10413445 1 Jan van Rijn 9954 Supervised Classification 16360 sklearn.svm.classes.SVC(32) 8251189 C 13257.403304167956 16360 cache_size 200 16360 class_weight null 16360 coef0 -0.609628306536486 16360 decision_function_shape "ovr" 16360 degree 3 16360 gamma 0.859964143916746 16360 kernel "sigmoid" 16360 max_iter -1 16360 probability false 16360 random_state 34665 16360 shrinking false 16360 tol 1.6626046731423483e-05 16360 verbose false 16360 openml-python Sklearn_0.21.2. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 21748699 description https://api.openml.org/data/download/21748699/description.xml -1 21748700 predictions https://api.openml.org/data/download/21748700/predictions.arff area_under_roc_curve 0.915088383838384 [0.904672,0.96875,1,1,1,0.936237,0.999684,0.999684,0.905619,0.96875,0.967803,0.999684,0.968434,0.8125,1,0.968434,0.999684,0.809659,0.652778,0.650884,0.874369,0.96875,0.904672,1,0.936869,0.714646,0.715593,0.935922,0.968434,1,0.999684,1,0.999369,0.746843,0.999369,0.936237,0.748422,0.748422,0.999369,1,0.935606,0.999684,0.999684,0.968434,1,0.96875,0.937184,0.874369,0.90404,0.90625,0.968119,0.905934,0.937184,0.842803,0.873737,0.74779,1,0.999684,0.902462,0.873737,0.936869,1,0.841856,0.937184,0.999684,0.841856,0.748106,0.999684,0.842803,0.904987,0.874369,0.905619,0.746528,0.96875,0.905619,0.96875,0.968434,0.716856,1,0.96875,0.875,0.90625,0.936869,0.749369,0.905934,1,0.999684,0.936553,0.937184,0.96875,0.874684,0.967803,0.937184,0.937184,0.96875,0.936237,0.905619,0.905303,0.653409,0.874684] average_cost 0 f_measure 0.833236927198149 [0.764706,0.967742,1,1,1,0.823529,0.969697,0.969697,0.83871,0.967742,0.882353,0.969697,0.9375,0.769231,1,0.9375,0.969697,0.571429,0.3125,0.263158,0.8,0.967742,0.764706,1,0.875,0.388889,0.424242,0.8,0.9375,1,0.969697,1,0.941176,0.470588,0.941176,0.823529,0.551724,0.551724,0.941176,1,0.777778,0.969697,0.969697,0.9375,1,0.967742,0.903226,0.8,0.722222,0.896552,0.909091,0.866667,0.903226,0.733333,0.75,0.516129,1,0.969697,0.634146,0.75,0.875,1,0.666667,0.903226,0.969697,0.666667,0.533333,0.969697,0.733333,0.787879,0.8,0.83871,0.457143,0.967742,0.83871,0.967742,0.9375,0.482759,1,0.967742,0.857143,0.896552,0.875,0.615385,0.866667,1,0.969697,0.848485,0.903226,0.967742,0.827586,0.882353,0.903226,0.903226,0.967742,0.823529,0.83871,0.8125,0.333333,0.827586] kappa 0.8301767676767677 kb_relative_information_score 0.8315080835458679 mean_absolute_error 0.003362499999999983 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 0.8409790661780596 [0.722222,1,1,1,1,0.777778,0.941176,0.941176,0.866667,1,0.833333,0.941176,0.9375,1,1,0.9375,0.941176,0.526316,0.3125,0.227273,0.857143,1,0.722222,1,0.875,0.35,0.411765,0.736842,0.9375,1,0.941176,1,0.888889,0.444444,0.888889,0.777778,0.615385,0.615385,0.888889,1,0.7,0.941176,0.941176,0.9375,1,1,0.933333,0.857143,0.65,1,0.882353,0.928571,0.933333,0.785714,0.75,0.533333,1,0.941176,0.52,0.75,0.875,1,0.647059,0.933333,0.941176,0.647059,0.571429,0.941176,0.785714,0.764706,0.857143,0.866667,0.421053,1,0.866667,1,0.9375,0.538462,1,1,1,1,0.875,0.8,0.928571,1,0.941176,0.823529,0.933333,1,0.923077,0.833333,0.933333,0.933333,1,0.777778,0.866667,0.8125,0.357143,0.923077] predictive_accuracy 0.831875 prior_entropy 6.643856189774611 recall 0.831875 [0.8125,0.9375,1,1,1,0.875,1,1,0.8125,0.9375,0.9375,1,0.9375,0.625,1,0.9375,1,0.625,0.3125,0.3125,0.75,0.9375,0.8125,1,0.875,0.4375,0.4375,0.875,0.9375,1,1,1,1,0.5,1,0.875,0.5,0.5,1,1,0.875,1,1,0.9375,1,0.9375,0.875,0.75,0.8125,0.8125,0.9375,0.8125,0.875,0.6875,0.75,0.5,1,1,0.8125,0.75,0.875,1,0.6875,0.875,1,0.6875,0.5,1,0.6875,0.8125,0.75,0.8125,0.5,0.9375,0.8125,0.9375,0.9375,0.4375,1,0.9375,0.75,0.8125,0.875,0.5,0.8125,1,1,0.875,0.875,0.9375,0.75,0.9375,0.875,0.875,0.9375,0.875,0.8125,0.8125,0.3125,0.75] relative_absolute_error 0.16982323232323118 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.057987067523715866 root_relative_squared_error 0.5827919565732375 total_cost 0 area_under_roc_curve 0.9243093702730674 [0.993711,0.75,1,1,1,1,1,1,1,1,0.75,1,1,0.75,1,1,1,0.746835,0.743671,0.996855,0.496855,1,0.996855,1,0.996855,0.75,0.75,0.996835,1,1,1,1,1,0.496835,1,0.996855,1,0.996855,1,1,0.996855,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,0.75,0.996855,0.496855,1,1,1,1,1,1,1,1,1,1,0.75,1,1,0.496855,0.75,1,0.746835,1,1,1,0.75,0.496835,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,0.746835,1,0.993671,0.496835,1] area_under_roc_curve 0.9179205477270915 [1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.75,1,1,1,0.75,0.75,0.490566,1,1,0.996855,1,1,0.746835,0.496835,1,1,1,1,1,1,0.996835,1,0.496855,0.996855,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.75,1,0.496855,1,1,0.996855,1,0.5,1,0.996835,1,1,0.746835,0.746835,1,0.5,1,0.993671,1,0.496835,1,1,1,1,0.993671,1,0.75,0.75,1,0.993711,0.5,0.746835,1,1,0.996835,0.75,1,0.75,1,0.75,0.75,1,1,1,1,0.746835,0.5] area_under_roc_curve 0.9243093702730671 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[0.75,1,1,1,1,0.996835,1,1,0.5,1,1,1,0.5,0.5,1,0.996835,1,0.746835,0.990566,0.740506,0.75,1,0.75,1,1,0.987342,0.746835,1,0.996855,1,0.996855,1,1,0.496835,1,1,0.5,0.75,1,1,0.993671,1,1,0.5,1,1,1,0.75,1,1,0.496855,0.996855,0.75,0.993711,0.496835,0.5,1,0.996835,0.990506,1,1,1,0.5,0.5,1,1,0.5,1,0.5,0.996835,1,1,1,1,0.75,1,0.996835,0.75,1,1,1,0.75,1,0.75,1,1,1,1,1,1,1,1,1,1,0.75,0.996855,0.996835,1,0.496855,1] area_under_roc_curve 0.9115118223071409 [0.75,1,1,1,1,1,1,1,1,0.75,1,0.996835,1,1,1,1,1,0.993671,0.5,0.75,1,0.75,0.996835,1,0.996835,0.993671,0.740506,0.5,1,1,1,1,0.996835,0.746835,1,0.746835,0.75,0.746835,1,1,0.75,1,1,0.996855,1,1,0.996835,0.75,0.746835,0.75,1,1,1,1,0.996835,0.75,1,1,0.75,0.996855,1,1,0.493711,1,1,0.75,1,1,1,1,1,0.746835,1,1,0.75,1,1,0.996835,1,1,0.5,0.75,1,0.996835,0.5,1,1,0.996855,0.996835,0.75,0.5,0.996835,1,1,1,1,1,1,0.496855,0.75] area_under_roc_curve 0.9021176657909402 [0.996835,1,1,1,1,0.75,1,1,0.996855,1,0.996855,1,1,1,1,0.75,1,0.996855,0.493671,0.490506,0.996835,1,0.996835,1,1,0.5,0.493711,0.746835,1,1,1,1,1,0.996855,1,1,0.5,0.75,0.993671,1,0.993671,1,1,1,1,0.75,0.5,0.746835,0.996855,1,1,1,1,1,0.75,0.746835,1,1,0.5,0.496855,0.996835,1,0.996855,0.996835,1,0.496855,0.5,1,1,1,1,1,0.746835,1,0.996835,1,1,0.496855,1,1,0.75,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.75,1,1,0.75,1,1,0.5,1] area_under_roc_curve 0.9336836239152934 [0.75,1,1,1,1,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,0.740506,0.5,0.75,1,1,1,0.75,0.496855,0.996855,0.996835,1,1,1,1,0.996855,1,1,1,0.496835,0.746835,1,1,1,1,1,1,1,1,1,0.75,0.996855,1,0.996855,0.75,0.75,0.996855,0.996835,0.993671,1,1,0.996835,1,1,1,1,1,1,0.996855,0.5,1,1,1,1,1,0.996835,1,1,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,1,1,1,1,1,1,0.75,1,1,1,0.996835,0.75,1,1,1] area_under_roc_curve 0.930598678449168 [0.996855,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.496855,0.75,0.990566,1,1,0.5,1,1,0.496855,0.496855,1,1,1,1,1,1,0.996855,1,1,1,0.496835,1,1,1,1,1,1,1,1,1,1,0.496855,1,1,0.75,0.996835,0.75,0.75,0.5,1,1,0.993671,1,1,1,0.75,1,1,0.996855,0.993671,1,0.746835,1,1,0.496855,0.493671,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.996835,1,1,0.75,1,1,0.996835,1,1,0.5,1,0.75,1] area_under_roc_curve 0.9086060027067908 [1,1,1,1,1,0.996855,1,0.996855,0.75,1,0.993711,1,1,0.75,1,1,1,0.496855,0.5,0.993711,1,1,1,1,1,0.493711,0.5,0.996835,0.75,1,1,1,1,0.993711,1,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,0.996855,1,1,0.75,1,0.75,1,1,1,1,0.993671,0.746835,0.75,1,0.496835,1,0.996855,0.996855,0.5,0.996855,0.75,0.993711,1,1,0.496835,1,0.75,0.75,1,1,1,1,1,0.5,1,0.5,1,1,0.996835,0.75,1,1,0.996835,0.996835,1,0.75,1,1,0.996855,0.5,0.75,0.996855] 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 f_measure 0.8452083333333332 [0.5,0.666667,1,1,1,1,1,1,1,1,0.666667,1,1,0.666667,1,1,1,0.5,0.4,0.666667,0,1,0.666667,1,0.666667,0.666667,0.666667,0.8,1,1,1,1,1,0,1,0.666667,1,0.666667,1,1,0.666667,1,1,1,1,1,1,0.666667,1,0.666667,1,1,1,0.666667,0.666667,0,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,0,0.666667,1,0.5,1,1,1,0.666667,0,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,0.5,1,0.666667,0,1] kappa 0.8484011054086064 kappa 0.8357224657426056 kappa 0.848389134554643 kappa 0.8042002210642666 kappa 0.7914856646394439 kappa 0.8230577826928394 kappa 0.8041383667667036 kappa 0.8673195387774444 kappa 0.8609849532009005 kappa 0.8168469250809189 kb_relative_information_score 0.8496726395948171 kb_relative_information_score 0.8371453595610518 kb_relative_information_score 0.8496726395948171 kb_relative_information_score 0.8058271594766385 kb_relative_information_score 0.7932998794428733 kb_relative_information_score 0.8246180795272865 kb_relative_information_score 0.8058271594766385 kb_relative_information_score 0.8684635596454652 kb_relative_information_score 0.8621999196285823 kb_relative_information_score 0.8183544395104039 mean_absolute_error 0.003000000000000001 mean_absolute_error 0.0032500000000000007 mean_absolute_error 0.003000000000000001 mean_absolute_error 0.0038750000000000013 mean_absolute_error 0.004125000000000002 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.0038750000000000013 mean_absolute_error 0.0026250000000000006 mean_absolute_error 0.0027500000000000007 mean_absolute_error 0.003625000000000001 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] precision 0.8770833333333334 [0.333333,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.333333,0.5,0,1,0.5,1,0.5,1,1,0.666667,1,1,1,1,1,0,1,0.5,1,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0,1] predictive_accuracy 0.85 predictive_accuracy 0.8375 predictive_accuracy 0.85 predictive_accuracy 0.80625 predictive_accuracy 0.79375 predictive_accuracy 0.825 predictive_accuracy 0.80625 predictive_accuracy 0.86875 predictive_accuracy 0.8625 predictive_accuracy 0.81875 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 prior_entropy 6.643856189774732 recall 0.85 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,0,1] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,0,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,0,0.5,1,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,1,0.5,0] recall 0.85 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,0,0,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1] recall 0.80625 [1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0,0,1,1,1,1,0,0,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,0.5,0,0.5,1,0.5,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0] recall 0.79375 [0.5,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,0.5,1,0.5,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0,1,1,1,0.5,1,1,0,1,0.5,1,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1] recall 0.825 [0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,1,0.5,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0,1,1,1,1,0.5,0,1,1,1,1,1,1,1,0,0.5] recall 0.80625 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,1,1,1,0.5,0.5,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0.5,1,1,0,1] recall 0.86875 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1] recall 0.8625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0,0,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1] recall 0.81875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,1,0.5,1,1,1,0,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0.5,1] relative_absolute_error 0.1515151515151513 relative_absolute_error 0.1641414141414139 relative_absolute_error 0.1515151515151513 relative_absolute_error 0.19570707070707044 relative_absolute_error 0.20833333333333307 relative_absolute_error 0.17676767676767655 relative_absolute_error 0.19570707070707044 relative_absolute_error 0.13257575757575737 relative_absolute_error 0.1388888888888887 relative_absolute_error 0.18308080808080782 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 0.05477225575051662 root_mean_squared_error 0.0570087712549569 root_mean_squared_error 0.05477225575051662 root_mean_squared_error 0.06224949798994367 root_mean_squared_error 0.06422616289332567 root_mean_squared_error 0.05916079783099617 root_mean_squared_error 0.06224949798994367 root_mean_squared_error 0.051234753829797995 root_mean_squared_error 0.052440442408507586 root_mean_squared_error 0.06020797289396149 root_relative_squared_error 0.5504818825631801 root_relative_squared_error 0.5729597091269403 root_relative_squared_error 0.5504818825631801 root_relative_squared_error 0.6256309946079566 root_relative_squared_error 0.6454972243679026 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.6256309946079566 root_relative_squared_error 0.5149286505444369 root_relative_squared_error 0.5270462766947296 root_relative_squared_error 0.6051128953853288 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 365.39689700001077 usercpu_time_millis 367.15700999998546 usercpu_time_millis 368.1357789999993 usercpu_time_millis 369.7455580000053 usercpu_time_millis 365.71656899999994 usercpu_time_millis 367.6683550000064 usercpu_time_millis 367.44812099999535 usercpu_time_millis 369.88691799999174 usercpu_time_millis 371.67679099999873 usercpu_time_millis 368.21629900001085 usercpu_time_millis_testing 64.54308200000014 usercpu_time_millis_testing 64.63125399999115 usercpu_time_millis_testing 63.83455900000001 usercpu_time_millis_testing 64.4624279999988 usercpu_time_millis_testing 64.22609999999906 usercpu_time_millis_testing 64.34046300000773 usercpu_time_millis_testing 65.09633899999301 usercpu_time_millis_testing 64.3173299999944 usercpu_time_millis_testing 64.73820099999728 usercpu_time_millis_testing 63.72306100000458 usercpu_time_millis_training 300.8538150000106 usercpu_time_millis_training 302.5257559999943 usercpu_time_millis_training 304.30121999999926 usercpu_time_millis_training 305.2831300000065 usercpu_time_millis_training 301.49046900000087 usercpu_time_millis_training 303.32789199999866 usercpu_time_millis_training 302.35178200000234 usercpu_time_millis_training 305.56958799999734 usercpu_time_millis_training 306.93859000000145 usercpu_time_millis_training 304.4932380000063 wall_clock_time_millis 365.4181957244873 wall_clock_time_millis 367.17915534973145 wall_clock_time_millis 368.15619468688965 wall_clock_time_millis 369.77529525756836 wall_clock_time_millis 365.74578285217285 wall_clock_time_millis 367.6900863647461 wall_clock_time_millis 367.46668815612793 wall_clock_time_millis 369.9157238006592 wall_clock_time_millis 371.69909477233887 wall_clock_time_millis 368.2563304901123 wall_clock_time_millis_testing 64.55135345458984 wall_clock_time_millis_testing 64.63932991027832 wall_clock_time_millis_testing 63.841819763183594 wall_clock_time_millis_testing 64.47076797485352 wall_clock_time_millis_testing 64.23473358154297 wall_clock_time_millis_testing 64.34869766235352 wall_clock_time_millis_testing 65.10400772094727 wall_clock_time_millis_testing 64.32580947875977 wall_clock_time_millis_testing 64.74781036376953 wall_clock_time_millis_testing 63.73167037963867 wall_clock_time_millis_training 300.86684226989746 wall_clock_time_millis_training 302.5398254394531 wall_clock_time_millis_training 304.31437492370605 wall_clock_time_millis_training 305.30452728271484 wall_clock_time_millis_training 301.5110492706299 wall_clock_time_millis_training 303.3413887023926 wall_clock_time_millis_training 302.36268043518066 wall_clock_time_millis_training 305.5899143218994 wall_clock_time_millis_training 306.95128440856934 wall_clock_time_millis_training 304.52466011047363