10412235 1 Jan van Rijn 9954 Supervised Classification 16360 sklearn.svm.classes.SVC(32) 8249999 C 1472.8662881498958 16360 cache_size 200 16360 class_weight null 16360 coef0 -0.3150805847806095 16360 decision_function_shape "ovr" 16360 degree 3 16360 gamma 0.06620574278449574 16360 kernel "sigmoid" 16360 max_iter -1 16360 probability false 16360 random_state 44380 16360 shrinking false 16360 tol 0.004847036473626274 16360 verbose false 16360 openml-python Sklearn_0.21.2. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 21746263 description https://api.openml.org/data/download/21746263/description.xml -1 21746264 predictions https://api.openml.org/data/download/21746264/predictions.arff area_under_roc_curve 0.9081439393939397 [0.842487,0.96875,1,1,0.96875,0.874369,0.96875,0.999684,0.936237,0.96875,0.905619,0.999053,0.96875,0.780934,1,0.968434,1,0.684659,0.653093,0.649937,0.873737,0.96875,0.873737,1,0.937184,0.622159,0.714331,0.936553,0.9375,0.96875,0.999369,1,0.967803,0.81029,0.905619,0.967172,0.807765,0.684975,0.999369,0.999684,0.904672,0.968119,1,0.967803,0.96875,0.968119,0.96875,0.905934,0.934975,0.905934,0.874053,0.874684,0.937184,0.811869,0.904987,0.590909,1,0.999684,0.811553,0.904356,0.999053,0.999684,0.90404,0.968119,0.999684,0.810922,0.684659,0.999684,0.874369,0.903725,0.843119,0.905619,0.840909,0.937184,0.842803,0.96875,0.96875,0.717487,1,0.96875,0.90625,0.937184,0.905934,0.873422,0.905619,0.936869,0.999684,0.905934,0.937184,1,0.812184,0.967803,0.968119,0.905934,0.968119,0.936237,0.967487,0.935922,0.685922,0.905934] average_cost 0 f_measure 0.8185077814494732 [0.709677,0.967742,1,1,0.967742,0.8,0.967742,0.969697,0.823529,0.967742,0.83871,0.914286,0.967742,0.692308,1,0.9375,1,0.387097,0.322581,0.243902,0.75,0.967742,0.75,1,0.903226,0.275862,0.378378,0.848485,0.933333,0.967742,0.941176,1,0.882353,0.606061,0.83871,0.833333,0.487805,0.4,0.941176,0.969697,0.764706,0.909091,1,0.882353,0.967742,0.909091,0.967742,0.866667,0.736842,0.866667,0.774194,0.827586,0.903226,0.714286,0.787879,0.214286,1,0.969697,0.689655,0.742857,0.914286,0.969697,0.722222,0.909091,0.969697,0.645161,0.387097,0.969697,0.8,0.702703,0.758621,0.83871,0.611111,0.903226,0.733333,0.967742,0.967742,0.518519,1,0.967742,0.896552,0.903226,0.866667,0.727273,0.83871,0.875,0.969697,0.866667,0.903226,1,0.740741,0.882353,0.909091,0.866667,0.909091,0.823529,0.857143,0.8,0.444444,0.866667] kappa 0.8162878787878788 kb_relative_information_score 0.817728075508727 mean_absolute_error 0.0036374999999999776 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 0.8267095286464474 [0.733333,1,1,1,1,0.857143,1,0.941176,0.777778,1,0.866667,0.842105,1,0.9,1,0.9375,1,0.4,0.333333,0.2,0.75,1,0.75,1,0.933333,0.307692,0.333333,0.823529,1,1,0.888889,1,0.833333,0.588235,0.866667,0.75,0.4,0.428571,0.888889,0.941176,0.722222,0.882353,1,0.833333,1,0.882353,1,0.928571,0.636364,0.928571,0.8,0.923077,0.933333,0.833333,0.764706,0.25,1,0.941176,0.769231,0.684211,0.842105,0.941176,0.65,0.882353,0.941176,0.666667,0.4,0.941176,0.857143,0.619048,0.846154,0.866667,0.55,0.933333,0.785714,1,1,0.636364,1,1,1,0.933333,0.928571,0.705882,0.866667,0.875,0.941176,0.928571,0.933333,1,0.909091,0.833333,0.882353,0.928571,0.882353,0.777778,0.789474,0.736842,0.545455,0.928571] predictive_accuracy 0.818125 prior_entropy 6.643856189774611 recall 0.818125 [0.6875,0.9375,1,1,0.9375,0.75,0.9375,1,0.875,0.9375,0.8125,1,0.9375,0.5625,1,0.9375,1,0.375,0.3125,0.3125,0.75,0.9375,0.75,1,0.875,0.25,0.4375,0.875,0.875,0.9375,1,1,0.9375,0.625,0.8125,0.9375,0.625,0.375,1,1,0.8125,0.9375,1,0.9375,0.9375,0.9375,0.9375,0.8125,0.875,0.8125,0.75,0.75,0.875,0.625,0.8125,0.1875,1,1,0.625,0.8125,1,1,0.8125,0.9375,1,0.625,0.375,1,0.75,0.8125,0.6875,0.8125,0.6875,0.875,0.6875,0.9375,0.9375,0.4375,1,0.9375,0.8125,0.875,0.8125,0.75,0.8125,0.875,1,0.8125,0.875,1,0.625,0.9375,0.9375,0.8125,0.9375,0.875,0.9375,0.875,0.375,0.8125] relative_absolute_error 0.18371212121211972 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.06031169040907391 root_relative_squared_error 0.6061552956332555 total_cost 0 area_under_roc_curve 0.9054016399968156 [0.993711,0.75,1,1,1,1,1,1,1,1,0.75,1,1,0.5,1,1,1,0.5,0.496835,0.987421,0.996855,1,1,1,1,0.746835,0.75,0.996835,1,0.5,1,1,0.746835,0.496835,0.75,0.996855,0.996855,0.996855,1,1,1,1,1,1,1,1,1,0.996855,1,0.75,1,1,1,0.75,0.996855,0.496855,1,1,1,1,1,0.996855,1,1,1,0.996835,0.5,1,1,0.496855,0.75,1,0.996835,1,0.996855,1,0.75,0.75,1,1,1,1,1,1,1,0.75,1,1,0.75,1,0.746835,1,1,0.75,1,0.743671,0.996855,0.993671,0.746835,1] area_under_roc_curve 0.921085104689117 [1,1,1,1,1,1,0.75,1,1,1,0.75,1,1,0.75,1,1,1,0.746835,0.75,0.496855,1,1,0.996855,1,1,0.496835,0.496835,1,1,1,1,1,1,1,1,0.996855,0.996855,0.496855,0.996855,1,1,1,1,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,0.493711,1,1,1,0.75,1,1,0.996835,1,1,0.75,0.996835,1,0.5,1,0.746835,1,0.75,0.75,1,1,1,0.990506,1,0.75,0.75,1,0.996855,1,0.746835,1,1,1,0.75,1,0.75,1,1,1,0.996835,1,1,0.996835,0.746835,0.496855] area_under_roc_curve 0.9179205477270915 [1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.75,1,1,1,0.743671,1,0.493671,0.5,1,0.75,1,1,0.743671,0.746835,1,1,1,1,1,1,0.5,0.996855,0.996855,0.990566,0.5,1,1,0.5,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,0.75,1,1,1,0.746835,1,1,0.75,0.5,1,1,0.493671,1,0.996855,0.75,0.746835,0.996835,0.996855,0.996835,1,1,1,0.496835,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.996855,1,1,0.996835,1,1,0.75,0.496855,1] area_under_roc_curve 0.8896186609346388 [0.5,1,1,1,0.75,0.75,1,1,0.746835,1,1,1,1,0.75,1,1,1,0.746835,0.493711,0.496835,0.5,1,0.993671,1,0.5,0.75,0.740506,1,1,1,1,1,1,0.75,0.996855,0.996855,0.993711,0.493711,1,1,0.996835,0.993711,1,1,1,1,1,1,0.996835,1,1,1,0.996855,0.5,1,0.496835,1,1,0.996855,1,0.996855,1,0.996835,1,1,0.5,0.746835,1,1,0.993671,0.5,0.75,0.490566,0.75,1,1,1,0.75,1,1,1,1,0.75,0.75,1,1,1,1,1,1,0.75,1,0.996855,1,1,0.996855,0.75,0.996835,0.496855,0.75] area_under_roc_curve 0.8957487461189393 [0.75,1,1,1,1,1,1,1,1,1,1,1,0.5,0.496855,1,0.996835,1,0.496835,0.996855,0.740506,0.996835,1,0.5,1,1,0.746835,0.743671,1,1,1,0.996855,1,1,0.746835,1,1,0.746835,0.746835,1,1,0.993671,1,1,0.5,1,1,1,1,1,1,0.493711,0.496855,0.75,0.496855,0.743671,0.496835,1,0.996835,0.5,1,1,1,1,1,1,1,0.496855,1,0.75,0.743671,1,1,1,1,0.75,1,1,0.75,1,1,1,1,0.75,0.993671,0.996855,1,1,1,1,1,1,0.75,1,0.5,0.75,1,0.993671,1,0.5,1] area_under_roc_curve 0.8957686489929143 [0.75,1,1,1,1,0.75,1,1,0.996855,0.75,0.75,0.996835,1,1,1,1,1,0.743671,0.496855,0.743671,1,0.75,0.996835,1,0.996835,0.490506,0.743671,0.5,1,1,1,1,0.996835,0.996835,1,0.75,0.75,0.496835,1,1,0.996835,1,1,0.996855,1,1,1,0.75,0.746835,0.75,1,1,1,1,0.996835,0.496835,1,1,0.75,0.996855,1,1,0.493711,1,1,0.75,0.996855,1,1,1,1,0.746835,1,1,0.75,1,1,0.75,1,1,0.5,0.75,1,0.996835,0.5,1,1,0.996855,0.996835,1,0.5,0.996835,1,1,1,1,1,0.996855,0.496855,0.75] area_under_roc_curve 0.8989929145768649 [0.996835,1,1,1,1,0.5,1,1,0.993711,1,0.996855,0.996855,1,1,1,0.75,1,1,0.490506,0.5,0.746835,1,1,1,1,0.5,0.487421,0.746835,1,1,0.996835,1,1,0.993711,1,1,0.493671,0.746835,0.996835,1,0.996835,0.75,1,1,0.5,0.75,0.75,0.75,0.996855,1,0.5,1,1,1,0.75,0.5,1,1,0.5,0.996855,0.993671,1,0.996855,0.996835,1,0.5,0.5,1,1,1,1,1,0.996835,1,0.996835,1,1,0.5,1,1,1,1,1,0.996835,1,1,1,0.5,1,1,1,1,0.746835,1,1,1,1,1,0.5,1] area_under_roc_curve 0.9116511424249658 [0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.743671,0.496835,0.746835,1,0.75,1,0.75,0.496855,0.996855,0.996835,0.5,1,1,1,0.996855,1,0.75,1,0.993671,0.75,1,0.996855,1,1,1,1,1,0.996835,1,0.75,0.993711,0.5,0.496855,0.75,0.75,0.996855,1,0.743671,1,1,0.996835,0.993711,1,1,1,1,1,0.490566,0.5,1,1,0.996835,1,1,0.996835,1,0.996835,1,1,0.5,1,1,0.75,1,0.75,0.75,0.75,0.75,1,0.5,1,1,0.5,1,1,1,1,0.996835,1,1,0.75,1] area_under_roc_curve 0.9337234296632433 [0.996855,1,1,1,1,0.996855,1,1,0.75,1,1,0.996855,1,1,1,1,1,0.496855,0.75,0.990566,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.996855,1,1,0.743671,0.496835,1,1,0.5,1,1,1,1,0.996835,1,1,0.996855,1,1,0.75,1,0.75,0.75,0.5,1,1,0.996835,1,1,1,0.996835,0.996835,1,1,0.993671,1,0.746835,1,1,0.5,0.746835,1,0.75,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.75,1,1,0.996835,1,0.75,1,1,0.75,1] area_under_roc_curve 0.9117506567948412 [1,1,1,1,1,1,1,0.996855,1,1,0.996855,1,1,0.75,1,1,1,0.496855,0.5,0.990566,1,1,1,1,1,0.5,0.5,1,0.75,1,1,1,1,0.996855,0.75,0.996835,0.746835,1,1,1,1,1,1,0.996835,1,1,1,1,0.996855,0.996855,0.75,0.75,1,0.75,1,0.996855,1,1,0.75,0.746835,1,1,0.746835,1,0.996855,0.996855,0.496835,0.996855,0.75,0.993711,1,1,0.496835,1,0.5,0.75,1,1,1,1,1,0.496855,1,0.496855,1,0.996835,0.996835,0.75,1,1,1,0.996835,1,0.75,1,1,0.996855,0.75,1,1] 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 0.8105313018078472 kappa 0.8420533070088845 kappa 0.8357419252941641 kappa 0.7789444597955236 kappa 0.7914691943127962 kappa 0.7914938988271532 kappa 0.7978282329713722 kappa 0.8230927183699257 kappa 0.8673090593160098 kappa 0.8231555678364189 kb_relative_information_score 0.8120907994935211 kb_relative_information_score 0.8434089995779346 kb_relative_information_score 0.8371453595610518 kb_relative_information_score 0.7807725994091079 kb_relative_information_score 0.7932998794428733 kb_relative_information_score 0.7932998794428733 kb_relative_information_score 0.7995635194597558 kb_relative_information_score 0.8246180795272865 kb_relative_information_score 0.8684635596454652 kb_relative_information_score 0.8246180795272865 mean_absolute_error 0.003750000000000001 mean_absolute_error 0.0031250000000000006 mean_absolute_error 0.0032500000000000007 mean_absolute_error 0.004375000000000002 mean_absolute_error 0.004125000000000002 mean_absolute_error 0.004125000000000002 mean_absolute_error 0.004000000000000002 mean_absolute_error 0.003500000000000001 mean_absolute_error 0.0026250000000000006 mean_absolute_error 0.003500000000000001 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 0.8125 predictive_accuracy 0.84375 predictive_accuracy 0.8375 predictive_accuracy 0.78125 predictive_accuracy 0.79375 predictive_accuracy 0.79375 predictive_accuracy 0.8 predictive_accuracy 0.825 predictive_accuracy 0.86875 predictive_accuracy 0.825 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 0.8125 [1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0,1,1,1,1,1,1,0.5,0.5,1,1,0,1,1,0.5,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1] recall 0.84375 [1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,0] recall 0.8375 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0,0,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,0,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1] recall 0.78125 [0,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0,0,1,1,1,0,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0,0.5,0,0.5,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,0.5] recall 0.79375 [0.5,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,1,0.5,1,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0.5,0,0.5,0,1,1,0,1,1,1,1,1,1,1,0,1,0.5,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,0,1] recall 0.79375 [0.5,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,1,1,0,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,0,1,1,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0.5] recall 0.8 [1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0,0.5,1,1,1,1,0,0,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0.5,0.5,0.5,1,1,0,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.825 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,0.5,0.5,0.5,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1] recall 0.86875 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1] recall 0.825 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,0,1,0.5,1,1,1,0,1,0,0.5,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,1] relative_absolute_error 0.18939393939393911 relative_absolute_error 0.1578282828282826 relative_absolute_error 0.1641414141414139 relative_absolute_error 0.2209595959595957 relative_absolute_error 0.20833333333333307 relative_absolute_error 0.20833333333333307 relative_absolute_error 0.2020202020202018 relative_absolute_error 0.17676767676767655 relative_absolute_error 0.13257575757575737 relative_absolute_error 0.17676767676767655 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 0.061237243569579464 root_mean_squared_error 0.05590169943749475 root_mean_squared_error 0.0570087712549569 root_mean_squared_error 0.06614378277661478 root_mean_squared_error 0.06422616289332567 root_mean_squared_error 0.06422616289332567 root_mean_squared_error 0.0632455532033676 root_mean_squared_error 0.05916079783099617 root_mean_squared_error 0.051234753829797995 root_mean_squared_error 0.05916079783099617 root_relative_squared_error 0.6154574548966634 root_relative_squared_error 0.5618332187193681 root_relative_squared_error 0.5729597091269403 root_relative_squared_error 0.6647700293478879 root_relative_squared_error 0.6454972243679026 root_relative_squared_error 0.6454972243679026 root_relative_squared_error 0.6356417261637279 root_relative_squared_error 0.5945883900105629 root_relative_squared_error 0.5149286505444369 root_relative_squared_error 0.5945883900105629 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 316.9303970000783 usercpu_time_millis 319.55009599982986 usercpu_time_millis 320.73728499995013 usercpu_time_millis 329.9005110000053 usercpu_time_millis 321.4047080000455 usercpu_time_millis 320.33525800011375 usercpu_time_millis 320.32619800020257 usercpu_time_millis 327.1978980001222 usercpu_time_millis 327.81223599999976 usercpu_time_millis 324.2858939997859 usercpu_time_millis_testing 62.75619500001994 usercpu_time_millis_testing 63.564482999936445 usercpu_time_millis_testing 63.083825999910914 usercpu_time_millis_testing 64.35807499997281 usercpu_time_millis_testing 63.12459400010084 usercpu_time_millis_testing 62.91120200012301 usercpu_time_millis_testing 63.53934000003392 usercpu_time_millis_testing 64.43978600009359 usercpu_time_millis_testing 63.24668299998848 usercpu_time_millis_testing 63.06385599987152 usercpu_time_millis_training 254.17420200005836 usercpu_time_millis_training 255.98561299989342 usercpu_time_millis_training 257.6534590000392 usercpu_time_millis_training 265.54243600003247 usercpu_time_millis_training 258.28011399994466 usercpu_time_millis_training 257.42405599999074 usercpu_time_millis_training 256.78685800016865 usercpu_time_millis_training 262.75811200002863 usercpu_time_millis_training 264.5655530000113 usercpu_time_millis_training 261.2220379999144 wall_clock_time_millis 316.91932678222656 wall_clock_time_millis 319.5490837097168 wall_clock_time_millis 320.7263946533203 wall_clock_time_millis 329.95128631591797 wall_clock_time_millis 321.40445709228516 wall_clock_time_millis 320.3318119049072 wall_clock_time_millis 320.3110694885254 wall_clock_time_millis 327.2106647491455 wall_clock_time_millis 327.8036117553711 wall_clock_time_millis 324.293851852417 wall_clock_time_millis_testing 62.7591609954834 wall_clock_time_millis_testing 63.567161560058594 wall_clock_time_millis_testing 63.086748123168945 wall_clock_time_millis_testing 64.37349319458008 wall_clock_time_millis_testing 63.12704086303711 wall_clock_time_millis_testing 62.912940979003906 wall_clock_time_millis_testing 63.54022026062012 wall_clock_time_millis_testing 64.44430351257324 wall_clock_time_millis_testing 63.251495361328125 wall_clock_time_millis_testing 63.08746337890625 wall_clock_time_millis_training 254.16016578674316 wall_clock_time_millis_training 255.9819221496582 wall_clock_time_millis_training 257.63964653015137 wall_clock_time_millis_training 265.5777931213379 wall_clock_time_millis_training 258.27741622924805 wall_clock_time_millis_training 257.4188709259033 wall_clock_time_millis_training 256.7708492279053 wall_clock_time_millis_training 262.76636123657227 wall_clock_time_millis_training 264.55211639404297 wall_clock_time_millis_training 261.20638847351074