8888206 710 William Raynaut 9954 Supervised Classification 8311 weka.kf.HoeffdingTree(1) 6835536 mDataExp Modelage study_107 1491 one-hundred-plants-margin https://www.openml.org/data/download/1592283/phpCsX3fx -1 18692226 description https://api.openml.org/data/download/18692226/description963247977466755263.xml -1 18692227 predictions https://api.openml.org/data/download/18692227/predictions8423245934425663980.arff area_under_roc_curve 0.987252 [0.995561,1,1,0.96875,0.968711,0.967507,1,1,0.999014,0.96875,0.999369,1,1,0.874132,1,0.999842,1,0.959616,0.925623,0.942649,0.999566,1,0.96733,1,0.999428,0.959142,0.989781,0.999763,0.999428,1,1,1,0.999921,0.992582,1,0.967606,0.995462,0.990491,0.999842,0.999961,0.935961,0.999566,1,0.999961,0.999566,0.999961,0.999645,0.998935,0.999763,0.968415,0.999171,0.998323,0.968395,0.996784,0.99779,0.925979,1,0.999645,0.997711,0.997396,0.999921,0.999803,0.998185,0.999921,0.999467,0.967862,0.990885,1,0.967527,0.966836,0.968099,0.999684,0.964883,1,0.935527,0.999921,0.999724,0.931424,1,1,0.998382,0.967823,0.999684,0.998106,0.999507,0.968316,1,0.96804,0.999527,1,0.999329,0.999388,0.999605,0.99929,0.999882,0.999961,0.999803,0.999329,0.926807,1] average_cost 0 f_measure 0.843727 [0.733333,0.967742,1,0.967742,0.933333,0.774194,1,0.969697,0.787879,0.967742,0.903226,1,0.967742,0.733333,1,0.903226,1,0.344828,0.514286,0.205128,0.909091,1,0.758621,1,0.909091,0.444444,0.457143,0.941176,0.909091,0.967742,0.967742,1,0.933333,0.580645,0.969697,0.848485,0.8125,0.533333,0.903226,0.969697,0.722222,0.909091,1,0.9375,0.941176,0.967742,0.875,0.8125,0.888889,0.83871,0.875,0.75,0.909091,0.764706,0.733333,0.413793,1,0.9375,0.625,0.758621,0.914286,0.914286,0.727273,0.9375,0.903226,0.875,0.457143,1,0.774194,0.848485,0.882353,0.903226,0.685714,1,0.764706,0.969697,0.903226,0.666667,1,1,0.727273,0.903226,0.909091,0.666667,0.83871,0.866667,1,0.866667,0.83871,1,0.758621,0.875,0.866667,0.827586,0.9375,0.967742,0.864865,0.882353,0.5,1] kappa 0.84154 kb_relative_information_score 1400.591464 mean_absolute_error 0.003231 mean_prior_absolute_error 0.0198 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 0.850092 [0.785714,1,1,1,1,0.8,1,0.941176,0.764706,1,0.933333,1,1,0.785714,1,0.933333,1,0.384615,0.473684,0.173913,0.882353,1,0.846154,1,0.882353,0.4,0.421053,0.888889,0.882353,1,1,1,1,0.6,0.941176,0.823529,0.8125,0.571429,0.933333,0.941176,0.65,0.882353,1,0.9375,0.888889,1,0.875,0.8125,0.8,0.866667,0.875,0.75,0.882353,0.722222,0.785714,0.461538,1,0.9375,0.625,0.846154,0.842105,0.842105,0.705882,0.9375,0.933333,0.875,0.421053,1,0.8,0.823529,0.833333,0.933333,0.631579,1,0.722222,0.941176,0.933333,0.818182,1,1,0.705882,0.933333,0.882353,0.647059,0.866667,0.928571,1,0.928571,0.866667,1,0.846154,0.875,0.928571,0.923077,0.9375,1,0.761905,0.833333,0.75,1] predictive_accuracy 0.843125 prior_entropy 6.643856 recall 0.843125 [0.6875,0.9375,1,0.9375,0.875,0.75,1,1,0.8125,0.9375,0.875,1,0.9375,0.6875,1,0.875,1,0.3125,0.5625,0.25,0.9375,1,0.6875,1,0.9375,0.5,0.5,1,0.9375,0.9375,0.9375,1,0.875,0.5625,1,0.875,0.8125,0.5,0.875,1,0.8125,0.9375,1,0.9375,1,0.9375,0.875,0.8125,1,0.8125,0.875,0.75,0.9375,0.8125,0.6875,0.375,1,0.9375,0.625,0.6875,1,1,0.75,0.9375,0.875,0.875,0.5,1,0.75,0.875,0.9375,0.875,0.75,1,0.8125,1,0.875,0.5625,1,1,0.75,0.875,0.9375,0.6875,0.8125,0.8125,1,0.8125,0.8125,1,0.6875,0.875,0.8125,0.75,0.9375,0.9375,1,0.9375,0.375,1] relative_absolute_error 0.163174 root_mean_prior_squared_error 0.099499 root_mean_squared_error 0.05191 root_relative_squared_error 0.521711 total_cost 0 area_under_roc_curve 0.982717 [0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.993671,0.735759,0.987421,1,1,1,1,1,0.996835,0.990506,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.748418,1,1,1,1,0.993711,1,1,1,0.993711,1,1,1,0.993671,1,1,1,0.990506,1,1,0.974843,1,1,1,1,0.993711,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.993671,0.737342,1] area_under_roc_curve 0.989381 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,0.743671,0.990506,0.993711,1,1,1,1,1,0.990506,0.990506,1,1,1,1,1,1,1,1,0.993711,0.987421,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.484277,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.974684,1] area_under_roc_curve 0.985366 [0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.69462,1,1,0.743671,1,1,0.984177,1,1,1,1,1,1,1,0.969937,1,1,1,0.968553,1,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,0.992089,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.742089,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1] area_under_roc_curve 0.988472 [1,1,1,1,0.75,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.981013,0.468553,0.955696,1,1,1,1,1,0.990506,1,1,1,1,1,1,1,0.990506,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,1,0.748418,1,0.981132,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.993711,1] area_under_roc_curve 0.985841 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,0.993671,0.993671,1,1,1,1,1,0.971519,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.987421,0.75,0.987421,0.992089,0.731013,1,0.996835,0.996835,1,1,1,1,1,1,1,0.987421,1,1,0.746835,1,1,1,1,0.748418,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1] area_under_roc_curve 0.989004 [0.987342,1,1,1,1,0.748418,1,1,1,0.75,0.996835,1,1,1,1,1,1,1,1,0.96519,1,1,0.996835,1,0.996835,0.990506,0.987342,1,1,1,1,1,1,1,1,0.748418,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.990506,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.993671,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1] area_under_roc_curve 0.991776 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.971519,0.977848,1,1,0.996835,1,0.996835,0.474843,0.968553,1,1,1,1,1,1,0.981132,1,1,0.993671,0.987342,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.5,1,1,1,1,0.996835,1,1,1,1,1,0.987342,1] area_under_roc_curve 0.985743 [0.990506,1,1,0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.990506,0.974684,0.996835,1,1,1,1,0.993711,1,1,0.996855,1,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.993711,0.996835,1,1,1,0.990506,1,1,1,1,1,1,1,1,1,0.493711,0.987421,1,1,0.996835,1,1,1,1,0.995253,1,1,0.468553,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1] area_under_roc_curve 0.992426 [0.993711,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.993671,0.993711,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,0.993671,0.981013,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.990506,1,0.993711,1,1,1,0.993671,1,1,1,1,1,1,0.993671,1,1,1,1,0.993711,0.987342,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.742089,1] area_under_roc_curve 0.98333 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,0.993711,1,0.987421,1,1,1,1,1,0.981132,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.990506,1,0.996855,1,0.993671,1,0.748418,0.993711,1,1,0.738924,1,0.748418,1,1,1,1,1,1,0.490566,1,0.987421,1,0.996835,1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,1,1] 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 f_measure 0.802708 [0,0.666667,1,1,0.666667,1,1,0.666667,1,1,0.666667,1,1,0,1,1,1,0,0.5,0,1,1,1,1,1,0.8,0.5,0.8,1,1,1,1,0.666667,0,1,0.666667,1,0.666667,1,1,0.666667,0.666667,1,1,1,1,1,0.5,1,0.666667,1,1,1,1,0,0,1,1,0,1,1,0.666667,0.5,0.8,1,1,0.4,1,0.666667,0,1,1,1,1,0,1,0.666667,0,1,1,1,1,1,0.666667,1,0.666667,1,1,0.666667,1,1,1,1,0.666667,1,1,0.666667,0.666667,0.5,1] f_measure 0.843125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,0.666667,1,0.666667,0.5,0.666667,1,1,1,1,1,0.5,0.5,1,0.8,1,1,1,1,1,1,0.666667,0,0.666667,1,1,0.5,1,1,1,1,1,1,1,0.8,1,1,0.666667,0.666667,1,1,0,1,1,1,0.666667,0.666667,0.666667,0.666667,1,1,0.666667,1,1,0,1,0.666667,1,1,1,1,1,0.666667,1,1,1,0,0.8,0.666667,1,0.5,1,1,0.8,0,1,0.666667,1,0.666667,0.666667,1,1,1,1,0,1] f_measure 0.847917 [0.666667,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,0,1,1,0,1,1,0.333333,1,1,1,1,1,1,0.666667,0,1,1,1,0,1,1,0.5,1,1,1,0.8,1,0.666667,1,1,1,1,1,1,0.8,1,0,1,1,0.666667,0.666667,1,1,1,1,1,0.8,0,1,0,1,1,1,0.666667,1,0.666667,1,1,0.5,1,1,0.666667,1,1,0.666667,1,1,1,1,0.8,1,1,1,1,0.666667,1,1,0.8,1,0,1] f_measure 0.832083 [1,1,1,1,0.666667,0.666667,1,1,0.5,1,1,1,1,0.666667,1,1,1,0,0,0,1,1,1,1,0,0.4,0.8,1,1,1,1,1,1,0.666667,1,0.666667,1,0.666667,0.666667,1,0.8,0.666667,1,1,1,1,0.666667,1,0.8,1,1,0.666667,1,0.666667,1,0.666667,1,1,0.666667,1,0.666667,1,1,1,1,1,0,1,1,1,0.666667,1,0,1,1,1,1,0.666667,1,1,1,1,1,0.666667,0,1,1,1,1,1,0.666667,1,0,0.8,1,0,1,0.8,0,1] f_measure 0.812708 [0.666667,1,1,1,1,0.8,1,1,0,1,1,1,1,0.666667,1,1,1,0,0.4,0.5,0.5,1,0.666667,1,1,1,0,1,0.666667,0.666667,1,1,1,0.666667,1,1,1,0.4,1,1,0.8,1,1,0,1,0,1,0.666667,1,1,0,0,0.666667,0.5,0.666667,0.5,1,0.8,0.8,1,1,1,1,1,0.666667,1,0,1,1,0.666667,1,1,0.666667,1,0.666667,1,1,0.666667,1,1,0.666667,1,1,0.666667,0.666667,1,1,1,1,1,1,0.5,1,0,0.666667,1,0.8,1,0.666667,1] f_measure 0.850625 [0.666667,1,1,1,1,0,1,1,0.666667,0.666667,0.8,1,0,0.666667,1,1,1,1,1,0.4,1,1,0.666667,1,0.8,0.4,0.4,1,1,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0.8,1,1,0.666667,1,1,1,0.666667,1,0.666667,1,1,0.8,1,0,0.5,1,1,0.5,1,1,1,0.5,1,1,1,0.666667,1,1,1,1,0.666667,1,1,1,1,0.8,0.666667,1,1,1,0.666667,1,0.5,1,1,1,1,0.8,1,1,1,1,1,1,1,0.8,1,0,1] f_measure 0.808333 [0.8,1,1,1,1,0.666667,1,1,0.666667,1,1,1,1,0.666667,1,0.666667,1,0,0.4,0,1,1,0.5,1,0.8,0,0,1,1,1,0.666667,1,1,0,1,1,0.8,0,1,1,1,0.666667,1,1,1,1,1,0.666667,1,0.666667,1,0.8,1,0.666667,0.666667,0.5,1,0.666667,0,1,0.8,0.8,1,0.666667,0.666667,1,0.666667,1,1,1,1,1,1,1,0.666667,0.666667,1,1,1,1,0.666667,1,0.8,0.666667,1,0.666667,1,0,1,1,0.666667,1,0.666667,1,1,1,1,1,0,1] f_measure 0.825685 [0.666667,1,1,0.666667,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,0,0.571429,0,0.8,1,0.8,1,1,0,0.666667,0.8,0,1,1,1,1,1,0.8,1,0,1,1,0.666667,0.666667,1,1,1,0.666667,1,1,1,0.666667,0,0.666667,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0,1,0.666667,0.8,1,1,0.8,1,0.8,1,1,0,1,1,0.666667,1,0.666667,1,0.666667,0.666667,1,0,1,1,0,1,1,1,1,1,0.8,1,0.666667,1] f_measure 0.828393 [0.666667,1,1,1,1,0.5,1,1,0.5,1,0,1,1,1,1,1,1,0.666667,0.666667,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0.666667,1,1,0.8,0,0.666667,1,0,1,1,1,1,1,0.666667,0.8,0.666667,1,0.666667,0.666667,1,0.5,0.666667,0,1,1,0.666667,0,1,1,0.666667,1,1,1,0.8,1,0.8,1,1,0,0.5,1,1,1,1,1,1,1,0.571429,1,1,0.5,1,1,1,0.666667,1,1,0.666667,0.666667,1,1,0.666667,1,1,0.666667,0.666667,1] f_measure 0.860625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,0,0,0.4,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,1,0.666667,1,0.666667,0.666667,1,1,1,1,1,1,1,0.666667,1,1,0.666667,1,1,1,0.666667,1,1,1,1,0.4,0.666667,1,1,0.4,1,0.666667,1,0.5,1,0.666667,0.666667,0.666667,1,0,1,0.666667,1,1,1,1,1,1,0,1,0,1,0.8,1,1,1,1,0.5,0.8,1,1,1,1,1,1,1,1] kappa 0.816818 kappa 0.854718 kappa 0.854666 kappa 0.835722 kappa 0.823107 kappa 0.861001 kappa 0.823107 kappa 0.842041 kappa 0.835755 kappa 0.867335 kb_relative_information_score 135.203355 kb_relative_information_score 140.82432 kb_relative_information_score 140.898627 kb_relative_information_score 140.991564 kb_relative_information_score 138.453993 kb_relative_information_score 143.685633 kb_relative_information_score 136.297634 kb_relative_information_score 139.34836 kb_relative_information_score 142.529611 kb_relative_information_score 142.358367 mean_absolute_error 0.003775 mean_absolute_error 0.002992 mean_absolute_error 0.003035 mean_absolute_error 0.003229 mean_absolute_error 0.003436 mean_absolute_error 0.002854 mean_absolute_error 0.003743 mean_absolute_error 0.003238 mean_absolute_error 0.003206 mean_absolute_error 0.002801 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 mean_prior_absolute_error 0.0198 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 0.821875 [0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,0,0.5,0,1,1,1,1,1,0.666667,0.5,0.666667,1,1,1,1,1,0,1,0.5,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.333333,1,1,1,1,1,1,0,0,1,1,0,1,1,0.5,0.5,0.666667,1,1,0.333333,1,0.5,0,1,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1] precision 0.866667 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1,0.666667,1,1,1,1,1,1,0.5,0,0.5,1,1,0.333333,1,1,1,1,1,1,1,0.666667,1,1,1,0.5,1,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,1,1,1,1,1,1,1,0,0.666667,0.5,1,0.5,1,1,0.666667,0,1,1,1,1,1,1,1,1,1,0,1] precision 0.863542 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0.25,1,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,1,0.666667,1,1,1,1,1,1,1,1,0.666667,1,0,1,1,0.5,1,1,1,1,1,1,0.666667,0,1,0,1,1,1,0.5,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,1,0.666667,1,0,1] precision 0.861458 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0.333333,0.666667,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0.666667,0.5,1,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0.666667,1,0,1,0.666667,0,1] precision 0.843229 [1,1,1,1,1,0.666667,1,1,0,1,1,1,1,0.5,1,1,1,0,0.25,0.5,0.5,1,1,1,1,1,0,1,0.5,1,1,1,1,1,1,1,1,0.333333,1,1,0.666667,1,1,0,1,0,1,1,1,1,0,0,1,0.333333,0.5,0.5,1,0.666667,0.666667,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,0.666667,1,0.5,1] precision 0.872917 [1,1,1,1,1,0,1,1,0.5,1,0.666667,1,0,0.5,1,1,1,1,1,0.333333,1,1,1,1,0.666667,0.333333,0.333333,1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,1,1,1,1,1,0.666667,1,0,0.5,1,1,0.5,1,1,1,0.333333,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,0.5,1,1,1,1,0.666667,1,1,1,1,1,1,1,0.666667,1,0,1] precision 0.834375 [0.666667,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0.333333,0,1,1,0.5,1,0.666667,0,0,1,1,1,1,1,1,0,1,1,0.666667,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.666667,1,0.5,1,0.5,1,1,0,1,0.666667,0.666667,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.666667,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0,1] precision 0.845625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.4,0,0.666667,1,0.666667,1,1,0,0.5,0.666667,0,1,1,1,1,1,0.666667,1,0,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0.5,0.5,1,1,1,0.5,1,1,1,0.333333,1,1,1,1,1,0,0,1,1,0.666667,1,1,0.666667,1,0.666667,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,0.666667,1,1,1] precision 0.86125 [0.5,1,1,1,1,0.333333,1,1,0.5,1,0,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,1,1,0.666667,0,1,1,0,1,1,1,1,1,0.5,0.666667,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0,0.5,1,1,1,1,1,1,1,0.4,1,1,0.333333,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1] precision 0.881771 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.25,1,1,1,1,1,0,0,1,1,1,1,1,1,0.333333,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.333333,1,1,1,0.333333,1,0.5,1,0.5,1,1,0.5,0.5,1,0,1,1,1,1,1,1,1,1,0,1,0,1,0.666667,1,1,1,1,0.5,0.666667,1,1,1,1,1,1,1,1] predictive_accuracy 0.81875 predictive_accuracy 0.85625 predictive_accuracy 0.85625 predictive_accuracy 0.8375 predictive_accuracy 0.825 predictive_accuracy 0.8625 predictive_accuracy 0.825 predictive_accuracy 0.84375 predictive_accuracy 0.8375 predictive_accuracy 0.86875 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 prior_entropy 6.643856 recall 0.81875 [0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0,1,1,0,1,1,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1] recall 0.85625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,0,1] recall 0.85625 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,0,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1] recall 0.8375 [1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,0,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0,1,1,0,1,1,0,1] recall 0.825 [0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,0,1,0,1,0.5,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1] recall 0.8625 [0.5,1,1,1,1,0,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1] recall 0.825 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0.5,0,1,1,0.5,1,1,0,0,1,1,1,0.5,1,1,0,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1] recall 0.84375 [0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1] recall 0.8375 [1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1] recall 0.86875 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1] relative_absolute_error 0.190648 relative_absolute_error 0.151093 relative_absolute_error 0.153301 relative_absolute_error 0.163056 relative_absolute_error 0.173527 relative_absolute_error 0.144165 relative_absolute_error 0.189065 relative_absolute_error 0.163532 relative_absolute_error 0.161907 relative_absolute_error 0.141445 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_prior_squared_error 0.099499 root_mean_squared_error 0.057316 root_mean_squared_error 0.050656 root_mean_squared_error 0.04981 root_mean_squared_error 0.051015 root_mean_squared_error 0.054551 root_mean_squared_error 0.047678 root_mean_squared_error 0.05532 root_mean_squared_error 0.052561 root_mean_squared_error 0.050585 root_mean_squared_error 0.048792 root_relative_squared_error 0.576045 root_relative_squared_error 0.509107 root_relative_squared_error 0.500611 root_relative_squared_error 0.512721 root_relative_squared_error 0.548254 root_relative_squared_error 0.479186 root_relative_squared_error 0.555984 root_relative_squared_error 0.528257 root_relative_squared_error 0.508397 root_relative_squared_error 0.490379 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