6003764 1 Jan van Rijn 9956 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) 4038495 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.26139488613162076 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 7 6902 min_samples_split 4 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 33355 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 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 12930631 description https://api.openml.org/data/download/12930631/description.xml -1 12930632 predictions https://api.openml.org/data/download/12930632/predictions.arff area_under_roc_curve 0.9933105570094616 [0.995455,1,0.976666,0.997394,0.982233,0.997671,0.995183,0.997118,0.989221,0.999052,0.996605,0.986221,0.999566,0.998934,0.990208,0.999842,0.984405,0.996012,0.999961,0.993959,1,0.981128,0.99771,0.999842,0.934559,0.99696,0.977653,0.963795,1,0.999763,0.999131,0.999921,0.980812,0.999842,0.998144,0.984602,0.997986,0.999803,0.988787,0.999329,0.999645,0.995065,0.992459,0.972086,0.987761,0.999447,0.982707,0.998026,0.990919,0.995736,0.996131,0.997315,0.999092,0.993525,0.991196,0.997986,1,0.954102,0.999447,1,1,0.999526,0.999368,1,0.999368,0.99775,1,0.990287,0.998737,0.991038,0.999131,0.99009,0.999961,0.991669,0.999882,0.999645,0.989932,0.999526,0.999487,0.992577,0.9985,0.990919,0.988313,0.997631,0.995696,0.99921,0.951181,0.999131,0.999724,0.998934,0.982154,0.989103,0.999368,0.999882,0.994551,0.993999,0.999921,0.999645,0.99775,0.999487] average_cost 0 f_measure 0.7667197485048537 [0.827586,0.857143,0.4,0.827586,0.6875,0.866667,0.8125,0.756757,0.8,0.8125,0.83871,0.83871,0.909091,0.875,0.689655,0.941176,0.529412,0.705882,0.967742,0.823529,0.888889,0.25,0.75,0.888889,0.111111,0.764706,0.8,0.210526,0.969697,0.882353,0.857143,0.882353,0.692308,0.8,0.8125,0.4,0.736842,0.888889,0.666667,0.83871,0.83871,0.580645,0.615385,0.48,0.62069,0.882353,0.571429,0.882353,0.764706,0.6875,0.722222,0.722222,0.8,0.8125,0.516129,0.705882,0.914286,0.758621,0.909091,0.941176,0.9375,0.833333,0.882353,0.8,0.933333,0.764706,0.914286,0.705882,0.848485,0.583333,0.810811,0.62069,0.941176,0.8,0.9375,0.864865,0.83871,0.9375,0.875,0.62069,0.903226,0.758621,0.5,0.645161,0.75,0.875,0.692308,0.714286,0.882353,0.810811,0.756757,0.3,0.875,0.909091,0.810811,0.785714,0.914286,1,0.848485,0.909091] kappa 0.7789020441042322 kb_relative_information_score 1141.914941906294 mean_absolute_error 0.012998552779773766 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 0.7837337915451749 [0.857143,0.789474,1,0.923077,0.6875,0.928571,0.8125,0.666667,0.857143,0.8125,0.866667,0.866667,0.882353,0.875,0.769231,0.888889,0.5,0.666667,1,0.777778,0.8,0.375,0.75,0.8,0.5,0.722222,0.857143,0.666667,0.941176,0.833333,1,0.833333,0.9,0.666667,0.8125,0.555556,0.636364,0.8,0.714286,0.866667,0.866667,0.6,0.8,0.666667,0.692308,0.833333,0.526316,0.833333,0.722222,0.6875,0.65,0.65,0.666667,0.8125,0.533333,0.666667,0.842105,0.846154,0.882353,0.888889,0.9375,0.75,0.833333,0.666667,1,0.722222,0.842105,0.666667,0.823529,0.875,0.714286,0.692308,0.888889,0.736842,0.9375,0.761905,0.866667,0.9375,0.875,0.692308,0.933333,0.846154,0.583333,0.666667,0.75,0.875,0.9,0.576923,0.833333,0.714286,0.666667,0.75,0.875,0.882353,0.714286,0.916667,0.842105,1,0.823529,0.882353] predictive_accuracy 0.7811131957473421 prior_entropy 6.6438309601245775 recall 0.7811131957473421 [0.8,0.9375,0.25,0.75,0.6875,0.8125,0.8125,0.875,0.75,0.8125,0.8125,0.8125,0.9375,0.875,0.625,1,0.5625,0.75,0.9375,0.875,1,0.1875,0.75,1,0.0625,0.8125,0.75,0.125,1,0.9375,0.75,0.9375,0.5625,1,0.8125,0.3125,0.875,1,0.625,0.8125,0.8125,0.5625,0.5,0.375,0.5625,0.9375,0.625,0.9375,0.8125,0.6875,0.8125,0.8125,1,0.8125,0.5,0.75,1,0.6875,0.9375,1,0.9375,0.9375,0.9375,1,0.875,0.8125,1,0.75,0.875,0.4375,0.9375,0.5625,1,0.875,0.9375,1,0.8125,0.9375,0.875,0.5625,0.875,0.6875,0.4375,0.625,0.75,0.875,0.5625,0.9375,0.9375,0.9375,0.875,0.1875,0.875,0.9375,0.9375,0.6875,1,1,0.875,0.9375] relative_absolute_error 0.6564928062857893 root_mean_prior_squared_error 0.09949872432040595 root_mean_squared_error 0.07141051283945232 root_relative_squared_error 0.7177027979725256 total_cost 0 area_under_roc_curve 0.9926866889578857 [1,1,0.968553,1,0.96519,0.971519,0.977848,1,1,1,1,1,1,1,0.987342,1,0.996835,1,1,1,1,0.936709,1,1,0.993671,1,1,0.990506,1,1,1,1,1,1,0.993711,0.981013,1,1,0.990506,0.993671,1,1,0.993711,1,1,1,0.93038,0.993711,0.990506,1,1,1,1,1,0.937107,1,1,0.993711,1,1,1,1,1,1,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996835,0.962025,1,1,0.996835,0.911392,0.984177,1,1,0.968354,0.958861,1,1,1,1] area_under_roc_curve 0.9940783974205877 [1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,1,1,1,1,0.958861,1,1,0.993671,1,0.984177,1,1,0.968354,0.987342,0.874214,0.996835,1,1,1,1,1,1,0.987421,0.955696,1,1,0.996835,1,1,1,0.974843,0.911392,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,0.90566,1,0.974684,1,0.984177,1,1,1,1,1,0.996835,1,1,1,1,0.962264,1,1,1,0.996835,0.996835,1,1,1,0.993671,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9952976972374813 [1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.987342,0.996835,1,0.987421,1,1,0.96519,1,1,1,1,0.993671,1,1,0.968553,1,1,1,1,1,0.993711,1,1,0.990506,1,0.996835,1,1,0.987421,1,0.987342,1,1,1,1,1,0.981132,0.987421,1,1,1,1,1,1,1,1,1,0.987421,1,1,0.955696,1,1,1,1,1,1,1,0.993671,1,0.968354,0.993711,1,0.993711,1,0.882911,1,1,0.993711,1,0.984177,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9945550712522886 [1,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,0.946203,1,0.981013,0.996835,1,1,1,0.990506,1,1,0.786164,0.993671,1,0.974684,1,1,0.996835,1,1,1,0.996835,1,1,1,0.937107,1,1,0.993711,0.943396,0.993671,1,1,1,0.993671,1,1,1,0.996835,1,0.987342,0.996835,0.996835,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,0.990506,1,1,1,0.996835,0.927215,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1] area_under_roc_curve 0.9955007065520262 [0.996835,1,0.990506,1,1,1,1,0.993671,0.867925,1,1,0.968553,1,1,0.981132,1,0.971519,0.996835,1,1,1,0.968553,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.990506,1,0.974684,1,1,1,0.993671,0.996835,1,0.981132,0.977848,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,0.993671,1,1,0.993711,1,1,0.993671,1,0.984177,0.993711,0.993711,1,1,0.968354,1,1,1,1,0.993671,1,1,1,0.993711,1,1,0.981013,1] area_under_roc_curve 0.9920832586975559 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990506,0.993671,1,1,1,0.987421,0.996835,1,1,1,0.933544,0.685535,1,1,0.987421,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,0.990506,0.977848,1,1,1,1,1,0.993671,0.993711,1,1,0.996835,0.993671,1,0.761076,1,1,1,1,1,1,1,1,1,0.987342,0.993671,1,1,1,1,1,1,1,1,1,1,1,0.990506,1,0.996835,1,0.974684,1,1,0.981132,1,1,1,0.987342,0.996835,1,1,1,1,1,1,1] area_under_roc_curve 0.9930800195048166 [1,1,0.952532,0.987421,1,1,1,1,1,1,0.984177,0.898734,1,1,1,1,1,1,1,1,1,1,1,1,0.936709,1,0.990506,0.993711,1,1,1,1,0.946203,1,0.996835,0.996835,1,1,0.990506,1,1,1,1,1,0.962025,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.936709,1,1,1,1,1,1,1,1,1,1,0.993671,0.987421,1,1,1,0.939873,1,1,0.987421,1,1,1,1,1,0.958861,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,1,1,1] area_under_roc_curve 0.9900510508717459 [0.955975,1,0.905063,1,1,1,0.993711,0.993671,0.987342,1,0.987342,1,1,1,1,1,0.981132,0.990506,1,0.968354,1,1,1,1,0.810127,1,1,0.993711,1,1,1,1,0.952532,1,1,0.987342,1,1,0.968354,1,0.993711,0.993671,1,0.930818,1,1,1,1,1,0.990506,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.993711,1,1,1,1,1,1,1,0.996835,0.955696,1,1,0.996835,1,0.987342,0.993711,0.672956,1,1,1,1,1,1,1,1,0.987342,1,1,1,1] area_under_roc_curve 0.9955758399012815 [0.968553,1,1,1,0.977848,1,1,0.987342,0.996835,1,1,1,1,1,0.990506,1,1,1,1,1,1,0.968354,1,1,0.987342,1,1,0.990506,1,1,1,0.996835,0.987421,1,1,1,0.981013,1,1,1,1,1,1,0.949686,1,1,1,1,0.943038,0.993671,0.990506,1,1,0.971519,0.993671,0.993711,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835,0.955975,1,0.987342,1,1,1,0.996835,1,1,1,1,0.996835,1,0.987342,1,1,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,0.996835] area_under_roc_curve 0.9953229513857724 [1,1,0.993671,0.987261,0.926752,1,0.996815,1,1,1,0.993671,1,1,1,1,1,0.962025,0.993671,1,1,1,0.990446,0.993671,1,0.914013,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993631,1,1,0.987261,1,0.873418,1,1,0.955696,1,0.996815,0.996815,0.984076,1,1,1,1,1,1,1,0.996815,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.990446,1,1,1,1,1,0.990446,1,0.993671,1,1,1,1,1,1,1,1] 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 0.7473950110514683 kappa 0.7852603323727944 kappa 0.8041692987997473 kappa 0.7789531854424884 kappa 0.7599115463591849 kappa 0.7915021323645554 kappa 0.8167963043392427 kappa 0.7725657427149965 kappa 0.741079886327755 kappa 0.7901871401151632 kb_relative_information_score 112.26771130743964 kb_relative_information_score 113.08931139663187 kb_relative_information_score 115.01672676084047 kb_relative_information_score 113.48737589702449 kb_relative_information_score 114.50680889003822 kb_relative_information_score 116.38638008316391 kb_relative_information_score 114.01171962001365 kb_relative_information_score 113.30854795124618 kb_relative_information_score 113.91403150310931 kb_relative_information_score 115.92632849678657 mean_absolute_error 0.013152205942443498 mean_absolute_error 0.013162383044039258 mean_absolute_error 0.013034675505049827 mean_absolute_error 0.013177124569874816 mean_absolute_error 0.01292834718753429 mean_absolute_error 0.012563266441891216 mean_absolute_error 0.012954897723804112 mean_absolute_error 0.0130766180902431 mean_absolute_error 0.01317928141303151 mean_absolute_error 0.012755206968505593 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 0.75 predictive_accuracy 0.7875 predictive_accuracy 0.80625 predictive_accuracy 0.78125 predictive_accuracy 0.7625 predictive_accuracy 0.79375 predictive_accuracy 0.81875 predictive_accuracy 0.775 predictive_accuracy 0.74375 predictive_accuracy 0.7924528301886792 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 0.75 [1,1,0,1,0.5,0.5,0,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0,1,1,0.5,1,1,0,1,0,1,1,1,1,0,0,1,1,0.5,0.5,1,1,0,0,1,1,0.5,1,0.5,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0,0.5,0,1,0.5,1,0.5,0.5,1,1,0.5,0.5,1,1,0.5,1] recall 0.7875 [1,1,0,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0,0.5,0,0,1,1,0.5,1,1,1,1,0,1,1,1,1,0.5,1,0,0.5,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,0,1,1,1,0,1,1,1,1] recall 0.80625 [1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,0.5,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,1,0.5,1,0.5,1,0.5,0,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.78125 [1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,0,1,0.5,1,0.5,1,1,0,1,1,0,0.5,1,0,1,1,0.5,1,1,1,0.5,0,1,1,0,1,1,0,0,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,0.5,1,1,0,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1] recall 0.7625 [0.5,1,0.5,1,1,1,1,0.5,0,0,1,0,1,1,0,1,0,0.5,1,1,1,0,0,1,0,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,1,1,1,0,0.5,0.5,0.5,1,1,1,0.5,0.5,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,1,1,0.5,1] recall 0.79375 [1,1,0.5,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,0.5,1,0,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,0.5,1,1,1,1,1,1,0,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0,0,0,1,0,1,1,0,1,1,1,0,0.5,1,1,1,1,1,1,1] recall 0.81875 [1,1,0,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,0.5,0.5,0,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0.5,0,1,1,1,0,1,1,0,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.775 [0,1,0,1,0,1,1,1,0,0,0,1,1,1,1,1,0,0.5,1,0.5,1,1,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0.5,1,1,0.5,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,0.5,1,0,1,1,0.5,0,0.5,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1] recall 0.74375 [0,1,0,1,0.5,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0,1,1,0,1,1,0.5,0.5,0,1,1,0,0.5,1,0.5,0.5,0,0.5,0.5,0,0,1,1,1,0.5,0,0.5,1,1,0.5,0,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,0.5] recall 0.7924528301886793 [1,0.5,0,0.5,0,1,0.5,1,1,1,0,1,0.5,1,0.5,1,0,1,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0,1,0,1,1,0,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1] relative_absolute_error 0.6642518380871577 relative_absolute_error 0.6647658323532883 relative_absolute_error 0.6583159662332969 relative_absolute_error 0.6655103527535415 relative_absolute_error 0.6529458571687421 relative_absolute_error 0.6345098207801902 relative_absolute_error 0.6542892225502495 relative_absolute_error 0.6604367295104595 relative_absolute_error 0.6656217573727965 relative_absolute_error 0.6442037933283983 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 0.07229308924437841 root_mean_squared_error 0.07226863429907288 root_mean_squared_error 0.07125733033983626 root_mean_squared_error 0.07198159529986863 root_mean_squared_error 0.07138533018831765 root_mean_squared_error 0.06972320451291633 root_mean_squared_error 0.07098452723512047 root_mean_squared_error 0.07147247672564153 root_mean_squared_error 0.07237311282512399 root_mean_squared_error 0.07030973524138732 root_relative_squared_error 0.7265716789578198 root_relative_squared_error 0.726325897917679 root_relative_squared_error 0.716161927567548 root_relative_squared_error 0.723441052218622 root_relative_squared_error 0.7174483723133673 root_relative_squared_error 0.7007460122837478 root_relative_squared_error 0.7134228086811893 root_relative_squared_error 0.7183268956643856 root_relative_squared_error 0.7273786476548467 root_relative_squared_error 0.7066408635103 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 7911.318482999945 usercpu_time_millis 7898.620698000059 usercpu_time_millis 7917.214736999995 usercpu_time_millis 7813.734791000002 usercpu_time_millis 7899.661352999942 usercpu_time_millis 7912.611698000092 usercpu_time_millis 7867.462034000027 usercpu_time_millis 7905.212797000104 usercpu_time_millis 7862.371722000034 usercpu_time_millis 7885.950928999932 usercpu_time_millis_testing 40.23856599997089 usercpu_time_millis_testing 39.936685000043326 usercpu_time_millis_testing 39.50618700002906 usercpu_time_millis_testing 39.44443599993974 usercpu_time_millis_testing 39.52671399997598 usercpu_time_millis_testing 39.34783900001548 usercpu_time_millis_testing 40.972968000005494 usercpu_time_millis_testing 39.51585900006194 usercpu_time_millis_testing 39.536197000074935 usercpu_time_millis_testing 39.74403999995957 usercpu_time_millis_training 7871.079916999975 usercpu_time_millis_training 7858.6840130000155 usercpu_time_millis_training 7877.708549999966 usercpu_time_millis_training 7774.290355000062 usercpu_time_millis_training 7860.134638999966 usercpu_time_millis_training 7873.263859000076 usercpu_time_millis_training 7826.489066000022 usercpu_time_millis_training 7865.696938000042 usercpu_time_millis_training 7822.8355249999595 usercpu_time_millis_training 7846.206888999973