8878280 710 William Raynaut 9956 Supervised Classification 7844 weka.kf.Bagging-IBk5(1) 6833440 mDataExp Modelage study_107 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 18672339 description https://api.openml.org/data/download/18672339/description2243948735609227705.xml -1 18672340 predictions https://api.openml.org/data/download/18672340/predictions6984177534163541401.arff area_under_roc_curve 0.977841 [0.997306,0.999803,0.997789,0.999013,0.972363,0.998973,0.936552,0.951792,0.967901,0.999487,0.999447,0.939672,0.999645,1,0.993466,0.999763,0.969737,0.99925,1,0.94816,1,0.848626,0.999171,0.977989,0.835242,0.943916,0.918509,0.897623,0.999724,0.999763,0.972501,0.999921,0.987603,0.99925,0.999408,0.997078,0.997276,0.999961,0.995045,0.998361,1,0.91008,0.928123,0.861951,0.829458,0.999842,0.926781,0.999921,0.989991,0.998302,0.997868,0.99771,0.99698,0.961387,0.959334,0.988215,1,0.990544,0.999803,1,1,0.999763,0.999763,0.99925,0.999368,0.998421,0.999408,0.983319,1,0.995006,0.998816,0.917739,1,0.926563,0.999724,0.999605,0.995894,0.999961,0.953234,0.9985,0.999921,0.993683,0.930077,0.997828,0.986517,1,0.83005,0.998934,1,0.998381,0.942968,0.990702,0.999645,0.999961,0.987563,0.996723,0.995716,0.999526,1,0.999447] average_cost 0 f_measure 0.773098 [0.827586,0.857143,0.814815,0.769231,0.418605,0.75,0.692308,0.727273,0.875,0.848485,0.83871,0.153846,0.857143,0.933333,0.580645,0.967742,0.551724,0.83871,0.933333,0.896552,0.914286,0.32,0.833333,0.933333,0.285714,0.758621,0.727273,0.466667,0.866667,0.882353,0.83871,0.969697,0.642857,0.820513,0.83871,0.64,0.7,0.864865,0.647059,0.814815,1,0.62069,0.4,0.4375,0.428571,0.914286,0.6875,0.967742,0.727273,0.666667,0.810811,0.848485,0.727273,0.785714,0.685714,0.5,0.969697,0.717949,0.833333,0.967742,1,0.857143,0.814815,0.875,0.875,0.787879,0.969697,0.848485,0.9375,0.733333,0.733333,0.62069,0.941176,0.777778,0.896552,0.896552,0.6,0.933333,0.83871,0.717949,0.967742,0.5,0.571429,0.6,0.742857,0.969697,0.72,0.857143,1,0.780488,0.933333,0.583333,0.875,0.9375,0.789474,0.651163,0.823529,0.9375,0.941176,0.882353] kappa 0.775744 kb_relative_information_score 1340.30397 mean_absolute_error 0.007369 mean_prior_absolute_error 0.0198 number_of_instances 1599 [15,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16] precision 0.791542 [0.857143,0.789474,1,1,0.333333,0.75,0.9,0.705882,0.875,0.823529,0.866667,0.2,0.789474,1,0.6,1,0.615385,0.866667,1,1,0.842105,0.444444,0.75,1,0.6,0.846154,0.705882,0.5,0.928571,0.833333,0.866667,0.941176,0.75,0.695652,0.866667,0.888889,0.583333,0.761905,0.611111,1,1,0.692308,0.428571,0.4375,0.5,0.842105,0.6875,1,0.705882,0.517241,0.714286,0.823529,0.705882,0.916667,0.631579,0.45,0.941176,0.608696,0.75,1,1,0.789474,1,0.875,0.875,0.764706,0.941176,0.823529,0.9375,0.785714,0.785714,0.692308,0.888889,0.7,1,1,0.642857,1,0.866667,0.608696,1,0.75,0.666667,0.642857,0.684211,0.941176,1,0.789474,1,0.64,1,0.875,0.875,0.9375,0.681818,0.518519,0.777778,0.9375,0.888889,0.833333] predictive_accuracy 0.777986 prior_entropy 6.643831 recall 0.777986 [0.8,0.9375,0.6875,0.625,0.5625,0.75,0.5625,0.75,0.875,0.875,0.8125,0.125,0.9375,0.875,0.5625,0.9375,0.5,0.8125,0.875,0.8125,1,0.25,0.9375,0.875,0.1875,0.6875,0.75,0.4375,0.8125,0.9375,0.8125,1,0.5625,1,0.8125,0.5,0.875,1,0.6875,0.6875,1,0.5625,0.375,0.4375,0.375,1,0.6875,0.9375,0.75,0.9375,0.9375,0.875,0.75,0.6875,0.75,0.5625,1,0.875,0.9375,0.9375,1,0.9375,0.6875,0.875,0.875,0.8125,1,0.875,0.9375,0.6875,0.6875,0.5625,1,0.875,0.8125,0.8125,0.5625,0.875,0.8125,0.875,0.9375,0.375,0.5,0.5625,0.8125,1,0.5625,0.9375,1,1,0.875,0.4375,0.875,0.9375,0.9375,0.875,0.875,0.9375,1,0.9375] relative_absolute_error 0.372158 root_mean_prior_squared_error 0.099499 root_mean_squared_error 0.057274 root_relative_squared_error 0.575625 total_cost 0 area_under_roc_curve 0.973814 [1,1,0.993711,1,0.996835,0.993671,0.506329,1,1,1,1,0.772152,1,1,0.987342,1,1,1,1,1,1,0.572785,1,0.803797,0.925633,1,1,1,1,1,0.996835,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.764241,1,0.990506,0.993671,1,1,1,1,0.993711,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,0.996835,1,1,1,1,1,1,0.746835,0.996835,1,1,0.889241,0.993671,1,1,1,1] area_under_roc_curve 0.959421 [1,0.993711,1,1,0.936709,1,1,1,1,1,1,0.987342,1,1,0.990506,1,1,1,1,0.754747,1,0.650316,1,1,0.609177,0.571203,0.619497,0.996835,1,1,1,1,1,1,1,0.993671,1,1,1,0.992089,1,1,0.006289,0.981013,1,1,0.906646,1,1,1,0.993711,1,0.993711,0.996835,0.993711,0.996835,1,1,1,1,1,1,1,1,1,0.996835,1,0.716981,1,0.987342,1,1,1,1,1,1,0.987342,1,1,1,1,0.990506,0.528302,1,1,1,0.511076,1,1,1,1,1,1,1,1,0.996835,0.993711,1,1,1] area_under_roc_curve 0.986297 [1,1,1,1,0.990506,1,0.990506,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,0.990506,1,1,0.968553,1,1,0.993671,1,1,1,1,0.987342,1,1,1,1,1,1,0.993711,1,1,1,0.987342,0.683544,1,0.981013,1,0.996835,0.993711,1,0.996835,0.996835,1,1,1,1,0.974843,1,1,1,1,1,1,1,1,1,1,1,0.981013,0.996835,0.716772,1,1,1,0.993671,1,1,1,0.996835,1,0.974684,0.993711,0.996835,1,1,0.708861,1,1,1,1,0.987342,1,1,1,1,1,1,1,1] area_under_roc_curve 0.969432 [1,1,0.996835,1,1,1,0.996835,1,1,1,1,0.993711,1,1,0.996835,1,0.977848,1,1,1,1,0.572785,1,1,0.31761,1,1,0.613924,1,1,1,1,1,1,1,1,1,1,0.981132,1,1,0.993711,0.974843,1,0.556962,1,1,1,0.993711,1,1,1,0.985759,0.710443,0.700949,0.987342,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.996835,0.849684,1,1,0.996835,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] area_under_roc_curve 0.967665 [1,1,1,1,0.993711,1,1,0.601266,0.968553,1,1,0.676101,1,1,0.937107,1,0.762658,1,1,1,1,0.968553,1,1,1,0.996835,1,0.993711,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.984177,0.681962,0.64557,1,0.757911,1,1,1,0.996835,1,1,0.987421,1,0.925633,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.996835,1,0.993711,1,1,1,1,1,0.974843,1,1,1,0.618671,1,1,0.987421,0.446541,1,1,1,1,1,1,1,1,0.996835] area_under_roc_curve 0.982661 [1,1,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.987421,0.996835,1,0.487421,1,0.987342,0.805031,1,1,0.628931,1,1,1,1,1,1,1,1,1,1,0.518987,1,1,0.996835,1,0.996835,1,1,1,1,0.987421,1,1,0.990506,0.990506,1,0.968354,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,1,1,0.987421,1,1,1,1,0.993711,0.781646,0.993711,0.996835,1,1,0.981132,1,0.993711,1,1,1,1,1,1,0.981013,1,1,1] area_under_roc_curve 0.982781 [1,1,1,1,1,1,1,1,1,1,0.996835,0.931962,1,1,1,1,1,1,1,1,1,0.987421,0.993711,1,1,1,1,0.415094,1,1,1,1,1,1,0.993671,1,0.990506,1,0.984177,1,1,1,0.981013,1,0.704114,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,0.431962,1,1,1,1,1,1,1,1,0.968354,0.993711,1,1,1,1,1,1,1,0.921384,1,1,0.987421,1,1,1,1,1] area_under_roc_curve 0.972306 [0.955975,1,0.996835,1,0.987421,1,1,1,0.77057,1,1,1,1,1,1,1,0.981132,1,1,0.846519,1,1,1,1,0.837025,1,0.561709,0.974843,1,1,1,1,0.938291,1,1,0.990506,0.996835,1,0.993671,1,1,1,0.984177,0.122642,1,1,0.993711,1,1,1,1,1,1,1,1,0.993711,1,1,0.993671,1,1,1,1,1,1,0.996835,1,0.996835,1,1,1,1,1,1,1,1,0.993711,1,0.672468,0.996835,1,0.993711,0.996835,1,0.920886,1,0.597484,1,1,1,1,1,1,1,1,0.996835,1,1,1,1] area_under_roc_curve 0.990812 [0.974843,1,1,0.996835,0.987342,1,1,1,1,1,1,0.993671,1,1,0.993671,0.996835,0.993711,1,1,1,1,0.981013,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.996835,0.990506,1,1,1,1,1,0.996835,0.31761,0.993711,1,1,1,0.931962,1,1,1,0.993711,0.996835,0.987342,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,1,1,0.996835,0.816456,1,1,1,1,1,1,1,1,1,1,0.990506,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1] area_under_roc_curve 0.993758 [1,1,1,0.996815,0.909236,1,1,1,1,1,1,0.968153,1,1,0.996815,1,0.981013,1,1,1,1,1,1,1,0.980892,1,1,0.996815,1,1,1,1,0.993671,0.993671,1,1,1,1,1,1,1,0.786624,0.984076,0.987342,0.974684,1,0.882911,1,1,1,0.996815,1,1,1,1,1,1,0.990446,1,1,1,1,1,1,1,0.996815,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993631,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] 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 0.745208 [1,1,0,0.666667,0.666667,0.5,0,1,1,0.8,0.666667,0,0.666667,1,0.5,1,1,1,1,1,1,0,1,0.666667,0.666667,1,1,0.8,1,0,0.8,1,0.666667,1,1,0.666667,0.666667,0.666667,0.666667,0.666667,1,0.5,0,0.666667,0,1,0.666667,1,0.5,0.666667,0.666667,1,1,0.666667,0.5,0.5,1,0.4,1,1,1,1,1,1,0.666667,1,1,1,0.666667,0.666667,0,0.666667,0.666667,1,1,1,0.666667,1,1,0.5,1,0.8,0.666667,0.666667,0.666667,1,0,1,1,0.8,0.666667,0.666667,0.666667,1,0.5,0.5,0.666667,1,1,1] f_measure 0.697083 [1,0.666667,1,0.666667,0,0,0.8,0.666667,1,0.8,1,0,1,1,0.4,1,0.666667,0.666667,1,0.666667,0.8,0,0.5,0.666667,0.5,0,0,0.8,1,0.8,0.666667,1,1,0.5,0,0.5,1,0.666667,1,0.666667,1,1,0,0,1,1,0.666667,1,0.666667,1,0.666667,0.8,0.5,0.5,0.666667,0.5,1,1,1,1,1,0.666667,1,0,1,0.666667,1,0,1,0.5,1,1,1,1,0.666667,0.666667,0.5,1,1,1,1,0,0,1,0.666667,1,0,0.8,1,0.8,1,0,1,0.666667,1,0.8,1,1,1,0] f_measure 0.784851 [1,1,1,1,0.571429,1,0,1,1,1,1,0,1,0.666667,1,1,0.8,1,1,1,1,0.4,1,1,0,0.666667,1,0,1,1,1,1,0,1,1,1,0.666667,1,0.4,0,1,1,1,0.666667,0,1,0.8,1,0.5,0.333333,1,0.666667,0.666667,1,0.666667,1,1,0,0.666667,1,1,0.5,1,0,1,0.666667,1,1,1,0.666667,0.5,0.666667,1,1,1,0.666667,1,1,1,0.666667,1,0,0.5,0.8,0.5,1,0.666667,0.666667,1,1,1,0,1,1,0.8,1,1,1,1,0.666667] f_measure 0.775625 [0.8,0,0.666667,1,0.5,1,0.666667,0.666667,1,1,1,0,1,0.666667,0.666667,1,0.666667,0.8,1,1,1,0.666667,1,1,0,0.666667,0.5,0,0.666667,1,1,1,1,1,1,1,0.5,1,0,1,1,0,0,0.666667,0.666667,0.8,1,0.666667,0.666667,0.5,1,1,0.666667,0.666667,0.666667,0,1,0.666667,0.666667,1,1,1,1,1,1,1,0.8,0.666667,1,1,0.5,0,1,1,0.666667,0.666667,0.666667,1,0.8,1,1,0.666667,1,1,1,1,1,0.5,1,1,1,0.666667,0.666667,1,0.666667,0.5,0.5,1,0.8,0.666667] f_measure 0.722917 [0.666667,0.8,0.666667,1,0.4,0.666667,1,0,0,0,0.666667,0,0,1,0,1,0,0,1,1,1,0,1,1,0,0.5,0.666667,0.666667,0,1,1,1,0.8,0.8,0.666667,1,0.8,1,0.666667,0,1,0.8,0.4,0,0.4,1,0.666667,1,1,0.666667,0.666667,1,1,0,0.666667,0,1,0.8,1,1,1,1,1,0.8,0.666667,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0.666667,1,1,0.8,0.666667,0.666667,0,0,0.8,1,0.666667,1,1,0.5,0,1,1,0,1,0.5,1,1,1,0.8] f_measure 0.769435 [1,1,0.666667,0,0.333333,1,1,0.666667,1,1,1,0.666667,0.666667,1,1,1,0.666667,1,0.666667,1,1,0,0.8,1,0,1,0,0,1,0.8,0,1,1,0.8,1,1,0.8,1,0.666667,1,1,0,1,0.8,0.666667,1,0.5,1,1,0.4,0.571429,0,0.666667,1,0.5,0.4,1,0.666667,1,1,1,1,0,1,1,1,1,1,1,0.666667,1,0,1,0.666667,1,1,0,1,1,0.666667,1,0.666667,0,0,0.666667,1,1,0,1,0.5,1,0.666667,0.666667,1,1,1,0.666667,0.8,1,1] f_measure 0.75875 [0.666667,1,1,0,0.666667,1,1,0.8,0.8,1,0.5,0,1,1,0,1,0,1,1,1,1,0,0,1,0.666667,1,0.8,0,1,0.8,0,1,0,1,0.5,0.666667,0.5,0.8,0.666667,1,1,1,0,0.666667,0,1,1,1,0.666667,1,1,0.666667,0.666667,1,1,1,1,1,0.8,1,1,1,0.666667,0.8,1,0.5,1,1,1,1,1,0.666667,1,0,1,1,0.666667,0.666667,1,0.8,1,0,0,0,0.666667,0.666667,1,1,1,0.666667,1,0,1,1,0.5,0.666667,0.8,1,0.666667,1] f_measure 0.708601 [0,1,0.666667,1,0,0.666667,1,0.8,0.5,0,0.666667,0,1,1,0.666667,1,0,0.666667,0,0.666667,1,1,1,1,0,1,0.666667,0,1,1,1,1,0,1,1,0,0.666667,0.8,0.666667,1,1,0,0,0,1,0.8,0.5,1,1,0.666667,1,1,1,1,0.8,0.5,1,1,0.4,0.666667,1,0.666667,1,1,0.666667,0.666667,1,0.5,1,0.5,0.666667,0,1,1,0,1,0,0.666667,0,0.5,1,0,0.8,0,0.5,1,0,1,1,1,1,1,1,1,1,0.571429,0.8,1,1,1] f_measure 0.730417 [0,0.8,1,0.666667,0.666667,0.666667,0.666667,0.666667,1,1,1,0.666667,1,1,0.666667,0.666667,0.666667,1,1,1,0.666667,0,1,1,0,0.666667,1,1,0.666667,1,0.8,0.8,0,0.666667,1,0.666667,0.5,0.666667,1,0.666667,1,0.666667,0.666667,0,0,0.666667,1,1,0.5,0.666667,1,0.666667,0.4,0.666667,0.5,0.5,1,0.8,1,1,1,1,0,1,0.666667,1,1,1,0.666667,0,0.666667,0.5,0.666667,0.8,1,1,0,1,0,0.5,1,0,0.666667,0,1,1,1,1,1,0.8,1,0,0.666667,1,0.8,0.8,1,0,1,1] f_measure 0.828781 [1,0.8,1,0.666667,0,1,0.666667,1,1,1,1,0,0.8,1,0.5,1,0,1,1,0.666667,0.666667,0.666667,1,1,0,1,1,0,1,1,1,1,0.666667,0.5,1,0,1,1,0.666667,1,1,0.666667,0.666667,0,0,1,0,1,1,1,0.8,1,1,1,1,0.666667,0.8,0.666667,1,1,1,1,1,1,1,0.666667,1,0.8,1,1,1,1,1,0.8,1,1,0.8,1,1,1,1,0.666667,1,1,1,1,1,1,1,1,1,1,1,1,0.8,0.571429,1,1,1,1] kappa 0.76634 kappa 0.722069 kappa 0.804216 kappa 0.778962 kappa 0.759921 kappa 0.791519 kappa 0.791535 kappa 0.740947 kappa 0.753671 kappa 0.847409 kb_relative_information_score 134.01213 kb_relative_information_score 129.05884 kb_relative_information_score 134.975839 kb_relative_information_score 133.73237 kb_relative_information_score 131.771504 kb_relative_information_score 135.714281 kb_relative_information_score 135.93626 kb_relative_information_score 131.007161 kb_relative_information_score 135.912351 kb_relative_information_score 138.183233 mean_absolute_error 0.007319 mean_absolute_error 0.007955 mean_absolute_error 0.007401 mean_absolute_error 0.007428 mean_absolute_error 0.007599 mean_absolute_error 0.006874 mean_absolute_error 0.007078 mean_absolute_error 0.007703 mean_absolute_error 0.007581 mean_absolute_error 0.006745 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 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,1,2,2,2,2,1,1,2,2,1,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,2,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1] number_of_instances 160 [2,1,1,2,2,2,2,1,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,1,1,2,1,1,2,2,2,1,1,2,1,1,2,1,2,2,1,2,1,2,1,2,1,1,1,1,1,2,1,1,2,2,2,1,1,2,2,2,1,1,2,2,2,2,1,1,1,2,1,2,1,2,2,2,2,2,2,2,1,1,2,2,1,1,2,1] number_of_instances 160 [2,1,2,2,2,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,1,1,2,2,2,1,2,1,1,1,1,2,1,1,1,2,2,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,2,1,1,2,2,1] number_of_instances 160 [2,1,2,2,2,1,2,2,1,2,2,1,2,2,2,2,2,2,2,1,2,2,2,1,1,2,1,2,2,2,2,1,2,2,2,1,1,2,1,1,2,1,1,2,2,2,2,2,1,1,1,2,2,2,2,2,1,1,1,1,2,1,1,1,2,1,2,1,1,2,2,2,2,1,2,2,2,1,2,2,1,2,1,2,1,2,2,1,2,1,1,2,2,1,1,1,2,2,2,1] number_of_instances 160 [2,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,2,2,1,2,2,1,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,2,1,1,2,2,2,1,2,1,1,2,2,1,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,1,1,2,1,1,2,1,1,2,1,1,2,2,2,1,2,1,2,1,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,1,2,2,2,2,2,2,2,2,1,1,2,1,2,1,2,2,2,2,2,2,2,1,2,2,1,1,2,2,2,2,1,1,2,2,2,1,1,1,2,2,2,1,2,1,2,2,2,1,2,1,1,2,2,2,1,1,2,2,2,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,1,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,1,2,2,2,1,2] number_of_instances 160 [1,2,2,1,1,2,1,2,2,1,2,2,1,1,1,1,1,2,1,2,1,1,1,2,2,1,2,1,1,1,1,2,2,2,2,2,2,2,2,2,1,2,2,1,2,2,1,2,2,2,2,1,2,1,2,1,2,2,2,2,2,2,2,2,1,2,1,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,1,2,1,1,2,1,2,2,1,2,2,2,2,2,2,1,2] number_of_instances 160 [1,2,1,2,2,2,2,2,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,1,1,2,2,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,1,2,2,2,1,1,2,1,2,2,1,1,2,2,2,2,1,1,2] number_of_instances 159 [1,2,1,2,2,2,2,1,2,2,1,2,2,1,2,2,1,1,1,2,1,2,1,2,2,1,2,2,1,1,2,2,1,1,1,2,2,1,2,2,1,2,2,1,1,1,1,1,2,2,2,2,1,2,1,1,2,2,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,2,1,2,2,2,1,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,2,1,1,1,2] precision 0.786979 [1,1,0,1,0.5,0.5,0,1,1,0.666667,0.5,0,0.5,1,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.666667,1,0,0.666667,1,0.5,1,1,1,0.5,0.5,1,1,1,0.333333,0,1,0,1,1,1,0.5,0.5,0.5,1,1,1,0.333333,0.5,1,0.25,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,1,1,1,1,1,1,0.333333,1,0.666667,1,1,0.5,1,0,1,1,0.666667,1,1,0.5,1,0.5,0.5,0.5,1,1,1] precision 0.71875 [1,0.5,1,1,0,0,0.666667,0.5,1,0.666667,1,0,1,1,0.333333,1,1,0.5,1,1,0.666667,0,0.333333,1,0.5,0,0,0.666667,1,0.666667,1,1,1,0.333333,0,0.5,1,0.5,1,1,1,1,0,0,1,1,1,1,1,1,0.5,0.666667,0.333333,0.5,0.5,0.5,1,1,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0,0,1,0.5,1,0,0.666667,1,0.666667,1,0,1,0.5,1,0.666667,1,1,1,0] precision 0.810937 [1,1,1,1,0.4,1,0,1,1,1,1,0,1,1,1,1,0.666667,1,1,1,1,0.333333,1,1,0,1,1,0,1,1,1,1,0,1,1,1,0.5,1,0.25,0,1,1,1,1,0,1,0.666667,1,0.5,0.2,1,1,1,1,0.5,1,1,0,0.5,1,1,0.333333,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,0.333333,0.666667,0.333333,1,1,0.5,1,1,1,0,1,1,0.666667,1,1,1,1,0.5] precision 0.835417 [0.666667,0,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.666667,1,1,1,1,1,1,0,1,0.333333,0,1,1,1,1,1,1,1,1,0.333333,1,0,1,1,0,0,0.5,1,0.666667,1,1,0.5,0.333333,1,1,1,1,1,0,1,0.5,0.5,1,1,1,1,1,1,1,0.666667,0.5,1,1,0.5,0,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,1,1,0.333333,1,1,1,1,1,1,0.5,0.333333,0.5,1,0.666667,0.5] precision 0.731771 [1,0.666667,1,1,0.25,0.5,1,0,0,0,1,0,0,1,0,1,0,0,1,1,1,0,1,1,0,0.5,0.5,0.5,0,1,1,1,0.666667,0.666667,1,1,0.666667,1,0.5,0,1,0.666667,0.333333,0,0.333333,1,1,1,1,0.5,1,1,1,0,1,0,1,0.666667,1,1,1,1,1,0.666667,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5,1,1,0.666667,1,1,0,0,0.666667,1,1,1,1,0.333333,0,1,1,0,1,0.333333,1,1,1,0.666667] precision 0.795312 [1,1,1,0,0.2,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0,0.666667,1,0,1,0,0,1,0.666667,0,1,1,0.666667,1,1,0.666667,1,0.5,1,1,0,1,0.666667,1,1,0.5,1,1,0.25,0.4,0,1,1,0.5,0.333333,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0,1,1,0.5,1,0.5,0,0,1,1,1,0,1,0.333333,1,1,1,1,1,1,1,0.666667,1,1] precision 0.763542 [0.5,1,1,0,0.5,1,1,0.666667,0.666667,1,0.5,0,1,1,0,1,0,1,1,1,1,0,0,1,1,1,0.666667,0,1,0.666667,0,1,0,1,0.5,1,0.5,0.666667,1,1,1,1,0,0.5,0,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,0.666667,1,1,1,1,0.666667,1,0.333333,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,0.666667,1,0,0,0,1,0.5,1,1,1,0.5,1,0,1,1,0.333333,1,0.666667,1,0.5,1] precision 0.718542 [0,1,1,1,0,1,1,0.666667,0.5,0,1,0,1,1,0.5,1,0,1,0,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,0,0.5,0.666667,1,1,1,0,0,0,1,0.666667,0.333333,1,1,0.5,1,1,1,1,0.666667,0.333333,1,1,0.333333,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0.333333,0.5,0,1,1,0,1,0,1,0,0.5,1,0,0.666667,0,0.5,1,0,1,1,1,1,1,1,1,1,0.4,0.666667,1,1,1] precision 0.766146 [0,0.666667,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0,1,1,0,0.5,1,1,0.5,1,0.666667,0.666667,0,0.5,1,1,0.5,0.5,1,1,1,1,1,0,0,0.5,1,1,0.5,1,1,0.5,0.25,1,0.5,0.333333,1,0.666667,1,1,1,1,0,1,1,1,1,1,1,0,1,0.5,0.5,0.666667,1,1,0,1,0,0.333333,1,0,1,0,1,1,1,1,1,0.666667,1,0,0.5,1,0.666667,0.666667,1,0,1,1] precision 0.844654 [1,0.666667,1,1,0,1,1,1,1,1,1,0,0.666667,1,0.5,1,0,1,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,0.5,0.333333,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0.666667,1,1,1,1,0.5,0.666667,0.5,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,0.666667,1,1,0.666667,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,0.4,1,1,1,1] predictive_accuracy 0.76875 predictive_accuracy 0.725 predictive_accuracy 0.80625 predictive_accuracy 0.78125 predictive_accuracy 0.7625 predictive_accuracy 0.79375 predictive_accuracy 0.79375 predictive_accuracy 0.74375 predictive_accuracy 0.75625 predictive_accuracy 0.849057 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 prior_entropy 6.643831 recall 0.76875 [1,1,0,0.5,1,0.5,0,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0,1,0.5,0.5,1,1,1,1,0,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,0,0.5,0,1,0.5,1,0.5,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1] recall 0.725 [1,1,1,0.5,0,0,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,0.5,1,0,1,0.5,0.5,0,0,1,1,1,0.5,1,1,1,0,0.5,1,1,1,0.5,1,1,0,0,1,1,0.5,1,0.5,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,1,0,1,0.5,1,1,1,1,0.5,0.5,0.5,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,0] recall 0.80625 [1,1,1,1,1,1,0,1,1,1,1,0,1,0.5,1,1,1,1,1,1,1,0.5,1,1,0,0.5,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0.5,0,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,0,1,1,1,1,1,0,1,0.5,1,1,1,0.5,0.5,0.5,1,1,1,0.5,1,1,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.78125 [1,0,0.5,1,0.5,1,0.5,0.5,1,1,1,0,1,0.5,0.5,1,0.5,1,1,1,1,0.5,1,1,0,0.5,1,0,0.5,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,0.5,1,1,0.5,1,1,1,1,0.5,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0,1,1,0.5,0.5,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1] recall 0.7625 [0.5,1,0.5,1,1,1,1,0,0,0,0.5,0,0,1,0,1,0,0,1,1,1,0,1,1,0,0.5,1,1,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,0,0.5,1,0.5,1,1,1,0.5,1,1,0,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0,0,1,1,0.5,1,1,1,0,1,1,0,1,1,1,1,1,1] recall 0.79375 [1,1,0.5,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,1,1,1,0,0.5,1,0.5,0.5,1,0.5,1,1,1,1,0,1,1,1,1,1,1,0.5,1,0,1,1,1,1,0,1,1,1,1,1,0,0,0.5,1,1,0,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1] recall 0.79375 [1,1,1,0,1,1,1,1,1,1,0.5,0,1,1,0,1,0,1,1,1,1,0,0,1,0.5,1,1,0,1,1,0,1,0,1,0.5,0.5,0.5,1,0.5,1,1,1,0,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,0,0,0,0.5,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1] recall 0.74375 [0,1,0.5,1,0,0.5,1,1,0.5,0,0.5,0,1,1,1,1,0,0.5,0,0.5,1,1,1,1,0,1,0.5,0,1,1,1,1,0,1,1,0,1,1,0.5,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,0,1,0,0.5,0,0.5,1,0,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1] recall 0.75625 [0,1,1,0.5,0.5,1,0.5,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0.5,1,1,0.5,1,0.5,0.5,0,0,1,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,0,0.5,0.5,1,1,1,1,0,1,0,1,1,0,0.5,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1] recall 0.849057 [1,1,1,0.5,0,1,0.5,1,1,1,1,0,1,1,0.5,1,0,1,1,0.5,1,0.5,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] relative_absolute_error 0.369654 relative_absolute_error 0.401762 relative_absolute_error 0.373808 relative_absolute_error 0.375151 relative_absolute_error 0.38378 relative_absolute_error 0.347156 relative_absolute_error 0.357488 relative_absolute_error 0.38903 relative_absolute_error 0.382883 relative_absolute_error 0.340671 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 0.057301 root_mean_squared_error 0.061655 root_mean_squared_error 0.056381 root_mean_squared_error 0.058004 root_mean_squared_error 0.059227 root_mean_squared_error 0.055517 root_mean_squared_error 0.054777 root_mean_squared_error 0.058811 root_mean_squared_error 0.05856 root_mean_squared_error 0.051893 root_relative_squared_error 0.575894 root_relative_squared_error 0.619652 root_relative_squared_error 0.566651 root_relative_squared_error 0.58296 root_relative_squared_error 0.595257 root_relative_squared_error 0.557966 root_relative_squared_error 0.550532 root_relative_squared_error 0.591072 root_relative_squared_error 0.588556 root_relative_squared_error 0.521542 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