5995646 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) 4030379 bootstrap false 6902 class_weight null 6902 criterion "entropy" 6902 max_depth null 6902 max_features 0.7289554400367535 6902 max_leaf_nodes null 6902 min_impurity_split 1e-07 6902 min_samples_leaf 13 6902 min_samples_split 20 6902 min_weight_fraction_leaf 0.0 6902 n_estimators 100 6902 n_jobs 1 6902 oob_score false 6902 random_state 26519 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 "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 openml-pimp openml-python Sklearn_0.18.1. study_71 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 12914438 description https://api.openml.org/data/download/12914438/description.xml -1 12914439 predictions https://api.openml.org/data/download/12914439/predictions.arff area_under_roc_curve 0.9876337594696968 [0.978535,0.997751,0.999882,0.999487,0.996607,0.98765,0.996725,0.994003,0.994871,0.998501,0.997238,0.997356,0.994476,0.975616,0.99708,0.990767,0.999684,0.970249,0.970368,0.959517,0.996725,0.996883,0.984848,1,0.988755,0.956163,0.967211,0.980824,0.99566,0.998303,0.999053,0.999882,0.991398,0.979956,0.993805,0.997711,0.97459,0.97605,0.996962,0.999448,0.982086,0.995344,0.998619,0.994318,0.99633,0.96512,0.997317,0.990728,0.966619,0.987334,0.985243,0.981652,0.991556,0.951152,0.988952,0.954545,1,0.997948,0.991951,0.973485,0.998658,0.994042,0.993016,0.994594,0.995896,0.990491,0.968632,0.999527,0.955295,0.96583,0.979206,0.997593,0.988715,0.995462,0.96003,0.987176,0.998146,0.965475,0.998264,0.99783,0.988321,0.988557,0.986466,0.991162,0.988005,0.978851,0.99854,0.985795,0.994673,0.998619,0.998777,0.99858,0.989031,0.98256,0.991201,0.995423,0.990885,0.988202,0.954624,0.990333] average_cost 0 f_measure 0.5922285487015989 [0.551724,0.666667,1,0.866667,0.764706,0.4,0.866667,0.857143,0.580645,0.774194,0.666667,0.684211,0.590909,0.333333,0.702703,0.714286,0.8,0.342857,0.5,0.086957,0.742857,0.75,0.514286,1,0.571429,0.105263,0.352941,0.631579,0.727273,0.742857,0.689655,0.914286,0.705882,0.4,0.702703,0.736842,0.342857,0.411765,0.608696,0.761905,0.642857,0.666667,0.8,0.606061,0.6875,0.516129,0.717949,0.56,0.64,0.727273,0.580645,0.424242,0.578947,0.333333,0.413793,0.071429,0.941176,0.717949,0.457143,0.444444,0.702703,0.564103,0.6875,0.645161,0.702703,0.4375,0.363636,0.842105,0.173913,0.166667,0.24,0.702703,0.540541,0.722222,0.5,0.875,0.789474,0.095238,0.8125,0.875,0.642857,0.516129,0.611111,0.347826,0.5,0.717949,0.896552,0.484848,0.583333,0.787879,0.761905,0.769231,0.5,0.210526,0.4,0.666667,0.625,0.5,0,0.571429] kappa 0.6092171717171717 kb_relative_information_score 1062.5117605924636 mean_absolute_error 0.014330190844722394 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 0.6054358322201572 [0.615385,0.565217,1,0.928571,0.722222,0.428571,0.928571,0.789474,0.6,0.8,0.714286,0.590909,0.464286,0.5,0.619048,0.833333,0.666667,0.315789,0.5,0.142857,0.684211,0.75,0.473684,1,0.526316,0.333333,0.333333,0.545455,0.705882,0.684211,0.769231,0.842105,0.666667,0.428571,0.619048,0.636364,0.315789,0.388889,1,0.615385,0.75,0.6,0.736842,0.588235,0.6875,0.533333,0.608696,0.777778,0.888889,0.705882,0.6,0.411765,0.5,0.5,0.461538,0.083333,0.888889,0.608696,0.421053,0.545455,0.619048,0.478261,0.6875,0.666667,0.619048,0.4375,0.352941,0.727273,0.285714,0.25,0.333333,0.619048,0.47619,0.65,0.75,0.875,0.681818,0.2,0.8125,0.875,0.75,0.533333,0.55,0.571429,0.45,0.608696,1,0.470588,0.875,0.764706,0.615385,0.652174,0.75,0.666667,0.555556,0.6,0.625,0.5,0,0.666667] predictive_accuracy 0.613125 prior_entropy 6.6438561897747395 recall 0.613125 [0.5,0.8125,1,0.8125,0.8125,0.375,0.8125,0.9375,0.5625,0.75,0.625,0.8125,0.8125,0.25,0.8125,0.625,1,0.375,0.5,0.0625,0.8125,0.75,0.5625,1,0.625,0.0625,0.375,0.75,0.75,0.8125,0.625,1,0.75,0.375,0.8125,0.875,0.375,0.4375,0.4375,1,0.5625,0.75,0.875,0.625,0.6875,0.5,0.875,0.4375,0.5,0.75,0.5625,0.4375,0.6875,0.25,0.375,0.0625,1,0.875,0.5,0.375,0.8125,0.6875,0.6875,0.625,0.8125,0.4375,0.375,1,0.125,0.125,0.1875,0.8125,0.625,0.8125,0.375,0.875,0.9375,0.0625,0.8125,0.875,0.5625,0.5,0.6875,0.25,0.5625,0.875,0.8125,0.5,0.4375,0.8125,1,0.9375,0.375,0.125,0.3125,0.75,0.625,0.5,0,0.5] relative_absolute_error 0.7237470123597156 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.07890211518917381 root_relative_squared_error 0.7929960946905787 total_cost 0 area_under_roc_curve 0.988732485470902 [1,1,1,1,0.993671,1,1,1,0.993671,1,0.993671,0.987342,0.990506,0.958861,1,1,1,0.943038,0.949367,0.974843,1,0.993711,1,1,0.993711,0.981013,0.987342,0.996835,0.987342,1,0.996835,1,0.990506,0.977848,1,0.987421,1,0.993711,1,1,1,1,1,1,1,0.987342,1,1,0.996835,0.971519,0.93038,1,0.993711,0.984177,1,0.993711,1,1,0.993711,0.977848,1,1,1,0.987342,1,1,0.993671,1,0.993711,0.937107,0.952532,1,0.987342,0.987342,1,1,1,0.984177,1,1,1,0.987342,1,1,0.990506,0.924051,1,0.993671,0.990506,0.987421,1,1,1,0.987342,0.996835,0.990506,1,0.996835,0.851266,1] area_under_roc_curve 0.9882294403311838 [0.981132,1,1,1,0.996835,1,0.993671,1,1,1,1,1,0.993671,0.949367,1,1,1,0.933544,0.996835,0.987421,1,0.962264,0.993711,1,1,0.936709,0.981013,0.936709,1,1,1,1,1,0.987342,0.996835,1,0.91195,1,0.993711,1,0.993711,1,1,0.993671,1,0.981013,0.993711,0.993711,0.981013,1,1,0.949367,1,0.987342,1,0.930818,1,1,1,0.920886,1,1,1,0.990506,1,1,0.993671,1,0.867925,1,0.990506,1,0.984177,1,1,1,1,0.952532,1,0.996835,0.984177,0.993671,0.974843,0.981132,1,1,0.987342,0.993671,0.977848,1,0.996835,1,1,0.968354,0.993671,0.996835,0.993711,0.971519,0.990506,1] area_under_roc_curve 0.9864866949287479 [0.981013,0.993671,1,1,0.987342,0.977848,0.993711,1,0.977848,1,0.993671,1,1,0.993671,0.981013,0.987342,1,0.987342,0.899371,0.917722,1,0.981132,0.93038,1,0.91195,0.996835,1,1,1,1,1,1,1,0.958861,0.987421,1,1,0.924528,1,1,0.96519,1,1,1,0.996835,0.993711,0.996835,1,0.797468,1,0.984177,1,1,0.974684,1,0.996835,1,0.996835,0.993711,0.946203,1,0.987421,0.993671,1,0.996835,0.974684,0.987342,1,0.987421,0.952532,0.996835,0.996835,0.981132,0.990506,1,1,1,0.971519,0.996835,1,1,1,1,0.996835,1,1,1,0.996835,1,1,1,1,0.993711,0.974684,0.996835,1,0.987342,0.984177,0.981132,0.996835] area_under_roc_curve 0.9872405162805507 [1,1,1,1,0.993671,0.974684,1,1,0.993671,0.996835,1,0.996835,1,1,1,1,1,0.977848,0.823899,0.987342,1,1,0.996835,1,0.962264,0.96519,0.901899,1,1,0.996835,1,1,1,0.990506,1,0.981132,1,0.981132,1,1,0.984177,1,1,0.993711,1,1,1,1,0.993671,1,0.990506,1,0.962264,0.924051,1,0.993671,1,1,1,0.990506,1,1,1,1,0.990506,0.987342,0.949367,1,0.993711,0.914557,0.958861,0.993671,0.993711,1,0.993711,0.946203,0.996835,0.943038,1,0.993671,0.955975,0.974684,1,0.984177,1,1,1,1,1,1,1,1,0.949686,0.987342,1,0.993711,0.987342,0.996835,0.974843,0.946203] area_under_roc_curve 0.9853888026431017 [0.971519,1,1,1,0.993711,0.984177,0.962264,1,1,1,1,0.984177,1,0.805031,1,0.984177,1,1,0.993711,0.990506,0.981013,0.993671,1,1,1,0.939873,0.977848,1,1,0.993671,1,1,0.981013,0.952532,1,1,0.984177,0.939873,0.990506,1,1,0.996835,0.987421,1,1,1,1,0.993671,1,0.993671,1,0.930818,0.990506,0.974843,0.96519,0.924051,1,0.981013,0.996835,0.987421,1,1,1,0.987421,0.996835,1,0.849057,1,0.898734,0.990506,1,1,1,0.974843,0.901899,1,0.996835,0.952532,1,1,1,1,0.987342,0.996835,0.974843,1,1,1,1,1,1,0.993671,0.968553,0.993711,0.958861,1,0.990506,1,0.987421,0.990506] area_under_roc_curve 0.9864058395032244 [0.933544,1,1,1,1,0.987342,1,1,1,0.996835,1,1,1,0.987421,1,0.996835,1,1,1,0.924051,1,0.996835,0.977848,1,0.990506,0.984177,0.96519,0.993711,1,1,1,1,0.955696,0.993671,0.949686,1,0.924051,0.981013,1,1,1,0.984177,1,0.993711,1,1,1,0.996835,0.962025,0.971519,1,0.981132,1,1,0.974684,0.920886,1,1,1,1,1,0.987342,0.974843,1,1,1,0.968553,1,0.971519,1,0.962025,0.990506,1,1,0.85443,1,0.996835,0.974684,1,0.993711,1,0.987342,1,0.987342,0.993711,1,1,0.937107,0.984177,1,1,0.993671,0.968553,1,1,1,0.993671,0.949686,0.968553,0.981013] area_under_roc_curve 0.9899724345195443 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[1,1,1,1,1,0.990506,0.996835,1,0.993711,1,0.993711,1,0.993671,1,1,0.962025,1,0.943396,0.984177,0.933544,0.990506,1,1,1,0.996835,0.993711,0.899371,0.977848,1,0.996835,1,1,1,1,1,1,0.981013,0.968354,1,1,1,0.996835,1,0.990506,1,0.990506,1,1,0.987421,1,0.974843,0.977848,0.977848,1,1,0.96519,1,1,0.987342,1,0.996835,0.990506,0.993711,0.996835,1,0.968553,0.968553,1,0.958861,0.984177,0.987421,1,1,0.987421,0.984177,1,1,0.968553,1,0.993711,0.968354,1,0.955696,1,0.946203,0.917722,1,0.987421,1,1,1,1,1,0.955975,1,1,0.977848,1,0.952532,0.984177] area_under_roc_curve 0.9903222275296553 [0.968553,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,0.974843,1,0.990506,1,1,1,1,0.981132,0.996835,1,0.993671,0.968354,1,1,0.918239,0.996835,1,0.984177,0.981013,0.908228,1,0.990506,0.949686,1,1,0.993671,1,0.800633,0.984177,0.937107,1,1,0.993671,0.987342,1,1,1,1,1,1,0.990506,1,0.971519,0.981132,1,0.993711,0.974684,1,0.990506,0.96519,1,0.993711,1,0.996835,1,1,1,0.993711,0.993671,1,1,0.981013,0.993711,1,1,1,1,0.990506,0.987421,0.987342,0.987421,0.993671,0.996835,1] area_under_roc_curve 0.9922286740705356 [0.981132,0.993671,0.993711,1,1,0.993711,1,0.930818,0.993671,1,1,1,0.996835,0.987342,0.996835,1,1,0.993711,0.990506,0.993711,1,1,1,1,1,0.893082,1,0.996835,0.987342,1,1,1,1,0.981132,0.996835,0.996835,0.984177,1,1,1,0.987421,1,1,0.996835,1,0.882911,1,0.990506,1,0.993711,0.996835,0.990506,1,0.990506,0.993671,0.962264,1,1,0.981013,1,1,0.993671,0.981013,1,0.987421,1,0.993671,1,0.996835,0.949686,0.943396,1,0.974684,1,0.981013,0.996835,1,0.993711,0.974843,1,1,0.962264,1,0.943396,1,1,1,0.990506,1,1,1,1,1,0.996835,1,1,1,1,1,1] 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 0.6273193841294907 kappa 0.6526270082501086 kappa 0.602162844851403 kappa 0.621002763521516 kappa 0.5704697986577181 kappa 0.5831688639772638 kappa 0.5703849950641658 kappa 0.5958001105234073 kappa 0.6210775606867969 kappa 0.6462273463102618 kb_relative_information_score 107.42756517769111 kb_relative_information_score 105.66768558473464 kb_relative_information_score 104.94349262872547 kb_relative_information_score 104.98681241353088 kb_relative_information_score 104.94905664831703 kb_relative_information_score 104.4294940856667 kb_relative_information_score 105.9352994892934 kb_relative_information_score 105.69863816171782 kb_relative_information_score 109.51584555297873 kb_relative_information_score 108.95787084980716 mean_absolute_error 0.014211683557835756 mean_absolute_error 0.014366467417656886 mean_absolute_error 0.014381396304161001 mean_absolute_error 0.014434069773226565 mean_absolute_error 0.014380852413692241 mean_absolute_error 0.014408351706251668 mean_absolute_error 0.014492507862076143 mean_absolute_error 0.014374115516569651 mean_absolute_error 0.014068411007691493 mean_absolute_error 0.014184052888062348 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 0.63125 predictive_accuracy 0.65625 predictive_accuracy 0.60625 predictive_accuracy 0.625 predictive_accuracy 0.575 predictive_accuracy 0.5875 predictive_accuracy 0.575 predictive_accuracy 0.6 predictive_accuracy 0.625 predictive_accuracy 0.65 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 0.63125 [1,1,1,1,0.5,0,1,1,1,1,0.5,0.5,0.5,0,1,1,1,0,0,0,1,0,1,1,1,0,0,1,0.5,0,0.5,1,0.5,0,1,0,0,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0.5,0.5,1,0,1,0,1,1,1,0.5,1,1,1,0,1,0.5,0.5,1,0,0,0,1,0.5,1,1,1,1,0.5,1,1,0.5,0.5,1,0,0.5,0.5,1,0.5,0,0,1,1,1,0.5,0.5,0.5,1,0.5,0,1] recall 0.65625 [1,1,1,1,1,1,0.5,1,0.5,1,0.5,1,1,0.5,1,1,1,0,0.5,0,1,0,0,1,1,0,0.5,0.5,0.5,1,0.5,1,1,0.5,1,1,0,1,0,1,1,1,1,1,0.5,0.5,1,0,0,1,0.5,0.5,1,0.5,1,0,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,0,0,0.5,1,0.5,1,1,1,1,0,0.5,1,0.5,0.5,0,0,1,1,0.5,0.5,0.5,1,1,1,0,0,0,1,1,0,0,1] recall 0.60625 [0,0.5,1,1,0.5,0,1,1,0,1,0,1,1,0.5,0,0.5,1,0.5,0,0,1,0,0,1,0,0.5,0.5,1,1,1,1,1,1,0,0,1,1,0,1,1,0,1,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0.5,1,0,1,1,1,0,1,0,0.5,1,0.5,0.5,0,1,0,0,0.5,1,0,0.5,0,1,1,0,0.5,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,0,0.5] recall 0.625 [1,1,1,1,0.5,0,1,1,0,0.5,1,0.5,1,0,1,1,1,0.5,0,0,0,1,0.5,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0,1,0,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0.5,1,1,1,0.5,1,1,1,1,0.5,0,0.5,1,0,0.5,0,0.5,1,1,0,0.5,1,0,1,1,0,0.5,1,0,1,1,1,1,0.5,1,1,1,0,0,0.5,0,0.5,0.5,0,0] recall 0.575 [0.5,1,1,1,1,0.5,0,1,1,1,0.5,0.5,1,0,1,0.5,1,1,1,0,0.5,0.5,1,1,1,0,0.5,1,1,1,1,1,0,0,1,1,0.5,0,0,1,1,1,0,1,1,0,1,0,0.5,0.5,0,0,0,0,0,0,1,0.5,1,0,1,1,1,0,0.5,0,0,1,0,0,0,1,1,0,0,1,0.5,0,1,1,0,1,0.5,0,0,1,1,1,1,1,1,1,0,0,0.5,1,0.5,1,0,0.5] recall 0.5875 [0,1,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,0,1,1,1,0.5,1,0,1,1,0.5,1,0.5,0,0.5,1,1,1,0,1,0.5,1,0,1,0.5,0.5,0,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,0,1,0,0,0,1,1,0,1,0.5,0.5,0,1,1,0.5,0,1,0,0.5,0,1,1,1,0,1,1,0,1,0,1,0,1,0.5,0,1,0,0,0,1,1,1,0,0,0,1,0.5,0,0,0.5] recall 0.575 [0.5,1,1,0.5,1,1,1,1,0,0.5,1,1,0.5,0,0,0.5,1,0,0.5,0,1,1,0.5,1,0.5,0,0,0.5,0,1,0.5,1,1,0,1,1,0,1,0.5,1,0,0,1,0,0,0.5,0.5,0.5,1,1,0,0.5,0.5,0,0.5,0,1,0.5,0.5,0,0,0.5,1,0.5,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,0.5,0,0,0.5,1,1,0.5,0,0,0.5,1,0,0,0.5] recall 0.6 [1,1,1,0.5,1,0,1,1,1,0.5,1,1,0.5,0,1,0.5,1,0,0.5,0,0.5,1,0.5,1,0.5,0,0,0.5,1,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,0,1,0.5,1,1,0,1,0,0.5,0.5,1,0.5,0,1,1,0.5,1,1,0.5,1,0.5,1,0,1,1,0,0,0,1,1,0,0,1,1,0,1,1,0,0,0,0.5,0,0.5,1,0,1,1,1,1,0,0,0,1,0.5,1,0,0.5] recall 0.625 [0,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0.5,1,0.5,0,0.5,1,0,0.5,1,0.5,0,0,1,0,0,1,1,0,1,0,0,0,1,1,0,0,1,1,0.5,0.5,1,1,0.5,1,0.5,0,0,0,0.5,1,0.5,0.5,1,0,1,0.5,1,1,1,0,0.5,1,1,0.5,0,1,1,0.5,0,0,0,0.5,0,0.5,0,1] recall 0.65 [0,0,1,1,1,0,0.5,0,1,1,1,1,1,0.5,1,0,1,0,0.5,1,1,1,1,1,0.5,0,1,0.5,0.5,1,1,1,1,0,1,1,0,1,0,1,0,1,0.5,0.5,1,0.5,1,0.5,1,1,1,0.5,1,0.5,0.5,0,1,1,0,0.5,1,0.5,0,1,1,1,0.5,1,0.5,0,0,0,0,1,0.5,1,1,0,0,1,1,0,1,0,0.5,1,1,0,0,0.5,1,1,1,0,1,1,1,1,0,0] relative_absolute_error 0.7177617958502895 relative_absolute_error 0.7255791625079223 relative_absolute_error 0.7263331466747968 relative_absolute_error 0.7289934228902294 relative_absolute_error 0.7263056774592029 relative_absolute_error 0.7276945306187699 relative_absolute_error 0.7319448415189959 relative_absolute_error 0.7259654301297792 relative_absolute_error 0.7105258084692662 relative_absolute_error 0.7163663074778952 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 0.07792283670661405 root_mean_squared_error 0.07865601033395633 root_mean_squared_error 0.07921052985996854 root_mean_squared_error 0.07928202557379886 root_mean_squared_error 0.07959924837253704 root_mean_squared_error 0.07987169211211748 root_mean_squared_error 0.0798195605303117 root_mean_squared_error 0.0791629974084321 root_mean_squared_error 0.07727671981478963 root_mean_squared_error 0.07817667415422094 root_relative_squared_error 0.7831539756241568 root_relative_squared_error 0.7905226478304543 root_relative_squared_error 0.7960957787598731 root_relative_squared_error 0.7968143377201574 root_relative_squared_error 0.8000025468060997 root_relative_squared_error 0.8027407094141894 root_relative_squared_error 0.8022167673033485 root_relative_squared_error 0.7956180596474123 root_relative_squared_error 0.7766602565305439 root_relative_squared_error 0.7857051379618948 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 7768.18901799993 usercpu_time_millis 7644.788379999909 usercpu_time_millis 7587.749871999904 usercpu_time_millis 7625.934673000074 usercpu_time_millis 7617.71815499992 usercpu_time_millis 7573.834026999975 usercpu_time_millis 7800.275536999834 usercpu_time_millis 7632.279012000026 usercpu_time_millis 7629.448329999832 usercpu_time_millis 7631.847273999824 usercpu_time_millis_testing 34.511930999997276 usercpu_time_millis_testing 34.347534999938034 usercpu_time_millis_testing 34.40701399995305 usercpu_time_millis_testing 34.444302999986576 usercpu_time_millis_testing 34.427364999942256 usercpu_time_millis_testing 34.70944399998643 usercpu_time_millis_testing 37.992213999928026 usercpu_time_millis_testing 34.96026499999516 usercpu_time_millis_testing 34.390406999932566 usercpu_time_millis_testing 34.581905999857554 usercpu_time_millis_training 7733.677086999933 usercpu_time_millis_training 7610.440844999971 usercpu_time_millis_training 7553.342857999951 usercpu_time_millis_training 7591.490370000088 usercpu_time_millis_training 7583.290789999978 usercpu_time_millis_training 7539.124582999989 usercpu_time_millis_training 7762.283322999906 usercpu_time_millis_training 7597.318747000031 usercpu_time_millis_training 7595.057922999899 usercpu_time_millis_training 7597.265367999967