6146942 1 Jan van Rijn 9954 Supervised Classification 6952 sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)(1) 4180281 axis 0 6947 categorical_features [] 6947 copy true 6947 fill_empty 0 6947 missing_values "NaN" 6947 strategy "mean" 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 true 6948 threshold 0.0 6949 C 171.42849955193327 6953 cache_size 200 6953 class_weight null 6953 coef0 0.1889548134601673 6953 decision_function_shape null 6953 degree 3 6953 gamma 0.09670554946887729 6953 kernel "sigmoid" 6953 max_iter -1 6953 probability true 6953 random_state 41876 6953 shrinking false 6953 tol 5.703935811639041e-05 6953 verbose false 6953 openml-pimp openml-python Sklearn_0.18.1. 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 13224733 description https://api.openml.org/data/download/13224733/description.xml -1 13224734 predictions https://api.openml.org/data/download/13224734/predictions.arff area_under_roc_curve 0.9930922506313137 [0.988242,0.999645,1,1,0.999566,0.993371,0.998895,0.999803,0.993805,0.999842,0.997159,0.999132,0.997356,0.965949,0.999684,0.999961,1,0.980903,0.971117,0.972143,0.986308,0.999645,0.992227,1,0.995384,0.970802,0.974077,0.998658,0.99854,0.999961,0.999842,1,0.99929,0.9884,0.996449,0.998501,0.985677,0.969105,0.999724,0.999961,0.994871,0.99712,1,0.99854,0.998856,0.993687,0.99925,0.988834,0.998146,0.995384,0.991477,0.995739,0.996686,0.981613,0.994121,0.968434,1,0.999448,0.99128,0.979009,0.998974,0.99854,0.992779,0.997317,0.998777,0.992779,0.984099,0.999882,0.988991,0.990609,0.985519,0.997199,0.988281,0.999605,0.975734,0.999211,0.999527,0.98544,1,0.999369,0.993292,0.997711,0.998422,0.994594,0.995423,0.999408,1,0.996291,0.999171,0.99562,0.988439,0.999369,0.998067,0.992148,0.998303,0.99633,0.984533,0.991556,0.95202,0.994279] average_cost 0 f_measure 0.752469775789221 [0.666667,0.848485,1,1,0.9375,0.454545,0.909091,0.969697,0.717949,0.896552,0.8,0.864865,0.740741,0.571429,1,0.969697,1,0.322581,0.26087,0.230769,0.526316,0.903226,0.647059,1,0.787879,0.294118,0.272727,0.8,0.903226,0.896552,0.969697,0.896552,0.848485,0.486486,0.83871,0.8,0.4,0.5,0.848485,0.967742,0.702703,0.857143,0.933333,0.777778,0.9375,0.823529,0.83871,0.689655,0.769231,0.83871,0.787879,0.785714,0.875,0.608696,0.787879,0.206897,1,0.903226,0.634146,0.709677,0.848485,0.909091,0.702703,0.848485,0.875,0.666667,0.228571,1,0.645161,0.689655,0.516129,0.692308,0.384615,0.83871,0.692308,0.914286,0.903226,0.536585,1,0.9375,0.666667,0.903226,0.903226,0.48,0.8,0.875,0.933333,0.903226,0.909091,0.896552,0.689655,0.8,0.758621,0.736842,0.914286,0.736842,0.642857,0.611111,0.266667,0.774194] kappa 0.7518939393939394 kb_relative_information_score 907.5570687114242 mean_absolute_error 0.016856366245401124 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 0.7689773278197998 [0.6,0.823529,1,1,0.9375,0.833333,0.882353,0.941176,0.608696,1,0.857143,0.761905,0.909091,0.526316,1,0.941176,1,0.333333,0.428571,0.3,0.454545,0.933333,0.611111,1,0.764706,0.277778,0.214286,0.736842,0.933333,1,0.941176,1,0.823529,0.428571,0.866667,0.857143,0.428571,0.583333,0.823529,1,0.619048,0.789474,1,0.7,0.9375,0.777778,0.866667,0.769231,0.652174,0.866667,0.764706,0.916667,0.875,1,0.764706,0.230769,1,0.933333,0.52,0.733333,0.823529,0.882353,0.619048,0.823529,0.875,0.647059,0.210526,1,0.666667,0.769231,0.533333,0.9,0.5,0.866667,0.9,0.842105,0.933333,0.44,1,0.9375,0.714286,0.933333,0.933333,0.666667,0.736842,0.875,1,0.933333,0.882353,1,0.769231,0.857143,0.846154,0.636364,0.842105,0.636364,0.75,0.55,0.285714,0.8] predictive_accuracy 0.754375 prior_entropy 6.6438561897747395 recall 0.754375 [0.75,0.875,1,1,0.9375,0.3125,0.9375,1,0.875,0.8125,0.75,1,0.625,0.625,1,1,1,0.3125,0.1875,0.1875,0.625,0.875,0.6875,1,0.8125,0.3125,0.375,0.875,0.875,0.8125,1,0.8125,0.875,0.5625,0.8125,0.75,0.375,0.4375,0.875,0.9375,0.8125,0.9375,0.875,0.875,0.9375,0.875,0.8125,0.625,0.9375,0.8125,0.8125,0.6875,0.875,0.4375,0.8125,0.1875,1,0.875,0.8125,0.6875,0.875,0.9375,0.8125,0.875,0.875,0.6875,0.25,1,0.625,0.625,0.5,0.5625,0.3125,0.8125,0.5625,1,0.875,0.6875,1,0.9375,0.625,0.875,0.875,0.375,0.875,0.875,0.875,0.875,0.9375,0.8125,0.625,0.75,0.6875,0.875,1,0.875,0.5625,0.6875,0.25,0.75] relative_absolute_error 0.8513316285556108 root_mean_prior_squared_error 0.09949874371066209 root_mean_squared_error 0.08647233233980928 root_relative_squared_error 0.8690796397517034 total_cost 0 area_under_roc_curve 0.9917845911949683 [0.962264,1,1,1,1,1,1,1,0.993671,1,0.996835,0.993671,0.993671,0.914557,1,1,1,0.993671,0.962025,0.981132,0.974843,1,1,1,0.993711,0.981013,0.974684,1,1,1,1,1,0.996835,0.981013,0.981013,0.987421,0.993711,0.962264,1,1,1,0.993711,1,1,1,1,1,1,1,0.96519,0.993671,1,0.993711,0.990506,0.993711,0.993711,1,1,0.993711,0.993671,1,1,1,0.996835,1,1,1,1,1,0.899371,0.974684,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,0.987342,0.996835,1,1,0.996835,1,0.996835,1,1,1,1,0.987342,0.962264,0.990506,0.889241,1] area_under_roc_curve 0.9919463020460155 [0.987421,1,1,1,1,1,1,1,0.993671,1,0.996835,0.996835,1,0.908228,1,1,1,0.984177,0.993671,0.943396,0.993711,0.993711,1,1,1,0.968354,0.981013,1,1,1,1,1,0.996835,0.993671,0.996835,0.993711,0.987421,0.937107,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,0.993711,0.949686,1,1,1,0.946203,1,1,0.990506,1,1,0.993671,0.984177,1,0.880503,1,0.981013,1,1,1,1,1,1,0.987342,1,0.993671,0.981013,1,1,0.981132,0.990506,1,1,1,1,1,0.977848,1,0.996835,0.981013,0.996835,1,0.968553,0.984177,0.968354,0.987421] area_under_roc_curve 0.9930533994108748 [0.993671,1,1,1,1,0.993671,0.993711,1,0.990506,1,1,1,0.993711,0.996835,1,1,1,0.946203,0.968553,0.962025,0.937107,1,0.968354,1,1,0.981013,0.971519,0.993711,1,1,1,1,1,0.984177,1,1,1,0.899371,1,1,0.987342,0.993711,1,1,1,0.993711,1,0.987421,0.996835,1,0.993671,1,1,1,1,0.993671,1,1,0.974843,0.939873,1,1,1,0.981132,0.996835,0.993671,1,1,0.993711,0.993671,0.981013,0.996835,1,1,0.987421,1,1,0.996835,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1,0.996835,0.993671,1,0.993671,1,0.918239,1] area_under_roc_curve 0.9919485411193376 [0.990506,1,1,1,1,0.990506,1,1,0.987342,1,0.996835,1,1,0.996835,1,1,1,1,0.893082,0.974684,1,1,0.996835,1,0.974843,0.971519,0.952532,1,1,1,1,1,1,0.993671,0.993711,1,0.993711,0.930818,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.993711,0.958861,1,0.952532,1,1,0.987421,0.987342,1,1,1,1,0.996835,1,0.96519,1,0.993711,0.990506,0.974684,0.996835,0.974843,1,0.987421,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.990506,1,0.993711,0.996835,1,0.987421,0.971519,0.990506,0.842767,0.971519] area_under_roc_curve 0.994078894992437 [1,1,1,1,1,1,1,1,0.987421,1,0.990506,1,0.993711,0.924528,1,1,1,0.993671,0.981132,0.996835,1,0.996835,0.996835,1,0.993671,0.993671,0.981013,1,1,1,1,1,1,0.981013,0.993711,1,0.987342,0.955696,1,1,1,0.993671,1,1,1,0.974843,1,1,1,1,1,0.968553,0.996835,0.993711,0.987342,0.996835,1,0.996835,1,0.987421,1,1,0.987421,1,1,1,0.981132,1,0.993671,0.993671,0.996835,1,1,1,0.905063,1,0.993671,0.987342,1,1,0.993711,1,1,0.990506,0.974843,1,1,1,1,1,0.987421,0.996835,1,0.968553,0.990506,0.993711,1,1,0.993711,0.996835] area_under_roc_curve 0.9932449645728841 [0.958861,1,1,1,1,0.987342,1,1,1,1,1,1,0.987421,1,1,1,1,0.990506,0.955975,0.933544,1,1,0.990506,1,0.993671,0.974684,0.974684,1,1,1,1,1,1,0.993671,0.993711,0.996835,0.987342,0.981013,1,1,1,1,1,1,1,0.974843,1,0.984177,1,0.996835,1,1,0.996835,1,0.996835,0.971519,1,1,0.996835,1,0.993671,1,0.987421,1,1,0.987342,0.987421,1,0.996835,1,0.990506,0.990506,1,1,0.987342,1,1,0.974684,1,1,0.987421,0.996835,1,0.987342,0.993711,1,1,1,1,0.987342,0.962264,1,1,1,1,1,0.990506,0.987421,0.949686,0.987342] area_under_roc_curve 0.9934900187087011 [0.996835,1,1,1,1,0.996835,1,1,0.993711,1,1,1,0.993671,1,1,1,1,0.987421,0.981013,0.962025,0.993671,1,1,1,0.993671,0.855346,0.930818,0.993671,1,1,0.996835,1,1,0.981132,1,1,0.96519,0.977848,1,1,0.996835,1,1,1,0.981132,1,1,0.987342,1,1,0.987421,1,1,1,0.987342,0.968354,1,1,0.990506,0.993711,1,0.990506,1,0.996835,1,0.981132,0.993711,0.996835,0.990506,1,0.993711,1,0.996835,1,0.996835,1,1,0.968553,1,1,0.977848,1,1,1,1,1,1,0.962264,1,1,1,1,0.987342,0.987421,1,1,0.984177,0.974843,0.993671,1] area_under_roc_curve 0.9946349315341134 [1,1,1,1,1,1,1,1,0.987421,1,0.987421,1,0.996835,1,1,1,1,0.924528,0.96519,0.996835,0.993671,1,0.993671,1,0.993671,0.968553,0.974843,1,0.993711,1,1,1,1,0.987421,0.996835,1,0.977848,0.968354,1,1,1,1,1,1,1,1,1,0.987342,1,1,0.949686,0.996835,0.996835,1,0.996835,0.955696,1,1,0.984177,0.993711,1,1,0.993711,1,1,0.962264,0.949686,1,0.996835,0.996835,1,1,0.996835,1,0.993671,1,1,1,1,1,0.996835,1,0.993671,1,1,1,1,0.987421,1,0.996835,0.993711,1,1,1,1,0.993671,0.996835,0.974843,0.993671,1] area_under_roc_curve 0.993762688082159 [0.981132,1,1,1,1,0.993711,0.996835,1,1,1,0.993711,1,1,0.993671,1,1,1,0.981132,0.996835,0.987421,1,1,0.974843,1,1,1,0.981132,1,1,1,1,1,1,0.987421,0.996835,1,0.977848,0.990506,1,1,0.987421,1,1,0.990506,1,0.981013,1,0.990506,0.993711,0.993711,0.987342,0.996835,1,0.943038,0.990506,0.90566,1,1,1,0.996835,0.996835,1,1,0.996835,1,0.993711,0.968354,1,0.990506,0.993711,1,0.987421,0.949367,1,0.996835,0.993671,1,0.993711,1,0.996835,1,0.993711,1,0.981132,1,1,1,1,1,0.996835,0.993671,1,1,0.993671,0.993711,0.990506,0.981132,1,0.968354,1] area_under_roc_curve 0.9949080984794202 [0.993711,1,1,1,1,0.993711,1,1,0.993671,1,1,1,1,0.990506,1,1,1,0.943396,0.981013,0.962264,0.952532,1,1,1,1,0.974843,1,1,0.996835,1,1,1,1,1,1,1,0.990506,1,1,1,1,0.996835,1,1,1,1,1,0.996835,1,1,0.996835,1,1,0.984177,0.996835,0.981132,1,1,0.981013,0.987342,1,1,0.984177,1,0.993711,0.993711,0.977848,1,1,0.981132,0.993711,1,0.987342,0.996835,0.987342,0.993671,1,0.987421,1,1,1,0.981132,0.993711,0.981132,1,1,1,0.996835,1,0.990506,0.993671,1,1,0.993671,1,0.996835,0.968553,0.993671,0.993671,1] 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 0.715606114468539 kappa 0.7597787435796127 kappa 0.7472353870458136 kappa 0.7346390775548887 kappa 0.766183498558395 kappa 0.7220028431527404 kappa 0.7472154198593886 kappa 0.7724579284190567 kappa 0.7598641336545676 kappa 0.7914774298013506 kb_relative_information_score 90.89162335118601 kb_relative_information_score 89.77404050099031 kb_relative_information_score 90.63235088047901 kb_relative_information_score 89.98844473838257 kb_relative_information_score 90.06718865450992 kb_relative_information_score 89.07609071948745 kb_relative_information_score 92.98090092779631 kb_relative_information_score 91.75129420712848 kb_relative_information_score 90.9475808672391 kb_relative_information_score 91.44755386422342 mean_absolute_error 0.016774946771573502 mean_absolute_error 0.016935401183860374 mean_absolute_error 0.01687107113496967 mean_absolute_error 0.016911246969461342 mean_absolute_error 0.01694572974339952 mean_absolute_error 0.017011784559676474 mean_absolute_error 0.01665256352154496 mean_absolute_error 0.016784065006962876 mean_absolute_error 0.016857130325002898 mean_absolute_error 0.016819723237559453 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 0.71875 predictive_accuracy 0.7625 predictive_accuracy 0.75 predictive_accuracy 0.7375 predictive_accuracy 0.76875 predictive_accuracy 0.725 predictive_accuracy 0.75 predictive_accuracy 0.775 predictive_accuracy 0.7625 predictive_accuracy 0.79375 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 0.71875 [1,0.5,1,1,1,0,1,1,1,1,0.5,1,0.5,0,1,1,1,0.5,0.5,0,0,1,1,1,0,0,0.5,1,1,0,1,0.5,0.5,0.5,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0.5,1,0,1,0.5,0.5,1,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,1,0.5,0.5,1,0.5,0,1,0,1] recall 0.7625 [1,1,1,1,1,0,0.5,1,1,1,0.5,1,1,0.5,1,1,1,0.5,1,0,0,0,0,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,0,0.5,1,0,0.5,0,1,0.5,1,1,0.5,0,1,1,0,0.5,1,1,1,1,0,0.5,1,1,1,1,1,0,0.5,0.5,0] recall 0.75 [0.5,1,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0.5,0,0,0,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,0,0,1,0.5,0,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0.5,0,1,1,0,1,0,1,0.5,1,0,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0.5,0.5,0,1] recall 0.7375 [1,0.5,1,1,0.5,0,1,1,0.5,0.5,0.5,1,0,0.5,1,1,1,0.5,0,0,1,1,1,1,0,0.5,0.5,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,0,0.5,0,0,1,0,0.5,0.5,0.5,0,1,1,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,0,0.5] recall 0.76875 [0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,1,0,0,0.5,1,1,0.5,1,1,0.5,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0,0.5,0,0.5,0.5,1,0.5,0.5,1,1,1,1,1,0.5,1,0,1,0.5,0.5,1,0.5,0,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,0,1,1,1,0.5,0,1,1] recall 0.725 [0.5,1,1,1,1,0,1,1,1,0.5,1,1,0,1,1,1,1,0.5,0,0.5,1,0.5,1,1,1,0.5,0.5,0,1,0.5,1,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0.5,1,0.5,1,1,1,1,0.5,0,1,1,1,0.5,0,1,1,0.5,1,1,0.5,1,1,0,0.5,1,0.5,0,1,1,1,1,0,0,0.5,1,1,1,1,0.5,1,0,0] recall 0.75 [1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0.5,1,1,0,0.5,0,0.5,1,1,1,1,1,0,0.5,0,1,1,1,0,1,1,1,1,1,0,0,1,1,1,0,0.5,0.5,0,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,1] recall 0.775 [0.5,1,1,1,1,0.5,1,1,1,1,0,1,0.5,1,1,1,1,0,0,0.5,0.5,1,0.5,1,0.5,0,0,1,0,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0.5,1,0,1,0.5,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0.5,1,0,1,1,0,1,1,0,1,1,1,0,0.5,1] recall 0.7625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,0.5,0.5,0,1,0,1,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,0.5,0,1,0,1,1,0.5,1,1,1,1,1,0.5,1,0.5,0,1,0,0,0.5,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,0,1,0,1] recall 0.79375 [1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,0,0,0.5,1,1,1,1,0,0,1,0.5,1,1,0,1,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0,1,1,1,1,1,1,0,1,1,1,0.5,1,0.5,0,0,1,0,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1] relative_absolute_error 0.8472195339178522 relative_absolute_error 0.8553232921141588 relative_absolute_error 0.8520742997459415 relative_absolute_error 0.854103382296026 relative_absolute_error 0.8558449365353278 relative_absolute_error 0.8591810383674973 relative_absolute_error 0.8410385616941884 relative_absolute_error 0.8476800508567095 relative_absolute_error 0.8513702184344883 relative_absolute_error 0.8494809715939102 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 0.08620111077361681 root_mean_squared_error 0.08673916877831987 root_mean_squared_error 0.08659980304223235 root_mean_squared_error 0.08670349400918848 root_mean_squared_error 0.08684842376105012 root_mean_squared_error 0.087298652230909 root_mean_squared_error 0.0854840492488134 root_mean_squared_error 0.08603384723049573 root_mean_squared_error 0.08647661210918689 root_mean_squared_error 0.08632527188084274 root_relative_squared_error 0.8663537604483311 root_relative_squared_error 0.871761446863626 root_relative_squared_error 0.8703607685144321 root_relative_squared_error 0.8714029019433492 root_relative_squared_error 0.8728595007551199 root_relative_squared_error 0.8773844671322648 root_relative_squared_error 0.8591470209653826 root_relative_squared_error 0.8646726985888218 root_relative_squared_error 0.8691226530523545 root_relative_squared_error 0.8676016265277964 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 2102.692513000001 usercpu_time_millis 1950.9491050000013 usercpu_time_millis 1919.454179999999 usercpu_time_millis 1923.778284000001 usercpu_time_millis 1921.8195070000022 usercpu_time_millis 1908.1069959999973 usercpu_time_millis 1925.6812540000005 usercpu_time_millis 1922.9449719999998 usercpu_time_millis 1906.9201589999984 usercpu_time_millis 1911.0449679999988 usercpu_time_millis_testing 167.80878600000017 usercpu_time_millis_testing 162.36005900000094 usercpu_time_millis_testing 162.45684699999964 usercpu_time_millis_testing 161.40331500000116 usercpu_time_millis_testing 164.1422040000009 usercpu_time_millis_testing 160.99691699999852 usercpu_time_millis_testing 163.29651200000228 usercpu_time_millis_testing 161.81072299999855 usercpu_time_millis_testing 161.26553199999805 usercpu_time_millis_testing 159.75269799999836 usercpu_time_millis_training 1934.8837270000008 usercpu_time_millis_training 1788.5890460000003 usercpu_time_millis_training 1756.9973329999993 usercpu_time_millis_training 1762.3749689999997 usercpu_time_millis_training 1757.6773030000013 usercpu_time_millis_training 1747.1100789999987 usercpu_time_millis_training 1762.3847419999984 usercpu_time_millis_training 1761.1342490000013 usercpu_time_millis_training 1745.6546270000003 usercpu_time_millis_training 1751.2922700000004