0.993711,1,0.996835,1,1,0.996835,1,1,0.993671,0.993671,0.993671,1,1,1,1,1,1,1,1,1,1,0.990506,0.987421,1,1,1,1,0.984177,1,1,1,1,0.996835,0.993671,1,0.996835,0.974684,0.990506,0.987421,1,0.993671,1,0.993671,0.993711,0.974843,1,0.984177,1,0.984177,0.993671,1,1,1,0.990506,1,0.981132,1,0.968553,1,1,1,1,1,1,1,0.996835,0.996835,1,1,1,0.993711,1,1,1] 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 0.6842063711364623 kappa 0.7537198563365829 kappa 0.7410492243318991 kappa 0.6842313005723307 kappa 0.7410185550730359 kappa 0.7346914603813811 kappa 0.7599115463591849 kappa 0.7220467466835123 kappa 0.7157296272899558 kappa 0.6716264751154438 kb_relative_information_score 102.69733288396064 kb_relative_information_score 103.51052578961745 kb_relative_information_score 103.86241253032124 kb_relative_information_score 103.93085578937372 kb_relative_information_score 104.10184190596064 kb_relative_information_score 104.70026452367603 kb_relative_information_score 105.94510631616194 kb_relative_information_score 103.56130289520006 kb_relative_information_score 104.73323279468181 kb_relative_information_score 103.42704315300507 mean_absolute_error 0.015477426753797 mean_absolute_error 0.015373193205534092 mean_absolute_error 0.015410401019633016 mean_absolute_error 0.01544908508549869 mean_absolute_error 0.015297185958639086 mean_absolute_error 0.015369304423625446 mean_absolute_error 0.015180609871288372 mean_absolute_error 0.015396569461995654 mean_absolute_error 0.015358643008505484 mean_absolute_error 0.015479223036426907 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 0.6875 predictive_accuracy 0.75625 predictive_accuracy 0.74375 predictive_accuracy 0.6875 predictive_accuracy 0.74375 predictive_accuracy 0.7375 predictive_accuracy 0.7625 predictive_accuracy 0.725 predictive_accuracy 0.71875 predictive_accuracy 0.675 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 0.6875 [1,0.5,1,1,1,1,1,1,0,1,0.5,0.5,0.5,0,1,0,1,0,0.5,1,1,1,1,1,0,0,0,1,0.5,0,0.5,1,0.5,0,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,0,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0.5,1,1,0,0.5,1,0.5,1,0,0.5,0.5,0.5,1,0.5,0,1,0,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,1] recall 0.75625 [0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0,1,0.5,1,0,1,1,0,0.5,1,1,1,1,1,0,0.5,1,0,1,0.5,1,1,1,1,0,0.5,0.5,1,0,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,0,1] recall 0.74375 [0,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,0,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,0.5,1,1,1,1,0,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,0,0.5,0,1,1,1,0,0.5,1,0.5,1,0.5,0,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0,1] recall 0.6875 [0,1,1,1,0.5,0,1,0.5,0.5,1,1,1,1,0.5,1,0.5,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,0.5,1,0,0.5,0,0.5,1,0.5,0,0.5,1,0.5,1,0.5,1,0.5,1,1,1,0,1,0,1,1,1,1,0,0.5,1,1,0,0.5,0,0] recall 0.74375 [0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0.5,0.5,0.5,1,1,1,1,0,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,0,0.5,0,1,1,0,1,1,1,1,1,0.5,1,0,0,0,0.5,0.5,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,1] recall 0.7375 [0.5,1,1,1,1,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0,0,0.5,0.5,1,1,1,0,0,0,1,1,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0.5,1,0,1,1,1,1,0,1,0.5,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,1,1,0,0.5,0.5,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1] recall 0.7625 [1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0.5,1,1,1,0.5,0,0,0.5,1,1,0.5,0,1,0,1,1,1,0.5,0.5,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,0,0.5,0.5,1,0.5,0,1,1,1,1,1,1,1,0,0.5,0.5,0.5,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,0,1] recall 0.725 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0.5,0.5,1,1,0.5,1,1,0,0,1,1,0,1,1,0,1,0.5,0,1,0,1,1,1,0.5,1,1,0,1,1,0,0,0,1,0.5,0.5,1,0,1,1,1,1,1,1,1,0.5,0.5,1,0,1] recall 0.71875 [0,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,0,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0.5,1,0.5,1,1,0.5,0,1,1,0.5,0.5,0.5,0.5,0,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0,0,1,0.5,0.5,1,0,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,0,1] recall 0.675 [0,0.5,1,1,1,1,1,0,1,1,1,1,0.5,0,1,1,1,1,0,0,1,1,1,1,1,0,0,0.5,1,0,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,0.5,0.5,1,0.5,0,1,0.5,0.5,1,0.5,0.5,1,1,1,0,0,1,1,0,0.5,1,1,0.5,0,0,0,0,1,0,1,0,0,1,1,1,0,1,0,1,0,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0.5,0.5,1] relative_absolute_error 0.781688219888736 relative_absolute_error 0.7764238992693973 relative_absolute_error 0.7783030817996459 relative_absolute_error 0.7802568224999326 relative_absolute_error 0.7725851494262151 relative_absolute_error 0.7762274961426979 relative_absolute_error 0.7666974682468863 relative_absolute_error 0.7776045182826076 relative_absolute_error 0.775689040833609 relative_absolute_error 0.7817789412336809 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 0.08169112329925789 root_mean_squared_error 0.08101913467721653 root_mean_squared_error 0.08120183460745188 root_mean_squared_error 0.08149418650544649 root_mean_squared_error 0.08088538421609193 root_mean_squared_error 0.0809932922189253 root_mean_squared_error 0.0801107467871116 root_mean_squared_error 0.08119916157071608 root_mean_squared_error 0.08092713791450468 root_mean_squared_error 0.08176107925467281 root_relative_squared_error 0.82102668086757 root_relative_squared_error 0.8142729411018153 root_relative_squared_error 0.8161091444891327 root_relative_squared_error 0.8190473916176064 root_relative_squared_error 0.8129286983894295 root_relative_squared_error 0.8140132146235958 root_relative_squared_error 0.8051432992970252 root_relative_squared_error 0.816082279459122 root_relative_squared_error 0.8133483388477468 root_relative_squared_error 0.821729764673516 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 2010.9302459999299 usercpu_time_millis 1838.814887999888 usercpu_time_millis 1878.1612029999906 usercpu_time_millis 1839.501668999901 usercpu_time_millis 1843.2620759999736 usercpu_time_millis 1862.9800149999483 usercpu_time_millis 1818.0082650000031 usercpu_time_millis 1813.7087150000752 usercpu_time_millis 1823.4006080000427 usercpu_time_millis 1832.5175920000447 usercpu_time_millis_testing 32.410125999945194 usercpu_time_millis_testing 32.28032999993502 usercpu_time_millis_testing 31.878894999977092 usercpu_time_millis_testing 32.902489999969475 usercpu_time_millis_testing 32.347360000017034 usercpu_time_millis_testing 33.301149999942936 usercpu_time_millis_testing 32.33967799997117 usercpu_time_millis_testing 32.59914500006289 usercpu_time_millis_testing 32.15849100001833 usercpu_time_millis_testing 32.010684000056244 usercpu_time_millis_training 1978.5201199999847 usercpu_time_millis_training 1806.534557999953 usercpu_time_millis_training 1846.2823080000135 usercpu_time_millis_training 1806.5991789999316 usercpu_time_millis_training 1810.9147159999566 usercpu_time_millis_training 1829.6788650000053 usercpu_time_millis_training 1785.668587000032 usercpu_time_millis_training 1781.1095700000124 usercpu_time_millis_training 1791.2421170000243 usercpu_time_millis_training 1800.5069079999885