10401820 1 Jan van Rijn 9954 Supervised Classification 16360 sklearn.svm.classes.SVC(32) 8239589 C 14157.7694693682 16360 cache_size 200 16360 class_weight null 16360 coef0 0.3782597505563763 16360 decision_function_shape "ovr" 16360 degree 3 16360 gamma 0.0012505097632321644 16360 kernel "sigmoid" 16360 max_iter -1 16360 probability false 16360 random_state 51399 16360 shrinking true 16360 tol 0.009259120484187982 16360 verbose false 16360 openml-python Sklearn_0.21.2. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 21725424 description https://api.openml.org/data/download/21725424/description.xml -1 21725426 predictions https://api.openml.org/data/download/21725426/predictions.arff area_under_roc_curve 0.8147095959595965 [0.779672,0.714331,1,1,0.905619,0.684028,0.90625,0.999053,0.68529,0.90625,0.842487,0.998106,0.653725,0.624684,1,0.904987,1,0.52399,0.556503,0.557134,0.624053,0.90625,0.77904,1,0.810922,0.62279,0.620896,0.93529,0.937184,0.875,0.999053,0.96875,0.873737,0.808712,0.778409,0.90404,0.618687,0.557449,0.935606,0.96875,0.809659,0.90404,0.999369,0.840278,0.9375,0.873737,0.873737,0.622475,0.93529,0.842487,0.779672,0.779672,0.841225,0.717803,0.841225,0.526515,0.999684,0.968434,0.68529,0.716856,0.966856,0.874369,0.903409,0.874053,0.935606,0.716225,0.555556,1,0.684659,0.746528,0.686869,0.780934,0.715278,0.905303,0.624053,0.905934,0.968119,0.653093,1,0.968434,0.717803,0.936869,0.842172,0.809659,0.81029,0.937184,1,0.654356,0.905619,0.620265,0.717803,0.967172,0.717487,0.652778,0.998422,0.842487,0.618371,0.623106,0.498737,0.873422] average_cost 0 f_measure 0.6315173328479278 [0.6,0.378378,1,1,0.83871,0.363636,0.896552,0.914286,0.413793,0.896552,0.709677,0.842105,0.344828,0.380952,1,0.787879,1,0.05,0.108108,0.114286,0.347826,0.896552,0.5625,1,0.645161,0.296296,0.242424,0.756757,0.903226,0.857143,0.914286,0.967742,0.75,0.526316,0.529412,0.722222,0.2,0.117647,0.777778,0.967742,0.571429,0.722222,0.941176,0.578947,0.933333,0.75,0.75,0.285714,0.756757,0.709677,0.6,0.6,0.628571,0.538462,0.628571,0.0625,0.969697,0.9375,0.413793,0.482759,0.810811,0.8,0.684211,0.774194,0.777778,0.451613,0.1,1,0.387097,0.457143,0.5,0.692308,0.411765,0.8125,0.347826,0.866667,0.909091,0.322581,1,0.9375,0.538462,0.875,0.6875,0.571429,0.606061,0.903226,1,0.37037,0.83871,0.228571,0.538462,0.833333,0.518519,0.3125,0.864865,0.709677,0.195122,0.307692,0,0.727273] kappa 0.6294191919191919 kb_relative_information_score 0.6323243310089982 mean_absolute_error 0.007337499999999899 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 0.6474888740688276 [0.642857,0.333333,1,1,0.866667,0.352941,1,0.842105,0.461538,1,0.733333,0.727273,0.384615,0.8,1,0.764706,1,0.041667,0.095238,0.105263,0.571429,1,0.5625,1,0.666667,0.363636,0.235294,0.666667,0.933333,1,0.842105,1,0.75,0.454545,0.5,0.65,0.166667,0.111111,0.7,1,0.526316,0.65,0.888889,0.5,1,0.75,0.75,0.333333,0.666667,0.733333,0.642857,0.642857,0.578947,0.7,0.578947,0.0625,0.941176,0.9375,0.461538,0.538462,0.714286,0.857143,0.590909,0.8,0.7,0.466667,0.083333,1,0.4,0.421053,0.75,0.9,0.388889,0.8125,0.571429,0.928571,0.882353,0.333333,1,0.9375,0.7,0.875,0.6875,0.526316,0.588235,0.933333,1,0.454545,0.866667,0.210526,0.7,0.75,0.636364,0.3125,0.761905,0.733333,0.16,0.4,0,0.705882] predictive_accuracy 0.633125 prior_entropy 6.643856189774611 recall 0.633125 [0.5625,0.4375,1,1,0.8125,0.375,0.8125,1,0.375,0.8125,0.6875,1,0.3125,0.25,1,0.8125,1,0.0625,0.125,0.125,0.25,0.8125,0.5625,1,0.625,0.25,0.25,0.875,0.875,0.75,1,0.9375,0.75,0.625,0.5625,0.8125,0.25,0.125,0.875,0.9375,0.625,0.8125,1,0.6875,0.875,0.75,0.75,0.25,0.875,0.6875,0.5625,0.5625,0.6875,0.4375,0.6875,0.0625,1,0.9375,0.375,0.4375,0.9375,0.75,0.8125,0.75,0.875,0.4375,0.125,1,0.375,0.5,0.375,0.5625,0.4375,0.8125,0.25,0.8125,0.9375,0.3125,1,0.9375,0.4375,0.875,0.6875,0.625,0.625,0.875,1,0.3125,0.8125,0.25,0.4375,0.9375,0.4375,0.3125,1,0.6875,0.25,0.25,0,0.75] relative_absolute_error 0.3705808080808023 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08565920849505848 root_relative_squared_error 0.8609074376270682 total_cost 0 area_under_roc_curve 0.8048125149271552 [0.493711,0.5,1,1,1,0.987421,0.75,0.996855,0.5,1,0.75,1,0.5,0.5,1,1,1,0.5,0.5,0.984277,0.5,1,0.993711,1,0.5,0.5,0.75,0.996835,1,0.5,1,1,0.5,0.487342,0.5,0.493711,0.996855,0.987421,0.996855,1,0.996855,0.993711,0.996835,0.996835,1,1,1,0.993711,1,0.746835,1,0.5,0.993711,0.5,0.996855,0.490566,1,1,0.5,1,0.996855,0.993711,1,0.75,1,0.75,0.5,1,0.996855,0.490566,0.75,1,0.996835,1,0.493711,1,0.75,0.5,1,1,0.5,0.996835,1,1,0.75,0.75,1,0.75,0.75,0.990566,0.75,1,0.5,0.5,1,0.496835,0.984277,0.5,0.5,0.996855] area_under_roc_curve 0.8393440012737837 [1,0.5,1,1,1,0.993711,0.75,0.996855,0.5,1,0.75,1,0.5,0.75,1,0.996855,1,0.5,0.5,0.987421,1,0.5,0.496855,1,1,0.5,0.496835,0.996835,1,1,0.996835,1,0.996835,1,1,0.996855,0.993711,0.993711,0.996855,1,0.996855,0.996855,1,0.996835,0.75,0.75,0.996855,0.990566,0.746835,1,1,0.746835,0.993711,1,1,0.490566,1,1,1,0.75,0.996855,1,0.996835,0.75,0.996855,1,0.5,1,0.493711,0.996855,0.746835,1,1,0.75,0.5,0.746835,1,0.993671,1,0.75,0.5,1,0.996855,1,0.746835,1,1,0.75,0.75,0.990566,0.5,1,0.5,0.5,0.996835,0.75,0.993711,0.5,0.5,0.5] area_under_roc_curve 0.8110620173553057 [0.5,0.5,1,1,0.75,1,0.5,1,0.996835,1,1,1,0.993711,0.5,1,0.5,1,0.5,0.5,0.490506,0.5,0.5,0.75,1,0.996855,0.75,0.746835,0.996855,1,1,1,1,1,0.5,0.990566,0.996855,0.977987,0.487421,0.996855,0.75,0.496835,0.996855,1,0.987421,1,1,0.75,1,0.75,1,0.5,1,1,0.5,0.990566,0.5,1,1,0.993711,0.5,0.996855,0.5,0.75,0.493711,0.993671,0.5,0.496835,1,0.993711,0.746835,0.5,0.996835,0.990566,1,1,0.75,1,0.496835,1,1,0.996855,1,1,0.5,1,1,1,0.5,0.996835,0.981132,0.75,0.996855,1,0.5,1,1,0.5,0.75,0.496855,1] area_under_roc_curve 0.8016479579651298 [0.746835,0.746835,1,1,0.75,0.5,1,1,0.746835,0.75,0.75,1,0.996855,0.5,1,1,1,0.5,0.490566,0.496835,0.5,1,0.993671,1,0.493711,0.5,0.496835,0.993711,0.75,1,1,1,0.75,0.75,0.993711,0.996855,0.987421,0.481132,0.996855,1,1,0.990566,1,0.996855,1,0.996855,0.75,0.990566,1,1,0.5,1,0.993711,0.5,1,0.5,1,1,0.993711,0.5,0.996855,1,0.996835,0.5,0.746835,0.5,0.496835,1,0.493711,0.746835,0.5,0.75,0.490566,0.746835,1,1,1,0.5,1,1,1,1,0.75,0.5,0.987421,1,1,0.5,1,0.990566,0.5,1,1,0.5,1,0.996855,0.5,0.75,0.490566,0.75] area_under_roc_curve 0.804732903431255 [0.75,1,1,1,1,0.5,1,1,0.496855,0.75,1,1,0.993711,0.496855,1,0.996835,1,0.5,0.968553,0.5,0.5,1,0.5,1,0.746835,0.746835,0.5,1,0.996855,0.75,0.996855,0.5,0.75,0.996835,0.996855,1,0.5,0.5,1,1,0.996835,0.5,1,1,1,0.996855,1,0.5,1,0.5,0.5,0.493711,0.5,0.496855,0.743671,0.496835,0.996855,0.996835,0.5,0.993711,1,1,0.996855,1,0.75,0.75,0.477987,1,0.5,0.496835,0.5,0.75,0.993711,1,0.75,1,0.996835,0.5,1,1,0.996855,1,0.5,0.993671,0.993711,1,1,0.996855,1,0.5,0.996855,0.746835,0.990566,0.993711,1,0.996855,0.5,0.993711,0.5,0.996835] area_under_roc_curve 0.8172518111615317 [0.75,0.990566,1,1,0.996855,0.5,1,1,1,0.75,0.5,1,0.990566,1,1,1,1,0.496835,0.981132,0.5,0.5,0.75,0.746835,1,0.746835,0.743671,0.5,0.5,1,0.75,1,1,0.996835,0.746835,0.993711,0.75,0.496835,0.5,1,1,0.996835,0.75,1,0.996855,1,0.996855,0.996835,0.5,1,0.75,1,0.996855,0.746835,1,0.746835,0.496835,1,1,0.5,0.996855,1,1,0.993711,0.996855,1,0.5,0.971698,1,0.5,0.75,0.75,0.5,0.993711,0.996855,0.75,1,1,0.5,1,1,0.496855,0.75,0.75,0.990506,1,1,1,0.996855,0.996835,0.5,0.496855,0.996835,0.996855,0.996855,1,1,0.5,0.996855,0.5,0.5] area_under_roc_curve 0.8109824058594057 [1,0.987421,1,1,0.996855,0.5,1,1,0.993711,1,0.996855,0.990566,0.5,0.5,1,1,1,0.990566,0.5,0.5,0.493671,1,0.75,1,0.75,0.496855,0.484277,0.75,1,1,0.996835,1,1,0.993711,0.75,0.996835,0.490506,0.5,0.993671,1,0.746835,1,1,0.5,0.5,0.5,0.5,0.5,0.993711,1,0.993711,1,1,0.996855,0.746835,0.5,1,1,0.5,0.996855,0.993671,1,0.993711,1,1,0.493711,0.496855,1,0.746835,0.75,1,0.75,0.5,1,0.5,1,1,0.493711,1,1,0.75,1,0.996835,0.996835,0.5,1,1,0.493711,0.5,0.5,0.996855,0.996835,0.5,0.987421,0.996855,1,0.5,0.5,0.5,1] area_under_roc_curve 0.8299896505055328 [1,0.984277,1,1,1,0.5,1,1,0.993711,1,1,0.996855,0.75,1,1,0.75,1,0.477987,0.5,0.5,0.746835,1,0.75,1,0.75,0.990566,0.996855,0.993671,0.5,1,1,1,1,0.996855,0.496835,1,0.493671,0.5,1,1,0.496835,1,0.996835,0.5,1,0.75,1,0.5,0.993711,0.5,0.490566,0.75,0.75,0.996855,1,0.5,1,1,1,0.993711,1,0.75,0.996855,1,1,0.987421,0.990566,1,0.75,0.75,1,0.75,0.5,1,0.496835,1,1,0.993711,1,1,0.75,1,0.75,1,0.5,0.75,1,0.493711,1,0.5,0.5,1,1,0.987421,1,0.996835,0.5,0.5,0.5,1] area_under_roc_curve 0.8142862829392559 [0.493711,0.746835,1,1,0.75,0.993711,1,1,0.5,1,0.993711,0.993711,0.5,0.75,1,0.996855,1,0.484277,0.5,0.490566,0.75,1,1,1,1,0.5,0.990566,1,1,1,1,1,0.996855,0.996855,0.75,1,0.5,0.5,0.75,1,0.5,1,1,0.746835,1,0.996835,0.996855,0.5,0.996855,0.993711,1,0.746835,0.746835,0.75,0.5,0.490566,1,0.5,0.493671,0.5,0.75,0.75,1,1,1,0.993711,0.5,1,0.746835,0.996855,1,0.5,0.5,1,0.5,1,0.996855,0.993711,1,1,0.75,1,0.993711,0.493711,1,1,1,0.75,1,0.5,0.75,1,0.5,0.75,0.990566,0.75,0.977987,0.496835,0.5,0.996855] area_under_roc_curve 0.8173911312793567 [1,0.75,1,1,1,0.990566,1,0.996855,0.5,1,0.996855,1,0.5,0.5,1,0.996855,1,0.477987,0.5,0.496855,0.75,1,0.996855,1,1,0.5,0.496855,1,1,0.5,1,1,0.996855,0.993711,0.75,0.746835,0.5,0.5,0.75,1,0.993711,1,1,0.993671,1,1,0.996855,0.5,0.996855,0.996855,0.75,0.75,1,0.75,1,0.987421,1,1,0.746835,0.5,1,0.75,0.496835,1,0.993711,1,0.5,1,0.75,0.990566,0.496855,1,0.5,0.746835,0.5,0.75,1,0.996855,1,0.996835,0.75,0.496855,0.996855,0.496855,1,0.996835,1,0.5,1,0.5,1,0.996835,0.75,0.5,1,0.75,0.977987,0.493671,0.5,0.993711] 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 0.6088636542859397 kappa 0.6781192063429451 kappa 0.6214361765053827 kappa 0.6025706738161889 kappa 0.6088173823888955 kappa 0.6340116737655781 kappa 0.6213465862028162 kappa 0.6592656860038648 kappa 0.6277749300106462 kappa 0.6340549706218699 kb_relative_information_score 0.6116543189532763 kb_relative_information_score 0.6805543591389857 kb_relative_information_score 0.6241815989870414 kb_relative_information_score 0.6053906789363939 kb_relative_information_score 0.6116543189532764 kb_relative_information_score 0.6367088790208071 kb_relative_information_score 0.6241815989870416 kb_relative_information_score 0.6617634390883376 kb_relative_information_score 0.6304452390039245 kb_relative_information_score 0.6367088790208072 mean_absolute_error 0.007750000000000004 mean_absolute_error 0.006375000000000003 mean_absolute_error 0.007500000000000004 mean_absolute_error 0.007875000000000004 mean_absolute_error 0.007750000000000004 mean_absolute_error 0.007250000000000004 mean_absolute_error 0.007500000000000004 mean_absolute_error 0.006750000000000003 mean_absolute_error 0.007375000000000004 mean_absolute_error 0.007250000000000004 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 0.6125 predictive_accuracy 0.68125 predictive_accuracy 0.625 predictive_accuracy 0.60625 predictive_accuracy 0.6125 predictive_accuracy 0.6375 predictive_accuracy 0.625 predictive_accuracy 0.6625 predictive_accuracy 0.63125 predictive_accuracy 0.6375 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 0.6125 [0,0,1,1,1,1,0.5,1,0,1,0.5,1,0,0,1,1,1,0,0,1,0,1,1,1,0,0,0.5,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0,1,0,1,1,0,1,1,1,1,0.5,1,0.5,0,1,1,0,0.5,1,1,1,0,1,0.5,0,1,1,0,1,1,1,0.5,0.5,1,0.5,0.5,1,0.5,1,0,0,1,0,1,0,0,1] recall 0.68125 [1,0,1,1,1,1,0.5,1,0,1,0.5,1,0,0.5,1,1,1,0,0,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0,1,0.5,1,1,0.5,0,0.5,1,1,1,0.5,0,1,1,1,0.5,1,1,0.5,0.5,1,0,1,0,0,1,0.5,1,0,0,0] recall 0.625 [0,0,1,1,0.5,1,0,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,0,1,0.5,0,1,1,1,1,1,0.5,1,0.5,1,0,1,1,0,1,0,1,1,1,0,1,0,0.5,0,1,0,0,1,1,0.5,0,1,1,1,1,0.5,1,0,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,0,1,1,0,0.5,0,1] recall 0.60625 [0.5,0.5,1,1,0.5,0,1,1,0.5,0.5,0.5,1,1,0,1,1,1,0,0,0,0,1,1,1,0,0,0,1,0.5,1,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,0,1,1,1,0,1,1,1,0,0.5,0,0,1,0,0.5,0,0.5,0,0.5,1,1,1,0,1,1,1,1,0.5,0,1,1,1,0,1,1,0,1,1,0,1,1,0,0.5,0,0.5] recall 0.6125 [0.5,1,1,1,1,0,1,1,0,0.5,1,1,1,0,1,1,1,0,1,0,0,1,0,1,0.5,0.5,0,1,1,0.5,1,0,0.5,1,1,1,0,0,1,1,1,0,1,1,1,1,1,0,1,0,0,0,0,0,0.5,0,1,1,0,1,1,1,1,1,0.5,0.5,0,1,0,0,0,0.5,1,1,0.5,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0.5,1,1,1,1,0,1,0,1] recall 0.6375 [0.5,1,1,1,1,0,1,1,1,0.5,0,1,1,1,1,1,1,0,1,0,0,0.5,0.5,1,0.5,0.5,0,0,1,0.5,1,1,1,0.5,1,0.5,0,0,1,1,1,0.5,1,1,1,1,1,0,1,0.5,1,1,0.5,1,0.5,0,1,1,0,1,1,1,1,1,1,0,1,1,0,0.5,0.5,0,1,1,0.5,1,1,0,1,1,0,0.5,0.5,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0] recall 0.625 [1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,0,0,0,1,0.5,1,0.5,0,0,0.5,1,1,1,1,1,1,0.5,1,0,0,1,1,0.5,1,1,0,0,0,0,0,1,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,0,0,1,0.5,0.5,1,0.5,0,1,0,1,1,0,1,1,0.5,1,1,1,0,1,1,0,0,0,1,1,0,1,1,1,0,0,0,1] recall 0.6625 [1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0.5,1,0,0,0,0.5,1,0.5,1,0.5,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,0,1,0.5,1,0,1,0,0,0.5,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,0,1,0,1,1,1,1,1,0.5,1,0.5,1,0,0.5,1,0,1,0,0,1,1,1,1,1,0,0,0,1] recall 0.63125 [0,0.5,1,1,0.5,1,1,1,0,1,1,1,0,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,1,0,1,1,0.5,1,1,1,0,1,1,1,0.5,0.5,0.5,0,0,1,0,0,0,0.5,0.5,1,1,1,1,0,1,0.5,1,1,0,0,1,0,1,1,1,1,1,0.5,1,1,0,1,1,1,0.5,1,0,0.5,1,0,0.5,1,0.5,1,0,0,1] recall 0.6375 [1,0.5,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,1,0,1,1,1,1,0.5,0.5,0,0,0.5,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,1,0.5,1,1,1,1,0.5,0,1,0.5,0,1,1,1,0,1,0.5,1,0,1,0,0.5,0,0.5,1,1,1,1,0.5,0,1,0,1,1,1,0,1,0,1,1,0.5,0,1,0.5,1,0,0,1] relative_absolute_error 0.39141414141414105 relative_absolute_error 0.3219696969696966 relative_absolute_error 0.3787878787878784 relative_absolute_error 0.39772727272727226 relative_absolute_error 0.39141414141414105 relative_absolute_error 0.36616161616161574 relative_absolute_error 0.3787878787878784 relative_absolute_error 0.3409090909090905 relative_absolute_error 0.37247474747474707 relative_absolute_error 0.36616161616161574 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 0.08803408430829507 root_mean_squared_error 0.07984359711335658 root_mean_squared_error 0.08660254037844389 root_mean_squared_error 0.08874119674649426 root_mean_squared_error 0.08803408430829507 root_mean_squared_error 0.08514693182963202 root_mean_squared_error 0.08660254037844389 root_mean_squared_error 0.08215838362577493 root_mean_squared_error 0.08587782018658836 root_mean_squared_error 0.08514693182963202 root_relative_squared_error 0.884775837615541 root_relative_squared_error 0.8024583440524458 root_relative_squared_error 0.870388279778489 root_relative_squared_error 0.8918825850158444 root_relative_squared_error 0.884775837615541 root_relative_squared_error 0.8557588634207839 root_relative_squared_error 0.870388279778489 root_relative_squared_error 0.82572282384477 root_relative_squared_error 0.8631045677955218 root_relative_squared_error 0.8557588634207839 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 423.8188959998297 usercpu_time_millis 419.3196579999494 usercpu_time_millis 418.8718240000071 usercpu_time_millis 418.87384500000735 usercpu_time_millis 424.1016039998158 usercpu_time_millis 418.6408600000959 usercpu_time_millis 419.8410930000591 usercpu_time_millis 419.98905999980707 usercpu_time_millis 417.3484080001799 usercpu_time_millis 418.6474589998852 usercpu_time_millis_testing 63.996532999908595 usercpu_time_millis_testing 63.592602999960945 usercpu_time_millis_testing 63.57291399990572 usercpu_time_millis_testing 63.87716399990495 usercpu_time_millis_testing 63.96790999997393 usercpu_time_millis_testing 64.0809450001143 usercpu_time_millis_testing 63.5913480000454 usercpu_time_millis_testing 63.61272599997392 usercpu_time_millis_testing 63.28593700004603 usercpu_time_millis_testing 65.18737099986538 usercpu_time_millis_training 359.8223629999211 usercpu_time_millis_training 355.72705499998847 usercpu_time_millis_training 355.2989100001014 usercpu_time_millis_training 354.9966810001024 usercpu_time_millis_training 360.13369399984185 usercpu_time_millis_training 354.55991499998163 usercpu_time_millis_training 356.2497450000137 usercpu_time_millis_training 356.37633399983315 usercpu_time_millis_training 354.0624710001339 usercpu_time_millis_training 353.4600880000198 wall_clock_time_millis 423.83289337158203 wall_clock_time_millis 419.31986808776855 wall_clock_time_millis 418.86258125305176 wall_clock_time_millis 418.87617111206055 wall_clock_time_millis 424.11136627197266 wall_clock_time_millis 418.6427593231201 wall_clock_time_millis 419.8315143585205 wall_clock_time_millis 419.9941158294678 wall_clock_time_millis 417.339563369751 wall_clock_time_millis 418.66326332092285 wall_clock_time_millis_testing 64.00179862976074 wall_clock_time_millis_testing 63.59672546386719 wall_clock_time_millis_testing 63.576698303222656 wall_clock_time_millis_testing 63.881874084472656 wall_clock_time_millis_testing 63.97271156311035 wall_clock_time_millis_testing 64.08476829528809 wall_clock_time_millis_testing 63.59529495239258 wall_clock_time_millis_testing 63.630104064941406 wall_clock_time_millis_testing 63.28916549682617 wall_clock_time_millis_testing 65.2155876159668 wall_clock_time_millis_training 359.8310947418213 wall_clock_time_millis_training 355.72314262390137 wall_clock_time_millis_training 355.2858829498291 wall_clock_time_millis_training 354.9942970275879 wall_clock_time_millis_training 360.1386547088623 wall_clock_time_millis_training 354.55799102783203 wall_clock_time_millis_training 356.23621940612793 wall_clock_time_millis_training 356.36401176452637 wall_clock_time_millis_training 354.0503978729248 wall_clock_time_millis_training 353.44767570495605