10408806 1 Jan van Rijn 9954 Supervised Classification 16360 sklearn.svm.classes.SVC(32) 8246572 C 59.87279268674813 16360 cache_size 200 16360 class_weight null 16360 coef0 0.0 16360 decision_function_shape "ovr" 16360 degree 3 16360 gamma 0.0988888211054266 16360 kernel "rbf" 16360 max_iter -1 16360 probability false 16360 random_state 37692 16360 shrinking false 16360 tol 0.00017914430736309405 16360 verbose false 16360 openml-python Sklearn_0.21.2. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 21739400 description https://api.openml.org/data/download/21739400/description.xml -1 21739401 predictions https://api.openml.org/data/download/21739401/predictions.arff area_under_roc_curve 0.7730429292929302 [0.652778,0.650884,0.999684,1,0.842487,0.683396,0.905619,0.935606,0.68529,0.90625,0.717487,0.748106,0.622475,0.562184,1,0.717487,0.9375,0.522727,0.583965,0.557765,0.593119,0.90625,0.684659,1,0.779987,0.498106,0.589646,0.841856,0.873106,0.90625,0.936869,0.96875,0.748422,0.745896,0.650884,0.872475,0.619003,0.556187,0.90404,0.968434,0.809028,0.903725,0.967803,0.839962,0.84375,0.810606,0.873106,0.653093,0.778409,0.84154,0.74779,0.778725,0.809975,0.717487,0.746528,0.558081,0.999684,0.968434,0.684975,0.684659,0.935606,0.842803,0.903093,0.811237,0.935606,0.559343,0.555556,1,0.653725,0.683081,0.686869,0.780934,0.714646,0.810922,0.558712,0.812184,0.811237,0.621528,0.999684,0.937184,0.624369,0.874684,0.778725,0.777778,0.653725,0.874684,1,0.559975,0.905303,0.619318,0.592172,0.967172,0.686237,0.620265,0.933712,0.748422,0.616793,0.560922,0.498422,0.904672] average_cost 0 f_measure 0.5509569922305428 [0.3125,0.263158,0.969697,1,0.709677,0.342857,0.83871,0.777778,0.413793,0.896552,0.518519,0.533333,0.285714,0.210526,1,0.518519,0.933333,0.045455,0.12,0.121212,0.285714,0.896552,0.387097,1,0.62069,0,0.1875,0.666667,0.705882,0.896552,0.875,0.967742,0.551724,0.432432,0.263158,0.666667,0.205128,0.105263,0.722222,0.9375,0.540541,0.702703,0.882353,0.564103,0.814815,0.625,0.705882,0.322581,0.529412,0.647059,0.516129,0.545455,0.588235,0.518519,0.457143,0.125,0.969697,0.9375,0.4,0.387097,0.777778,0.733333,0.666667,0.666667,0.777778,0.142857,0.1,1,0.344828,0.333333,0.5,0.692308,0.388889,0.645161,0.133333,0.740741,0.666667,0.258065,0.969697,0.903226,0.363636,0.827586,0.545455,0.5,0.344828,0.827586,1,0.153846,0.8125,0.210526,0.25,0.833333,0.461538,0.228571,0.666667,0.551724,0.173913,0.173913,0,0.764706] kappa 0.5460858585858586 kb_relative_information_score 0.549644282786144 mean_absolute_error 0.008987499999999864 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 0.573151207206144 [0.3125,0.227273,0.941176,1,0.733333,0.315789,0.866667,0.7,0.461538,1,0.636364,0.571429,0.333333,0.666667,1,0.636364,1,0.035714,0.088235,0.117647,0.6,1,0.4,1,0.692308,0,0.1875,0.647059,0.666667,1,0.875,1,0.615385,0.380952,0.227273,0.6,0.173913,0.090909,0.65,0.9375,0.47619,0.619048,0.833333,0.478261,1,0.625,0.666667,0.333333,0.5,0.611111,0.533333,0.529412,0.555556,0.636364,0.421053,0.125,0.941176,0.9375,0.428571,0.4,0.7,0.785714,0.565217,0.714286,0.7,0.166667,0.083333,1,0.384615,0.3,0.75,0.9,0.35,0.666667,0.142857,0.909091,0.714286,0.266667,0.941176,0.933333,0.666667,0.923077,0.529412,0.45,0.384615,0.923077,1,0.2,0.8125,0.181818,0.375,0.75,0.6,0.210526,0.538462,0.615385,0.133333,0.285714,0,0.722222] predictive_accuracy 0.550625 prior_entropy 6.643856189774611 recall 0.550625 [0.3125,0.3125,1,1,0.6875,0.375,0.8125,0.875,0.375,0.8125,0.4375,0.5,0.25,0.125,1,0.4375,0.875,0.0625,0.1875,0.125,0.1875,0.8125,0.375,1,0.5625,0,0.1875,0.6875,0.75,0.8125,0.875,0.9375,0.5,0.5,0.3125,0.75,0.25,0.125,0.8125,0.9375,0.625,0.8125,0.9375,0.6875,0.6875,0.625,0.75,0.3125,0.5625,0.6875,0.5,0.5625,0.625,0.4375,0.5,0.125,1,0.9375,0.375,0.375,0.875,0.6875,0.8125,0.625,0.875,0.125,0.125,1,0.3125,0.375,0.375,0.5625,0.4375,0.625,0.125,0.625,0.625,0.25,1,0.875,0.25,0.75,0.5625,0.5625,0.3125,0.75,1,0.125,0.8125,0.25,0.1875,0.9375,0.375,0.25,0.875,0.5,0.25,0.125,0,0.8125] relative_absolute_error 0.4539141414141337 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.09480242612929199 root_relative_squared_error 0.9528002323825637 total_cost 0 area_under_roc_curve 0.7766101425045775 [0.493711,0.5,1,1,1,0.987421,0.496835,0.996855,0.5,1,0.75,0.75,0.5,0.5,1,0.996855,1,0.5,0.5,0.984277,0.5,1,0.990566,1,0.496855,0.5,0.75,0.996835,0.75,0.5,1,1,0.5,0.5,0.5,0.993711,0.996855,0.987421,0.993711,1,0.993711,0.993711,0.996835,0.996835,1,1,1,0.990566,0.75,0.746835,1,0.5,0.990566,0.5,0.993711,0.984277,1,1,0.5,1,0.996855,0.993711,1,0.75,1,0.5,0.5,1,0.993711,0.487421,0.75,1,0.996835,0.75,0.487421,0.75,0.5,0.5,1,1,0.5,1,1,0.996855,0.5,0.75,1,0.5,0.75,0.993711,0.5,1,0.5,0.5,1,0.5,0.984277,0.5,0.5,0.996855] area_under_roc_curve 0.7764509195127771 [0.993711,0.5,1,1,1,0.993711,0.75,0.993711,0.5,1,0.75,0.5,0.5,0.5,1,0.996855,1,0.5,0.5,0.981132,1,0.5,0.493711,1,1,0.5,0.5,1,1,1,0.996835,1,0.746835,0.5,0.5,0.990566,0.993711,0.993711,0.996855,1,0.990566,0.993711,1,0.996835,0.75,0.75,0.996855,0.990566,0.746835,1,1,0.746835,0.993711,1,0.996855,0.490566,1,1,0.996855,0.5,0.996855,1,0.996835,0.496835,0.993711,0.5,0.5,1,0.496855,0.993711,0.746835,1,1,0.496835,0.493711,0.496835,0.5,0.743671,1,0.75,0.5,0.75,0.990566,1,0.496835,1,1,0.5,0.75,0.990566,0.5,1,0.5,0.5,0.996835,0.5,0.990566,0.5,0.5,0.996855] area_under_roc_curve 0.7671960831144016 [0.5,0.5,1,1,0.75,1,1,0.75,0.996835,1,0.75,0.5,0.993711,0.5,1,0.5,0.75,0.5,0.490566,0.5,0.5,0.5,0.5,1,0.996855,0.5,0.496835,0.993711,0.75,1,1,1,1,0.5,0.981132,0.996855,0.974843,0.481132,0.996855,0.75,0.5,0.996855,1,0.987421,1,0.996855,0.75,0.993711,0.5,1,0.5,0.996855,1,0.5,0.987421,0.5,1,1,0.993711,0.5,0.996855,0.496855,0.75,0.493711,0.996835,0.5,0.5,1,0.993711,0.75,0.5,0.996835,0.984277,1,0.990566,0.75,0.75,0.5,1,1,0.496855,1,0.5,0.5,0.996855,1,1,0.5,0.996835,0.981132,0.75,0.996855,1,0.5,1,1,0.5,0.5,0.496855,1] area_under_roc_curve 0.7608669691903508 [0.496835,0.5,1,1,0.75,0.496835,1,0.75,0.746835,0.75,0.75,0.5,0.996855,0.75,1,0.5,1,0.5,0.987421,0.5,0.5,1,0.746835,1,0.496855,0.5,0.5,0.993711,0.75,1,1,1,0.5,0.75,0.984277,0.993711,0.984277,0.474843,0.996855,1,1,0.990566,1,0.993711,1,0.993711,0.75,0.993711,0.75,1,0.5,0.996855,0.993711,0.5,0.996855,0.5,1,1,0.990566,0.5,0.996855,0.5,0.996835,0.5,0.746835,0.5,0.5,1,0.493711,0.746835,0.5,0.75,0.490566,0.75,0.990566,1,0.75,0.5,1,1,1,0.75,0.5,0.5,0.990566,1,1,0.5,1,0.977987,0.5,1,1,0.5,1,0.993711,0.5,0.5,0.490566,0.75] area_under_roc_curve 0.7765106281347022 [0.75,0.993711,1,1,1,0.5,0.996855,0.996835,0.496855,0.75,0.5,1,0.993711,0.496855,1,0.75,1,0.5,0.962264,0.5,0.5,1,0.75,1,0.75,0.496835,0.5,0.996855,0.996855,0.75,0.996855,0.5,0.746835,0.996835,0.993711,1,0.5,0.5,0.75,1,1,0.5,1,1,1,0.996855,1,0.5,0.75,0.5,0.5,0.490566,0.5,0.496855,0.743671,0.5,0.996855,0.996835,0.5,0.993711,1,1,0.993711,1,0.75,0.5,0.474843,1,0.5,0.5,0.5,0.75,0.993711,1,0.5,1,0.996835,0.5,1,1,0.496855,1,0.75,0.743671,0.993711,1,1,0.996855,1,0.5,0.493711,0.746835,0.990566,0.993711,1,0.993711,0.5,0.990566,0.5,1] area_under_roc_curve 0.7827800334368282 [0.5,0.990566,0.996835,1,0.990566,0.5,1,1,1,0.75,0.5,0.75,0.990566,0.5,1,0.75,0.75,0.5,0.962264,0.5,0.5,0.75,0.75,1,0.75,0.5,0.5,0.5,1,1,1,1,0.496835,0.743671,0.987421,0.75,0.5,0.5,1,1,1,0.75,1,0.996855,1,0.996855,0.996835,0.5,0.75,0.75,1,0.996855,0.746835,0.996855,0.746835,0.5,1,1,0.5,0.996855,1,1,0.993711,0.996855,1,0.5,0.968553,1,0.5,0.75,0.75,0.5,0.993711,0.993711,0.5,1,1,0.5,1,1,0.5,0.75,0.75,0.990506,0.996855,1,1,0.996855,0.996835,0.5,0.493711,0.996835,0.996855,0.993711,0.5,0.996855,0.5,0.996855,0.496855,0.5] area_under_roc_curve 0.7859644932728284 [1,0.984277,1,1,0.996855,0.5,1,1,0.993711,1,0.996855,0.990566,0.5,1,1,0.75,1,0.984277,0.5,0.5,0.496835,1,0.496835,1,0.75,0.493711,0.481132,0.5,0.993711,1,0.75,1,1,0.987421,0.75,0.75,0.496835,0.5,0.993671,1,0.746835,1,1,0.5,0.5,0.5,0.5,0.5,0.993711,0.996855,0.493711,1,1,0.996855,0.75,0.5,1,1,0.5,0.993711,0.993671,1,0.993711,1,1,0.490566,0.493711,1,0.75,0.5,1,0.75,0.5,1,0.5,1,1,0.493711,1,1,0.75,1,0.996835,0.996835,0.5,0.75,1,0.490566,0.5,0.5,1,1,0.5,0.984277,0.993711,0.75,0.5,0.5,0.5,1] area_under_roc_curve 0.7734057797946022 [0.5,0.977987,1,1,1,0.5,1,1,0.993711,1,0.5,0.996855,0.5,0.5,1,0.5,1,0.471698,0.5,0.5,0.746835,1,0.496835,1,0.5,0.493711,0.996855,0.5,0.490566,1,0.75,1,1,0.996855,0.5,1,0.493671,0.5,1,0.996855,0.493671,1,0.993671,0.5,1,0.5,1,0.5,0.990566,0.5,0.484277,0.75,0.75,0.996855,0.75,0.5,1,1,1,0.987421,1,0.75,0.996855,1,1,0.487421,0.993711,1,0.5,0.5,1,0.75,0.5,1,0.5,1,1,0.987421,1,1,0.5,1,0.75,1,0.5,0.75,1,0.490566,1,0.5,0.496855,0.996835,1,0.981132,0.993711,1,0.5,0.5,0.5,1] area_under_roc_curve 0.7671562773664514 [0.481132,0.75,1,1,0.5,0.990566,1,0.996855,0.5,1,0.993711,0.993711,0.5,0.5,1,0.996855,1,0.484277,0.5,0.490566,0.75,1,1,1,1,0.496855,0.990566,1,1,1,1,1,0.996855,0.996855,0.5,1,0.5,0.5,0.75,1,0.5,1,0.75,0.746835,0.75,0.746835,0.996855,0.5,0.996855,0.990566,1,0.746835,0.5,0.75,0.5,0.490566,1,0.5,0.496835,0.5,0.75,0.75,1,0.75,1,0.993711,0.5,1,0.746835,0.990566,0.996855,0.5,0.5,0.746835,0.5,0.75,0.996855,0.996855,0.996855,0.75,0.75,1,0.993711,0.490566,0.75,1,1,0.5,0.996855,0.5,0.5,1,0.5,0.5,0.981132,0.75,0.974843,0.496835,0.5,0.996855] area_under_roc_curve 0.7702611257065517 [1,0.5,1,1,0.75,0.990566,1,0.996855,0.5,1,0.996855,1,0.5,0.5,1,0.996855,1,0.474843,0.5,0.496855,0.5,1,0.996855,1,0.996835,0.5,0.493711,1,1,0.5,1,1,0.996855,0.987421,0.5,0.5,0.5,0.5,0.75,1,0.990566,1,1,0.993671,0.5,1,0.990566,0.75,0.993711,0.993711,0.75,0.75,1,0.75,0.5,0.990566,1,1,0.746835,0.5,0.75,0.75,0.496835,1,0.993711,0.996855,0.5,1,0.75,0.987421,0.5,1,0.5,0.746835,0.5,0.75,0.993711,0.993711,1,0.996835,0.75,0.496855,0.993711,0.496855,0.5,0.746835,1,0.5,1,0.5,0.75,0.996835,0.5,0.5,0.996855,0.5,0.968553,0.5,0.5,0.993711] 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 0.5523681929230042 kappa 0.5522623364338641 kappa 0.5335093179937749 kappa 0.5209014617233364 kappa 0.5522270398108001 kappa 0.5648746649850228 kappa 0.5711132134973195 kappa 0.5459561721582847 kappa 0.5334541729056663 kappa 0.5397225725094577 kb_relative_information_score 0.5552815588013323 kb_relative_information_score 0.5552815588013325 kb_relative_information_score 0.5364906387506845 kb_relative_information_score 0.5239633587169191 kb_relative_information_score 0.5552815588013327 kb_relative_information_score 0.5678088388350979 kb_relative_information_score 0.5740724788519804 kb_relative_information_score 0.5490179187844498 kb_relative_information_score 0.5364906387506845 kb_relative_information_score 0.5427542787675673 mean_absolute_error 0.008875000000000004 mean_absolute_error 0.008875000000000004 mean_absolute_error 0.009250000000000005 mean_absolute_error 0.009500000000000005 mean_absolute_error 0.008875000000000004 mean_absolute_error 0.008625000000000004 mean_absolute_error 0.008500000000000004 mean_absolute_error 0.009000000000000005 mean_absolute_error 0.009250000000000005 mean_absolute_error 0.009125000000000005 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 0.55625 predictive_accuracy 0.55625 predictive_accuracy 0.5375 predictive_accuracy 0.525 predictive_accuracy 0.55625 predictive_accuracy 0.56875 predictive_accuracy 0.575 predictive_accuracy 0.55 predictive_accuracy 0.5375 predictive_accuracy 0.54375 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 0.55625 [0,0,1,1,1,1,0,1,0,1,0.5,0.5,0,0,1,1,1,0,0,1,0,1,1,1,0,0,0.5,1,0.5,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0,1,0,1,1,1,1,0,1,1,1,1,0.5,1,0,0,1,1,0,0.5,1,1,0.5,0,0.5,0,0,1,1,0,1,1,1,0,0.5,1,0,0.5,1,0,1,0,0,1,0,1,0,0,1] recall 0.55625 [1,0,1,1,1,1,0.5,1,0,1,0.5,0,0,0,1,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,1,1,0.5,0,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,0,1,0,0,1,0,1,0.5,1,1,0,0,0,0,0.5,1,0.5,0,0.5,1,1,0,1,1,0,0.5,1,0,1,0,0,1,0,1,0,0,1] recall 0.5375 [0,0,1,1,0.5,1,1,0.5,1,1,0.5,0,1,0,1,0,0.5,0,0,0,0,0,0,1,1,0,0,1,0.5,1,1,1,1,0,1,1,1,0,1,0.5,0,1,1,1,1,1,0.5,1,0,1,0,1,1,0,1,0,1,1,1,0,1,0,0.5,0,1,0,0,1,1,0.5,0,1,1,1,1,0.5,0.5,0,1,1,0,1,0,0,1,1,1,0,1,1,0.5,1,1,0,1,1,0,0,0,1] recall 0.525 [0,0,1,1,0.5,0,1,0.5,0.5,0.5,0.5,0,1,0.5,1,0,1,0,1,0,0,1,0.5,1,0,0,0,1,0.5,1,1,1,0,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0,1,1,0,1,0,1,1,1,0,1,0,1,0,0.5,0,0,1,0,0.5,0,0.5,0,0.5,1,1,0.5,0,1,1,1,0.5,0,0,1,1,1,0,1,1,0,1,1,0,1,1,0,0,0,0.5] recall 0.55625 [0.5,1,1,1,1,0,1,1,0,0.5,0,1,1,0,1,0.5,1,0,1,0,0,1,0.5,1,0.5,0,0,1,1,0.5,1,0,0.5,1,1,1,0,0,0.5,1,1,0,1,1,1,1,1,0,0.5,0,0,0,0,0,0.5,0,1,1,0,1,1,1,1,1,0.5,0,0,1,0,0,0,0.5,1,1,0,1,1,0,1,1,0,1,0.5,0.5,1,1,1,1,1,0,0,0.5,1,1,1,1,0,1,0,1] recall 0.56875 [0,1,1,1,1,0,1,1,1,0.5,0,0.5,1,0,1,0.5,0.5,0,1,0,0,0.5,0.5,1,0.5,0,0,0,1,1,1,1,0,0.5,1,0.5,0,0,1,1,1,0.5,1,1,1,1,1,0,0.5,0.5,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0,1,1,0,0.5,0.5,0,1,1,0,1,1,0,1,1,0,0.5,0.5,1,1,1,1,1,1,0,0,1,1,1,0,1,0,1,0,0] recall 0.575 [1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,0.5,1,1,0,0,0,1,0,1,0.5,0,0,0,1,1,0.5,1,1,1,0.5,0.5,0,0,1,1,0.5,1,1,0,0,0,0,0,1,1,0,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,0.5,0,1,0.5,0,1,0,1,1,0,1,1,0.5,1,1,1,0,0.5,1,0,0,0,1,1,0,1,1,0.5,0,0,0,1] recall 0.55 [0,1,1,1,1,0,1,1,1,1,0,1,0,0,1,0,1,0,0,0,0.5,1,0,1,0,0,1,0,0,1,0.5,1,1,1,0,1,0,0,1,1,0,1,1,0,1,0,1,0,1,0,0,0.5,0.5,1,0.5,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0,1,0.5,0,1,0,1,1,1,1,1,0,1,0.5,1,0,0.5,1,0,1,0,0,1,1,1,1,1,0,0,0,1] recall 0.5375 [0,0.5,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,0,0,0.5,1,0,1,0.5,0.5,0.5,0.5,1,0,1,1,1,0.5,0,0.5,0,0,1,0,0,0,0.5,0.5,1,0.5,1,1,0,1,0.5,1,1,0,0,0.5,0,0.5,1,1,1,0.5,0.5,1,1,0,0.5,1,1,0,1,0,0,1,0,0,1,0.5,1,0,0,1] recall 0.54375 [1,0,1,1,0.5,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,0,0,0,0,0.5,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,1,0.5,0,1,1,1,0.5,0,0.5,0.5,0,1,1,1,0,1,0.5,1,0,1,0,0.5,0,0.5,1,1,1,1,0.5,0,1,0,0,0.5,1,0,1,0,0.5,1,0,0,1,0,1,0,0,1] relative_absolute_error 0.4482323232323227 relative_absolute_error 0.4482323232323227 relative_absolute_error 0.4671717171717167 relative_absolute_error 0.4797979797979793 relative_absolute_error 0.4482323232323227 relative_absolute_error 0.43560606060606005 relative_absolute_error 0.4292929292929288 relative_absolute_error 0.45454545454545403 relative_absolute_error 0.4671717171717167 relative_absolute_error 0.4608585858585853 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 0.09420721840708389 root_mean_squared_error 0.09420721840708389 root_mean_squared_error 0.09617692030835674 root_mean_squared_error 0.09746794344808966 root_mean_squared_error 0.09420721840708389 root_mean_squared_error 0.09287087810503357 root_mean_squared_error 0.0921954445729289 root_mean_squared_error 0.0948683298050514 root_mean_squared_error 0.09617692030835674 root_mean_squared_error 0.09552486587271403 root_relative_squared_error 0.9468181696950296 root_relative_squared_error 0.9468181696950296 root_relative_squared_error 0.9666144186507013 root_relative_squared_error 0.9795896894087641 root_relative_squared_error 0.9468181696950296 root_relative_squared_error 0.9333874443188747 root_relative_squared_error 0.926599081904282 root_relative_squared_error 0.9534625892455919 root_relative_squared_error 0.9666144186507013 root_relative_squared_error 0.9600610249964171 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 491.47593899942876 usercpu_time_millis 490.21646099936333 usercpu_time_millis 492.7688279985887 usercpu_time_millis 493.89460399834206 usercpu_time_millis 497.1289599998272 usercpu_time_millis 492.52348600020923 usercpu_time_millis 496.60842699995555 usercpu_time_millis 496.3657839998632 usercpu_time_millis 493.89252699984354 usercpu_time_millis 493.11058800230967 usercpu_time_millis_testing 64.89556499946048 usercpu_time_millis_testing 64.6326179994503 usercpu_time_millis_testing 64.99938900014968 usercpu_time_millis_testing 65.11875999967742 usercpu_time_millis_testing 64.72889699944062 usercpu_time_millis_testing 64.70364500091819 usercpu_time_millis_testing 64.92912499925296 usercpu_time_millis_testing 64.86829399909766 usercpu_time_millis_testing 64.986321998731 usercpu_time_millis_testing 64.7912600015843 usercpu_time_millis_training 426.5803739999683 usercpu_time_millis_training 425.58384299991303 usercpu_time_millis_training 427.769438998439 usercpu_time_millis_training 428.77584399866464 usercpu_time_millis_training 432.4000630003866 usercpu_time_millis_training 427.81984099929105 usercpu_time_millis_training 431.6793020007026 usercpu_time_millis_training 431.49749000076554 usercpu_time_millis_training 428.90620500111254 usercpu_time_millis_training 428.31932800072536 wall_clock_time_millis 491.4865493774414 wall_clock_time_millis 490.22531509399414 wall_clock_time_millis 492.77734756469727 wall_clock_time_millis 493.90339851379395 wall_clock_time_millis 497.13826179504395 wall_clock_time_millis 492.53106117248535 wall_clock_time_millis 496.61874771118164 wall_clock_time_millis 496.384859085083 wall_clock_time_millis 493.90268325805664 wall_clock_time_millis 493.1190013885498 wall_clock_time_millis_testing 64.90540504455566 wall_clock_time_millis_testing 64.64076042175293 wall_clock_time_millis_testing 65.00720977783203 wall_clock_time_millis_testing 65.12641906738281 wall_clock_time_millis_testing 64.73755836486816 wall_clock_time_millis_testing 64.71037864685059 wall_clock_time_millis_testing 64.93854522705078 wall_clock_time_millis_testing 64.87536430358887 wall_clock_time_millis_testing 64.99576568603516 wall_clock_time_millis_testing 64.79930877685547 wall_clock_time_millis_training 426.58114433288574 wall_clock_time_millis_training 425.5845546722412 wall_clock_time_millis_training 427.77013778686523 wall_clock_time_millis_training 428.77697944641113 wall_clock_time_millis_training 432.4007034301758 wall_clock_time_millis_training 427.82068252563477 wall_clock_time_millis_training 431.68020248413086 wall_clock_time_millis_training 431.50949478149414 wall_clock_time_millis_training 428.9069175720215 wall_clock_time_millis_training 428.31969261169434