521124 64 Rafael Gomes Mantovani 9956 Supervised Classification 2605 classif.sda(7) 3510 seed 1 2605 kind Mersenne-Twister 2605 normal.kind Inversion 2605 study_7 1493 one-hundred-plants-texture https://www.openml.org/data/download/1592285/phpoOxxNn -1 1791609 description https://api.openml.org/data/download/1791609/file3c9b2133f4e0 -1 1791610 predictions https://api.openml.org/data/download/1791610/file3c9b622f676b area_under_roc_curve 0.884082 [0.864457,0.968118,0.875,0.875,0.746526,0.874684,0.811868,0.717171,0.905618,0.937184,0.936868,0.528407,0.968118,0.936552,0.843434,0.968434,0.778091,0.904987,0.905934,0.90625,0.999368,0.686868,0.874052,0.9375,0.684026,0.842171,0.778723,0.623737,0.905618,0.967171,0.749368,0.999368,0.810921,0.935605,0.812184,0.716539,0.935289,0.904671,0.904039,0.84375,0.999684,0.779987,0.713696,0.778407,0.780302,0.937184,0.779039,0.96875,0.90625,0.966855,0.904039,0.999052,0.904987,0.874684,0.903091,0.809657,0.999368,0.86963,0.936552,1,1,0.936552,0.843434,0.905302,0.905934,0.905618,0.999052,0.936868,0.9375,0.903091,0.936552,0.748421,0.999368,0.904039,0.9375,0.874684,0.905618,0.905618,0.905618,0.874368,0.937184,0.811237,0.714328,0.935605,0.966855,0.96875,0.780934,0.999052,0.9375,0.966539,0.9375,0.780618,0.936552,0.96875,0.936552,0.904671,0.904671,0.936868,0.90625,0.936552] average_cost 0 f_measure 0.770374 [0.666667,0.909091,0.857143,0.857143,0.457143,0.827586,0.714286,0.5,0.83871,0.903226,0.875,0.076923,0.909091,0.848485,0.785714,0.9375,0.514286,0.787879,0.866667,0.896552,0.941176,0.5,0.774194,0.933333,0.363636,0.6875,0.545455,0.333333,0.83871,0.833333,0.615385,0.941176,0.645161,0.777778,0.740741,0.466667,0.756757,0.764706,0.722222,0.814815,0.969697,0.62069,0.358974,0.529412,0.642857,0.903226,0.5625,0.967742,0.896552,0.810811,0.722222,0.914286,0.787879,0.827586,0.666667,0.571429,0.941176,0.533333,0.848485,1,1,0.848485,0.785714,0.8125,0.866667,0.83871,0.914286,0.875,0.933333,0.666667,0.848485,0.551724,0.941176,0.722222,0.933333,0.827586,0.83871,0.83871,0.83871,0.8,0.903226,0.666667,0.378378,0.777778,0.810811,0.967742,0.692308,0.914286,0.933333,0.789474,0.933333,0.666667,0.848485,0.967742,0.848485,0.764706,0.764706,0.875,0.896552,0.848485] kappa 0.768163 kb_relative_information_score 1231.191171 mean_absolute_error 0.00459 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 0.786074 [0.611111,0.882353,1,1,0.421053,0.923077,0.833333,0.583333,0.866667,0.933333,0.875,0.1,0.882353,0.823529,0.916667,0.9375,0.473684,0.764706,0.928571,1,0.888889,0.75,0.8,1,0.352941,0.6875,0.529412,0.5,0.866667,0.75,0.8,0.888889,0.666667,0.7,0.909091,0.5,0.666667,0.722222,0.65,1,0.941176,0.692308,0.304348,0.5,0.75,0.933333,0.5625,1,1,0.714286,0.65,0.842105,0.764706,0.923077,0.565217,0.526316,0.888889,0.413793,0.823529,1,1,0.823529,0.916667,0.8125,0.928571,0.866667,0.842105,0.875,1,0.565217,0.823529,0.615385,0.888889,0.65,1,0.923077,0.866667,0.866667,0.866667,0.857143,0.933333,0.714286,0.333333,0.7,0.714286,1,0.9,0.842105,1,0.681818,1,0.818182,0.823529,1,0.823529,0.722222,0.722222,0.875,1,0.823529] predictive_accuracy 0.770482 prior_entropy 6.643831 recall 0.770482 [0.733333,0.9375,0.75,0.75,0.5,0.75,0.625,0.4375,0.8125,0.875,0.875,0.0625,0.9375,0.875,0.6875,0.9375,0.5625,0.8125,0.8125,0.8125,1,0.375,0.75,0.875,0.375,0.6875,0.5625,0.25,0.8125,0.9375,0.5,1,0.625,0.875,0.625,0.4375,0.875,0.8125,0.8125,0.6875,1,0.5625,0.4375,0.5625,0.5625,0.875,0.5625,0.9375,0.8125,0.9375,0.8125,1,0.8125,0.75,0.8125,0.625,1,0.75,0.875,1,1,0.875,0.6875,0.8125,0.8125,0.8125,1,0.875,0.875,0.8125,0.875,0.5,1,0.8125,0.875,0.75,0.8125,0.8125,0.8125,0.75,0.875,0.625,0.4375,0.875,0.9375,0.9375,0.5625,1,0.875,0.9375,0.875,0.5625,0.875,0.9375,0.875,0.8125,0.8125,0.875,0.8125,0.875] relative_absolute_error 0.231837 root_mean_prior_squared_error 0.099499 root_mean_squared_error 0.067752 root_relative_squared_error 0.680936 total_cost 0 usercpu_time_millis 2.358 usercpu_time_millis_testing 0.0679999999999996 usercpu_time_millis_training 2.29 area_under_roc_curve 0.889658 [1,1,0.5,1,0.75,0.746835,0.5,0.5,1,1,0.996855,0.493671,0.996835,1,0.75,1,0.987342,0.996855,1,1,1,0.75,1,0.75,0.75,1,0.993711,0.5,1,0.5,0.746835,1,1,1,0.5,1,0.996855,1,0.746835,0.75,1,0.993711,0.493711,0.75,1,1,0.75,1,1,0.996835,0.996855,1,0.996855,1,0.993711,0.75,1,0.487421,1,1,1,1,1,1,0.75,1,1,1,1,1,0.75,1,0.996855,1,1,1,0.75,1,1,0.996855,0.996855,0.75,0.996835,0.75,1,1,0.5,1,1,0.996835,0.75,0.75,1,1,0.75,0.746835,0.996855,1,1,1] area_under_roc_curve 0.877 [1,1,1,1,0.496835,0.5,1,0.996855,1,1,1,0.746835,1,1,0.75,1,0.746835,1,1,0.75,1,0.75,0.993671,1,0.743671,0.496835,0.493711,0.743671,0.75,0.996835,0.5,1,0.993711,0.993711,0.496855,0.746835,1,0.996855,1,0.75,1,0.5,0.496855,0.746835,1,1,0.746835,1,1,1,0.996855,1,0.996855,0.996835,0.993711,1,0.996855,0.990566,1,1,1,0.75,0.996855,0.496855,1,0.75,1,0.5,1,0.75,1,0.75,1,1,1,0.75,0.746835,1,1,1,1,0.996835,0.496855,1,1,1,0.5,0.996835,0.75,1,1,0.75,1,1,1,0.75,0.5,1,1,1] area_under_roc_curve 0.880165 [1,1,1,1,0.990506,1,1,1,1,1,1,0.496855,1,0.75,0.996835,1,0.746835,0.75,1,1,1,0.746835,0.75,1,0.496855,0.75,1,0.75,1,1,0.75,1,0.5,0.75,0.75,0.493711,1,1,0.993711,0.5,1,1,0.996855,0.75,0.743671,0.75,0.496835,1,0.75,0.993711,0.996855,0.996835,0.75,1,0.996855,0.75,1,0.493711,1,1,1,1,0.5,0.996855,1,0.75,0.996835,1,1,0.746835,0.996835,0.75,1,1,1,0.75,1,1,1,0.75,1,0.5,0.490566,0.996835,0.990566,0.75,0.75,1,0.75,1,1,0.75,0.996835,1,0.996835,1,1,0.996835,1,0.996855] area_under_roc_curve 0.861177 [0.75,1,0.75,1,0.996835,0.5,0.5,0.496835,0.996855,1,0.996835,0.5,1,0.75,0.75,1,0.75,0.993671,0.75,1,1,0.496835,1,1,0.490566,0.746835,0.996855,0.5,1,0.996835,1,0.996855,0.75,1,0.75,0.496855,0.990566,0.75,0.496855,1,1,0.496855,0.496855,0.990506,0.75,1,0.996835,1,0.5,0.993711,1,1,0.75,0.75,0.746835,0.743671,1,0.993711,1,1,1,0.5,1,0.5,1,0.996855,0.996835,1,1,0.990506,0.996835,0.496835,1,1,0.75,0.75,0.75,0.5,0.75,1,1,0.746835,0.5,1,1,1,1,0.996855,1,1,1,1,0.75,1,1,0.996855,0.996835,0.75,1,0.996855] area_under_roc_curve 0.886295 [0.996835,0.996835,0.75,1,0.993711,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,0.5,1,0.5,0.5,0.746835,0.746835,0.996855,0.743671,1,1,1,0.996835,0.996835,1,1,1,1,0.996855,0.5,0.996835,0.996835,0.743671,0.746835,0.746835,0.75,0.75,1,1,0.996855,0.75,1,1,0.5,0.746835,0.75,1,1,1,1,1,1,1,0.996835,0.996855,1,1,1,1,0.987342,1,1,1,0.740506,1,1,0.996855,1,1,1,0.5,1,0.493711,1,0.996835,1,0.75,1,1,0.996855,0.5,0.75,1,0.5,1,0.996855,0.75,1,0.5,0.996835] area_under_roc_curve 0.908546 [1,1,1,0.5,0.990566,1,1,0.75,1,1,1,0.5,1,1,1,0.996855,0.996835,1,0.75,1,1,0.5,0.746835,1,0.993711,1,0.5,0.5,1,1,0.496855,1,0.996835,1,0.75,0.996855,0.996835,1,1,1,1,0.75,0.75,0.996835,0.75,1,0.746835,0.75,1,1,0.993671,0.996855,1,1,0.746835,0.993671,1,0.75,0.75,1,1,1,0.5,1,1,1,1,1,1,1,1,0.993711,1,1,0.75,1,1,1,1,1,1,0.5,0.5,0.993711,0.75,1,1,0.996855,1,0.996855,1,0.746835,0.75,1,1,0.996855,0.75,0.996835,1,1] area_under_roc_curve 0.892564 [0.993711,1,1,1,0.5,1,0.5,0.75,0.996835,1,0.75,0.496835,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0.746835,0.996835,0.75,0.5,0.5,0.996835,0.5,1,0.746835,1,0.75,0.746835,0.746835,0.993671,0.996835,1,1,1,0.737342,0.996855,0.5,1,1,1,1,1,0.996835,1,0.746835,0.5,1,0.5,0.996835,0.993671,1,1,1,1,1,0.75,0.5,1,1,1,0.5,0.996855,1,0.996855,1,0.496835,1,0.996855,1,0.743671,1,1,1,1,0.5,1,1,1,1,1,1,0.993671,1,0.5,1,1,0.993711,1,0.996835,1,1,1] area_under_roc_curve 0.854789 [0.493711,1,0.75,1,0.496855,1,0.493711,0.996835,0.5,0.5,0.75,0.493671,1,0.996855,1,1,0.493711,0.746835,0.496855,0.75,1,0.5,1,1,0.496835,1,0.743671,0.496855,1,0.996855,0.5,1,0.5,1,1,0.5,0.996835,0.5,0.75,1,1,0.5,0.493671,0.5,1,1,0.993711,1,1,1,0.75,1,0.996835,1,0.996835,0.493711,1,0.996835,0.746835,1,1,0.993671,1,1,1,0.996835,0.996855,0.746835,1,1,0.996855,0.5,1,1,1,0.5,1,0.75,0.746835,0.496835,1,1,0.987342,1,0.996835,1,0.496855,1,1,0.75,1,1,1,1,1,0.746835,0.993671,1,1,0.75] area_under_roc_curve 0.880105 [0.493711,0.996835,1,0.5,0.75,1,1,0.493671,0.75,1,1,0.496835,0.996835,0.996855,0.75,0.75,1,1,1,1,0.996855,0.75,1,1,0.746835,1,1,0.5,1,0.996855,0.75,0.996835,1,0.996855,1,0.746835,0.75,0.996855,1,0.75,1,0.75,0.996835,0.496855,0.5,0.996855,0.996855,1,0.75,0.75,1,0.996855,1,0.75,0.996835,0.990566,1,0.996835,1,1,1,1,0.5,1,0.75,1,1,1,1,0.5,0.75,0.496835,0.996855,0.990506,1,1,1,1,0.5,1,1,0.493711,0.743671,0.993671,0.996835,1,1,1,1,1,1,1,0.996855,1,0.75,1,1,0.5,1,0.75] area_under_roc_curve 0.91107 [0.5,0.75,1,0.75,0.5,1,1,1,1,0.996815,1,0.496815,1,0.996835,1,1,0.996835,0.5,1,1,0.996835,0.75,0.5,1,0.75,0.996835,0.75,0.75,1,1,1,1,1,0.493671,1,0.5,1,0.996835,0.996815,1,1,0.75,0.743631,0.496835,1,1,0.5,1,1,1,0.746815,1,1,1,1,1,1,0.743631,0.993631,1,1,0.996815,1,1,1,0.75,1,0.996815,1,0.996835,1,0.75,1,1,1,1,1,1,0.996835,0.5,1,1,0.996815,0.746815,1,1,1,1,1,0.993631,1,0.496835,0.996835,1,1,1,1,1,0.5,1] 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 0.772292 [1,1,0,1,0.666667,0.5,0,0,1,1,0.666667,0,0.8,1,0.666667,1,0.5,0.666667,1,1,1,0.666667,1,0.666667,0.666667,1,0.5,0,1,0,0.5,1,1,1,0,1,0.666667,1,0.5,0.666667,1,0.5,0,0.666667,1,1,0.666667,1,1,0.8,0.666667,1,0.666667,1,0.5,0.666667,1,0,1,1,1,1,1,1,0.666667,1,1,1,1,1,0.666667,1,0.666667,1,1,1,0.666667,1,1,0.666667,0.666667,0.666667,0.8,0.666667,1,1,0,1,1,0.8,0.666667,0.666667,1,1,0.666667,0.5,0.666667,1,1,1] f_measure 0.741042 [1,1,1,1,0,0,1,0.666667,1,1,1,0.5,1,1,0.666667,1,0.5,1,1,0.666667,1,0.666667,0.666667,1,0.4,0,0,0.4,0.666667,0.8,0,1,0.5,0.5,0,0.5,1,0.666667,1,0.666667,1,0,0,0.5,1,1,0.5,1,1,1,0.666667,1,0.666667,0.8,0.5,1,0.666667,0.4,1,1,1,0.666667,0.666667,0,1,0.666667,1,0,1,0.666667,1,0.666667,1,1,1,0.666667,0.5,1,1,1,1,0.8,0,1,1,1,0,0.8,0.666667,1,1,0.666667,1,1,1,0.666667,0,1,1,1] f_measure 0.759226 [1,1,1,1,0.571429,1,1,1,1,1,1,0,1,0.666667,0.8,1,0.5,0.666667,1,1,1,0.5,0.666667,1,0,0.666667,1,0.666667,1,1,0.666667,1,0,0.666667,0.666667,0,1,1,0.5,0,1,1,0.666667,0.666667,0.4,0.666667,0,1,0.666667,0.5,0.666667,0.8,0.666667,1,0.666667,0.666667,1,0,1,1,1,1,0,0.666667,1,0.666667,0.8,1,1,0.5,0.8,0.666667,1,1,1,0.666667,1,1,1,0.666667,1,0,0,0.8,0.4,0.666667,0.666667,1,0.666667,1,1,0.666667,0.8,1,0.8,1,1,0.8,1,0.666667] f_measure 0.704286 [0.666667,1,0.666667,1,0.8,0,0,0,0.666667,1,0.8,0,1,0.666667,0.666667,1,0.666667,0.666667,0.666667,1,1,0,1,1,0,0.5,0.666667,0,1,0.8,1,0.666667,0.666667,1,0.666667,0,0.4,0.666667,0,1,1,0,0,0.571429,0.666667,1,0.8,1,0,0.5,1,1,0.666667,0.666667,0.5,0.4,1,0.5,1,1,1,0,1,0,1,0.666667,0.8,1,1,0.571429,0.8,0,1,1,0.666667,0.666667,0.666667,0,0.666667,1,1,0.5,0,1,1,1,1,0.666667,1,1,1,1,0.666667,1,1,0.666667,0.8,0.666667,1,0.666667] f_measure 0.740625 [0.8,0.8,0.666667,1,0.5,1,1,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,1,0,0,0.5,0.5,0.666667,0.4,1,1,1,0.8,0.8,1,1,1,1,0.666667,0,0.8,0.8,0.4,0.5,0.5,0.666667,0.666667,1,1,0.666667,0.666667,1,1,0,0.5,0.666667,1,1,1,1,1,1,1,0.8,0.666667,1,1,1,1,0.5,1,1,1,0.333333,1,1,0.666667,1,1,1,0,1,0,1,0.8,1,0.666667,1,1,0.666667,0,0.666667,1,0,1,0.666667,0.666667,1,0,0.8] f_measure 0.799375 [1,1,1,0,0.4,1,1,0.666667,1,1,1,0,1,1,1,0.666667,0.8,1,0.666667,1,1,0,0.5,1,0.5,1,0,0,1,1,0,1,0.8,1,0.666667,0.666667,0.8,1,1,1,1,0.666667,0.666667,0.8,0.666667,1,0.5,0.666667,1,1,0.666667,0.666667,1,1,0.5,0.666667,1,0.666667,0.666667,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,0.666667,1,1,1,1,1,1,0,0,0.5,0.666667,1,1,0.666667,1,0.666667,1,0.5,0.666667,1,1,0.666667,0.666667,0.8,1,1] f_measure 0.749405 [0.5,1,1,1,0,1,0,0.666667,0.8,1,0.666667,0,1,1,0,1,0,1,1,1,1,1,0,1,0.5,0.8,0.666667,0,0,0.8,0,1,0.5,1,0.666667,0.5,0.5,0.666667,0.8,1,1,1,0.285714,0.666667,0,1,1,1,1,1,0.8,1,0.5,0,1,0,0.8,0.666667,1,1,1,1,1,0.666667,0,1,1,1,0,0.666667,1,0.666667,1,0,1,0.666667,1,0.4,1,1,1,1,0,1,1,1,1,1,1,0.666667,1,0,1,1,0.5,1,0.8,1,1,1] f_measure 0.684375 [0,1,0.666667,1,0,1,0,0.8,0,0,0.666667,0,1,0.666667,1,1,0,0.5,0,0.666667,1,0,1,1,0,1,0.4,0,1,0.666667,0,1,0,1,1,0,0.8,0,0.666667,1,1,0,0,0,1,1,0.5,1,1,1,0.666667,1,0.8,1,0.8,0,1,0.8,0.5,1,1,0.666667,1,1,1,0.8,0.666667,0.5,1,1,0.666667,0,1,1,1,0,1,0.666667,0.5,0,1,1,0.5,1,0.8,1,0,1,1,0.666667,1,1,1,1,1,0.5,0.666667,1,1,0.666667] f_measure 0.742976 [0,0.8,1,0,0.666667,1,1,0,0.666667,1,1,0,0.8,0.666667,0.666667,0.666667,1,1,1,1,0.666667,0.666667,1,1,0.5,1,1,0,1,0.666667,0.666667,0.8,1,0.666667,1,0.5,0.666667,0.666667,1,0.666667,1,0.666667,0.8,0,0,0.666667,0.666667,1,0.666667,0.666667,1,0.666667,1,0.666667,0.8,0.4,1,0.8,1,1,1,1,0,1,0.666667,1,1,1,1,0,0.666667,0,0.666667,0.571429,1,1,1,1,0,1,1,0,0.4,0.666667,0.8,1,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0,1,0.666667] f_measure 0.802516 [0,0.666667,1,0.666667,0,1,1,1,1,0.8,1,0,1,0.666667,1,1,0.666667,0,1,1,0.666667,0.666667,0,1,0.666667,0.666667,0.666667,0.666667,1,1,1,1,1,0,1,0,1,0.666667,0.8,1,1,0.666667,0.4,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.4,0.666667,1,1,0.8,1,1,1,0.666667,1,0.8,1,0.666667,1,0.666667,1,1,1,1,1,1,0.666667,0,1,1,0.8,0.5,1,1,1,1,1,0.666667,1,0,0.666667,1,1,1,1,1,0,1] kappa 0.778962 kappa 0.753681 kappa 0.760006 kappa 0.722058 kappa 0.772503 kappa 0.816818 kappa 0.785116 kappa 0.709367 kappa 0.759978 kappa 0.82197 kb_relative_information_score 124.934403 kb_relative_information_score 120.926164 kb_relative_information_score 121.928224 kb_relative_information_score 115.90283 kb_relative_information_score 123.932343 kb_relative_information_score 130.933597 kb_relative_information_score 125.923298 kb_relative_information_score 113.885546 kb_relative_information_score 121.902024 kb_relative_information_score 130.922745 mean_absolute_error 0.004375 mean_absolute_error 0.004875 mean_absolute_error 0.00475 mean_absolute_error 0.0055 mean_absolute_error 0.0045 mean_absolute_error 0.003625 mean_absolute_error 0.00425 mean_absolute_error 0.00575 mean_absolute_error 0.00475 mean_absolute_error 0.003522 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 0.821875 [1,1,0,1,1,0.5,0,0,1,1,0.5,0,0.666667,1,1,1,0.333333,0.5,1,1,1,1,1,1,1,1,0.333333,0,1,0,0.5,1,1,1,0,1,0.5,1,0.5,1,1,0.333333,0,1,1,1,1,1,1,0.666667,0.5,1,0.5,1,0.333333,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.666667,1,1,1,0,1,1,0.666667,1,1,1,1,1,0.5,0.5,1,1,1] precision 0.774479 [1,1,1,1,0,0,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0.333333,0,0,0.333333,1,0.666667,0,1,0.333333,0.333333,0,0.5,1,0.5,1,1,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0.5,0.666667,0.333333,1,0.5,0.25,1,1,1,1,0.5,0,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.666667,0,1,1,1,0,0.666667,1,1,1,1,1,1,1,1,0,1,1,1] precision 0.822187 [1,1,1,1,0.4,1,1,1,1,1,1,0,1,1,0.666667,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0.333333,0,1,1,0.5,1,0.333333,1,0,1,1,0.333333,0.5,0.666667,1,1,0.5,1,1,0,1,1,1,1,0,0.5,1,1,0.666667,1,1,0.5,0.666667,1,1,1,1,1,1,1,1,1,1,0,0,0.666667,0.25,1,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0.666667,1,0.5] precision 0.750104 [1,1,1,1,0.666667,0,0,0,0.5,1,0.666667,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,0.5,0,1,0.666667,1,0.5,1,1,1,0,0.25,1,0,1,1,0,0,0.4,1,1,0.666667,1,0,0.333333,1,1,1,1,0.5,0.333333,1,0.333333,1,1,1,0,1,0,1,0.5,0.666667,1,1,0.4,0.666667,0,1,1,1,1,1,0,1,1,1,0.5,0,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.666667,1,1,0.5] precision 0.745833 [0.666667,0.666667,1,1,0.333333,1,1,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,1,0,0,0.5,0.5,0.5,0.333333,1,1,1,0.666667,0.666667,1,1,1,1,0.5,0,0.666667,0.666667,0.333333,0.5,0.5,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.666667,0.5,1,1,1,1,0.333333,1,1,1,0.25,1,1,0.5,1,1,1,0,1,0,1,0.666667,1,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0,0.666667] precision 0.830729 [1,1,1,0,0.25,1,1,1,1,1,1,0,1,1,1,0.5,0.666667,1,1,1,1,0,0.5,1,0.333333,1,0,0,1,1,0,1,0.666667,1,1,0.5,0.666667,1,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.333333,1,1,1,1,1,1,1,1,1,0,0,0.333333,1,1,1,0.5,1,0.5,1,0.5,1,1,1,0.5,1,0.666667,1,1] precision 0.744167 [0.333333,1,1,1,0,1,0,1,0.666667,1,1,0,1,1,0,1,0,1,1,1,1,1,0,1,0.5,0.666667,1,0,0,0.666667,0,1,0.5,1,1,0.5,0.5,0.5,0.666667,1,1,1,0.2,0.5,0,1,1,1,1,1,0.666667,1,0.5,0,1,0,0.666667,0.5,1,1,1,1,1,1,0,1,1,1,0,0.5,1,0.5,1,0,1,0.5,1,0.333333,1,1,1,1,0,1,1,1,1,1,1,0.5,1,0,1,1,0.333333,1,0.666667,1,1,1] precision 0.69375 [0,1,1,1,0,1,0,0.666667,0,0,1,0,1,0.5,1,1,0,0.5,0,1,1,0,1,1,0,1,0.333333,0,1,0.5,0,1,0,1,1,0,0.666667,0,1,1,1,0,0,0,1,1,0.333333,1,1,1,1,1,0.666667,1,0.666667,0,1,0.666667,0.5,1,1,0.5,1,1,1,0.666667,0.5,0.5,1,1,0.5,0,1,1,1,0,1,1,0.5,0,1,1,0.333333,1,0.666667,1,0,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1] precision 0.781562 [0,0.666667,1,0,1,1,1,0,1,1,1,0,0.666667,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0.5,1,0.666667,1,0.5,1,0.5,1,0.5,1,1,1,1,0.666667,0,0,0.5,0.5,1,1,1,1,0.5,1,1,0.666667,0.25,1,0.666667,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0.5,0.4,1,1,1,1,0,1,1,0,0.333333,0.5,0.666667,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1] precision 0.81761 [0,1,1,1,0,1,1,1,1,0.666667,1,0,1,0.5,1,1,0.5,0,1,1,0.5,1,0,1,1,0.5,1,1,1,1,1,1,1,0,1,0,1,0.5,0.666667,1,1,1,0.333333,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.333333,0.5,1,1,0.666667,1,1,1,1,1,0.666667,1,0.5,1,1,1,1,1,1,1,1,0.5,0,1,1,0.666667,0.5,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1,0,1] predictive_accuracy 0.78125 predictive_accuracy 0.75625 predictive_accuracy 0.7625 predictive_accuracy 0.725 predictive_accuracy 0.775 predictive_accuracy 0.81875 predictive_accuracy 0.7875 predictive_accuracy 0.7125 predictive_accuracy 0.7625 predictive_accuracy 0.823899 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 0.78125 [1,1,0,1,0.5,0.5,0,0,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,0,1,0,0.5,1,1,1,0,1,1,1,0.5,0.5,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1] recall 0.75625 [1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0.5,0,0,0.5,0.5,1,0,1,1,1,0,0.5,1,1,1,0.5,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,1,0,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,0.5,1,1,1,0.5,0,1,1,1] recall 0.7625 [1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,1,0.5,0.5,1,0,0.5,1,0.5,1,1,0.5,1,0,0.5,0.5,0,1,1,1,0,1,1,1,0.5,0.5,0.5,0,1,0.5,1,1,1,0.5,1,1,0.5,1,0,1,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0,0,1,1,0.5,0.5,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1] recall 0.725 [0.5,1,0.5,1,1,0,0,0,1,1,1,0,1,0.5,0.5,1,0.5,1,0.5,1,1,0,1,1,0,0.5,1,0,1,1,1,1,0.5,1,0.5,0,1,0.5,0,1,1,0,0,1,0.5,1,1,1,0,1,1,1,0.5,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0.5,0,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1] recall 0.775 [1,1,0.5,1,1,1,1,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,1,0,0,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0.5,0.5,0.5,1,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,0.5,1,0,1] recall 0.81875 [1,1,1,0,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,0,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1] recall 0.7875 [1,1,1,1,0,1,0,0.5,1,1,0.5,0,1,1,0,1,0,1,1,1,1,1,0,1,0.5,1,0.5,0,0,1,0,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,0,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,0,1,1,1,1,0,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1] recall 0.7125 [0,1,0.5,1,0,1,0,1,0,0,0.5,0,1,1,1,1,0,0.5,0,0.5,1,0,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0,1,0,0.5,1,1,0,0,0,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,0.5,0.5,0,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5] recall 0.7625 [0,1,1,0,0.5,1,1,0,0.5,1,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0,1,1,0.5,1,1,1,1,0.5,0.5,1,1,0.5,1,0.5,1,0,0,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,0,0.5,0,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,1,0.5] recall 0.823899 [0,0.5,1,0.5,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,0.5,0,1,0.5,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,0.5,0.5,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1] relative_absolute_error 0.220959 relative_absolute_error 0.246212 relative_absolute_error 0.239899 relative_absolute_error 0.277777 relative_absolute_error 0.227272 relative_absolute_error 0.183081 relative_absolute_error 0.214647 relative_absolute_error 0.290405 relative_absolute_error 0.2399 relative_absolute_error 0.17788 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 0.066144 root_mean_squared_error 0.069821 root_mean_squared_error 0.06892 root_mean_squared_error 0.074162 root_mean_squared_error 0.067082 root_mean_squared_error 0.060208 root_mean_squared_error 0.065192 root_mean_squared_error 0.075829 root_mean_squared_error 0.06892 root_mean_squared_error 0.059347 root_relative_squared_error 0.664769 root_relative_squared_error 0.701728 root_relative_squared_error 0.692673 root_relative_squared_error 0.745355 root_relative_squared_error 0.674199 root_relative_squared_error 0.605114 root_relative_squared_error 0.655206 root_relative_squared_error 0.762109 root_relative_squared_error 0.692676 root_relative_squared_error 0.596456 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