8878837
710
William Raynaut
9956
Supervised Classification
7847
weka.kf.Bagging-SMO(1)
6833439
mDataExp
Modelage
study_107
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
18673451
description
https://api.openml.org/data/download/18673451/description8868950233889246072.xml
-1
18673452
predictions
https://api.openml.org/data/download/18673452/predictions7757594063848151806.arff
area_under_roc_curve
0.98886 [0.986848,0.997769,0.984819,0.996802,0.932525,0.99773,0.988432,0.975047,0.998065,0.998934,0.98859,0.968572,0.999151,0.999901,0.983181,0.999724,0.984326,0.998302,1,0.970981,0.999684,0.920898,0.985885,0.994986,0.893122,0.993249,0.982786,0.936671,0.998638,0.999309,0.981759,0.999684,0.929051,0.999092,0.999171,0.987445,0.98326,0.999605,0.958623,0.996545,1,0.990406,0.981503,0.973369,0.980891,0.999724,0.970606,0.996624,0.986912,0.997907,0.996624,0.998895,0.997967,0.990465,0.989754,0.993249,0.999961,0.964071,0.999901,1,1,0.999388,0.999684,0.998381,0.999092,0.999309,0.999684,0.993189,1,0.988254,0.999743,0.986201,1,0.988116,0.999566,0.999428,0.994848,0.999882,0.989162,0.99694,0.998796,0.982352,0.973922,0.9985,0.992952,0.999961,0.966243,0.998993,1,0.998006,0.99236,0.975857,0.998105,0.999961,0.994117,0.994867,0.995479,0.997315,0.999467,0.999743]
average_cost
0
f_measure
0.774215 [0.827586,0.848485,0.785714,0.758621,0.594595,0.83871,0.785714,0.5625,0.866667,0.8,0.875,0.090909,0.903226,0.967742,0.758621,1,0.666667,0.866667,0.933333,0.896552,0.941176,0.296296,0.8125,0.967742,0.214286,0.83871,0.733333,0.333333,0.875,0.833333,0.785714,0.941176,0.5,0.820513,0.903226,0.538462,0.7,0.864865,0.628571,0.814815,1,0.647059,0.384615,0.466667,0.538462,0.882353,0.571429,0.785714,0.857143,0.722222,0.666667,0.769231,0.727273,0.72,0.666667,0.484848,0.888889,0.55,0.9375,0.967742,1,0.857143,0.933333,0.8,0.875,0.83871,0.969697,0.875,0.969697,0.787879,0.875,0.647059,0.941176,0.777778,0.967742,0.866667,0.8,0.914286,0.714286,0.789474,0.866667,0.62069,0.424242,0.666667,0.823529,0.967742,0.538462,0.882353,1,0.780488,0.933333,0.64,0.83871,0.9375,0.857143,0.789474,0.777778,0.857143,0.909091,0.909091]
kappa
0.77827
kb_relative_information_score
236.082488
mean_absolute_error
0.019605
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
0.787755 [0.857143,0.823529,0.916667,0.846154,0.52381,0.866667,0.916667,0.5625,0.928571,0.736842,0.875,0.166667,0.933333,1,0.846154,1,0.6,0.928571,1,1,0.888889,0.363636,0.8125,1,0.25,0.866667,0.785714,0.5,0.875,0.75,0.916667,0.888889,0.583333,0.695652,0.933333,0.7,0.583333,0.761905,0.578947,1,1,0.611111,0.5,0.5,0.7,0.833333,0.526316,0.916667,1,0.65,0.565217,0.652174,0.705882,1,0.6,0.470588,0.8,0.458333,0.9375,1,1,0.789474,1,0.736842,0.875,0.866667,0.941176,0.875,0.941176,0.764706,0.875,0.611111,0.888889,0.7,1,0.928571,0.736842,0.842105,0.833333,0.681818,0.928571,0.692308,0.411765,1,0.777778,1,0.7,0.833333,1,0.64,1,0.888889,0.866667,0.9375,0.789474,0.681818,0.7,0.789474,0.882353,0.882353]
predictive_accuracy
0.780488
prior_entropy
6.643831
recall
0.780488 [0.8,0.875,0.6875,0.6875,0.6875,0.8125,0.6875,0.5625,0.8125,0.875,0.875,0.0625,0.875,0.9375,0.6875,1,0.75,0.8125,0.875,0.8125,1,0.25,0.8125,0.9375,0.1875,0.8125,0.6875,0.25,0.875,0.9375,0.6875,1,0.4375,1,0.875,0.4375,0.875,1,0.6875,0.6875,1,0.6875,0.3125,0.4375,0.4375,0.9375,0.625,0.6875,0.75,0.8125,0.8125,0.9375,0.75,0.5625,0.75,0.5,1,0.6875,0.9375,0.9375,1,0.9375,0.875,0.875,0.875,0.8125,1,0.875,1,0.8125,0.875,0.6875,1,0.875,0.9375,0.8125,0.875,1,0.625,0.9375,0.8125,0.5625,0.4375,0.5,0.875,0.9375,0.4375,0.9375,1,1,0.875,0.5,0.8125,0.9375,0.9375,0.9375,0.875,0.9375,0.9375,0.9375]
relative_absolute_error
0.990151
root_mean_prior_squared_error
0.099499
root_mean_squared_error
0.098674
root_relative_squared_error
0.991715
total_cost
0
area_under_roc_curve
0.98958 [1,1,0.990566,1,0.987342,0.990506,0.936709,1,1,1,1,0.969937,0.998418,1,0.963608,1,1,1,1,1,1,0.71519,1,0.958861,0.993671,1,1,0.990506,1,0.993711,1,1,0.993711,1,1,1,1,1,1,0.996835,1,0.993711,0.990566,1,1,1,0.920886,1,0.990506,0.993671,1,1,1,0.993671,0.968553,0.998418,1,0.987421,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996855,1,0.993671,0.996835,0.996835,1,1,0.976266,1,1,0.996835,0.977848,0.949367,1,1,0.968354,0.958861,0.996855,1,1,1]
area_under_roc_curve
0.989223 [1,0.993711,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.998418,1,0.962025,1,1,0.977848,1,0.886076,1,1,0.860759,0.968354,0.842767,0.968354,1,1,1,1,1,0.996855,0.990566,0.963608,1,0.996855,0.996835,1,1,1,0.893082,0.960443,1,1,0.96519,1,1,1,0.996855,1,1,0.993671,1,0.998418,1,0.993711,1,1,1,1,1,1,1,0.996835,1,0.91195,1,0.939873,1,1,1,1,1,1,0.998418,1,1,1,1,0.993671,0.842767,1,1,1,0.985759,1,1,1,1,1,1,1,1,1,0.993711,1,1,1]
area_under_roc_curve
0.99344 [1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,0.960443,0.987342,1,0.91195,1,1,0.957278,1,1,0.993671,1,0.984177,1,1,1,1,1,1,1,1,1,1,0.990506,0.998418,1,1,1,1,1,1,0.995253,0.996835,1,0.996855,0.996835,1,0.943396,1,1,1,1,1,0.993711,1,1,1,1,1,0.990506,1,0.949367,1,1,1,0.996835,1,1,1,0.998418,1,0.901899,1,0.998418,1,1,0.90981,0.993711,1,1,1,0.952532,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.989891 [1,1,0.995253,1,1,1,0.985759,0.973101,1,1,1,0.987421,1,1,0.914557,1,0.987342,1,1,1,1,0.941456,1,1,0.924528,0.996835,1,0.865506,1,1,1,1,0.990506,1,1,0.962264,0.996855,1,0.742138,1,1,0.993711,0.95283,1,1,1,1,1,0.987421,1,1,1,0.993671,0.943038,0.958861,0.992089,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.96519,1,1,0.996835,1,0.949367,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,0.995253,0.993671,1,1,1,0.998418,1,1,1]
area_under_roc_curve
0.991495 [0.990506,1,0.936709,1,1,1,1,0.89557,0.993711,1,1,0.930818,0.987421,1,0.90566,1,0.969937,1,1,1,1,0.886792,0.977848,1,0.889937,0.993671,0.996835,1,0.974684,1,1,1,1,1,1,1,1,1,1,0.937107,1,0.996835,0.982595,0.993671,0.96519,1,0.990506,0.993671,1,1,0.990506,1,1,1,0.993671,0.993671,1,0.974684,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.996855,1,1,1,1,1,0.993711,1,1,1,0.984177,1,1,0.993711,0.987421,0.993671,1,1,1,0.996855,0.990506,1,0.996835,0.996835]
area_under_roc_curve
0.992249 [1,1,0.987342,1,1,1,1,0.987342,1,1,1,0.990566,1,1,1,1,1,1,1,1,1,0.933962,0.996835,1,0.968553,1,0.993671,0.823899,1,1,0.767296,1,0.960443,1,1,1,1,1,1,1,1,0.996835,1,1,0.984177,1,0.993671,0.990506,1,1,0.993671,0.993711,1,1,0.982595,0.990506,1,0.867089,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,1,1,1,1,1,1,1,1,0.993711,0.962025,1,0.977848,1,1,1,1,0.996855,1,1,0.996835,1,1,1,0.990506,1,1,1]
area_under_roc_curve
0.991274 [1,1,1,1,1,1,1,0.993671,1,1,0.958861,0.871835,1,1,1,1,1,1,1,1,1,0.993711,0.830189,1,0.936709,1,0.990506,0.977987,1,1,1,1,1,1,0.996835,0.988924,0.971519,1,1,1,1,1,0.995253,1,0.958861,1,1,0.993671,1,1,1,1,1,0.987421,1,0.987421,1,1,1,1,1,1,1,0.988924,1,1,1,1,1,1,1,1,1,0.914557,1,1,1,1,0.993671,1,1,0.987421,0.947785,1,1,1,1,1,1,1,1,0.849057,1,1,0.987421,1,1,1,1,1]
area_under_roc_curve
0.981455 [0.855346,1,0.973101,1,0.962264,1,1,0.995253,0.988924,1,0.969937,0.981013,1,1,1,1,0.937107,0.993671,1,0.931962,1,1,1,1,0.759494,1,0.990506,0.930818,1,1,0.987421,1,0.599684,1,1,0.977848,1,0.996835,0.85443,1,1,0.981013,0.968354,0.899371,1,1,1,1,1,1,1,1,1,1,1,0.987421,1,0.996835,1,1,1,1,1,1,1,1,1,0.97943,1,1,1,1,1,1,1,0.993711,1,1,0.955696,0.984177,1,1,1,1,0.981013,1,0.77673,1,1,1,1,1,0.996835,1,1,1,0.995253,1,1,1]
area_under_roc_curve
0.993027 [0.987421,1,1,0.982595,0.960443,1,1,0.998418,1,1,1,0.988924,1,1,1,1,0.987421,1,1,1,0.996855,0.993671,1,1,0.977848,1,1,0.933544,1,1,0.996835,0.996835,0.993711,0.996855,1,1,0.919304,1,1,1,1,1,1,0.924528,0.993711,1,1,1,0.916139,1,1,1,1,0.996835,0.990506,0.993711,1,0.957278,1,1,1,1,1,1,0.995253,1,1,1,1,0.962264,1,0.97943,1,1,1,1,1,1,1,1,1,0.993711,0.968354,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.949686,1,1]
area_under_roc_curve
0.989572 [1,0.996815,1,0.987261,0.651274,1,0.993631,1,1,0.996815,1,0.984076,1,1,1,1,0.993671,1,1,1,1,0.993631,1,1,0.765924,1,1,0.984076,1,1,1,1,1,1,1,1,1,1,0.996815,1,1,0.971338,0.996815,0.936709,1,1,0.892405,1,1,1,0.990446,1,1,1,1,1,1,0.969745,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996815,0.996815,1,1,1,0.993631,1,1,1,1,1,1,0.995223,0.998408,1,1,1,1]
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
0.7375 [1,1,0,1,0.666667,0.5,0,0.666667,1,0.8,0.666667,0,0.8,1,0.5,1,0.8,1,1,0.666667,1,0,1,0.666667,0.666667,1,1,1,1,0,0.8,1,0,1,1,0.666667,0.666667,1,0.5,0.666667,1,0.4,0.666667,0.666667,0.666667,1,0.666667,1,0.666667,0.5,0.4,0.8,1,0,0.333333,0,1,0.4,1,1,1,1,1,0.666667,0.666667,1,1,1,1,1,0.666667,0.8,0.666667,1,1,1,1,1,1,0.666667,0.666667,0.666667,0,0.666667,1,1,0,0.8,1,0.8,0.666667,0.666667,0.666667,1,0.666667,0.5,0.666667,1,1,1]
f_measure
0.740208 [1,1,1,0.666667,0.5,0,0.666667,1,1,0.8,0.666667,0.666667,1,1,0.666667,1,0.666667,1,1,0.666667,1,0.666667,0.666667,1,0,0,0,0.4,1,0.8,0.666667,1,0.666667,0.5,0.666667,0.5,1,0.666667,0.8,0.666667,1,0.666667,0,0,1,1,0,0.666667,1,1,0.666667,0.8,0.5,0.666667,0.666667,0.5,0.666667,0.5,1,1,1,0.666667,1,1,1,0.666667,1,0,1,0.666667,1,1,1,1,1,1,0.4,1,1,1,1,0.666667,0,1,0.666667,1,0,1,1,1,1,0.666667,1,0.666667,1,0.8,0,0.666667,1,0]
f_measure
0.751726 [1,1,1,1,0.571429,1,1,1,1,1,1,0,1,0.666667,1,1,1,0.666667,1,1,1,0,0.666667,1,0,1,0.666667,0,1,1,1,1,0,1,1,0.666667,0.666667,1,0.666667,0,1,0.666667,1,0.666667,0,1,0.666667,1,0.666667,0.5,0.666667,0.8,0.5,1,0.666667,0,1,0,1,1,1,0.666667,0,0,1,0.666667,1,1,1,0.5,0.8,0.4,1,1,1,0.666667,1,1,1,0.8,1,0,0,0.666667,0.5,0.666667,0,1,1,1,1,0,1,1,0.8,1,1,0.8,1,0.666667]
f_measure
0.792083 [1,1,0.666667,0.8,0.8,1,0.666667,0,0.666667,1,1,0,1,1,0.666667,1,0.8,0.8,0.666667,1,1,0.4,1,1,0,1,0.666667,0,0.666667,1,1,1,0.666667,1,1,0,0.5,1,0,1,1,0.666667,0,0.666667,0.666667,0.8,1,0.666667,0,0.5,1,0.8,0.666667,0.666667,0.666667,0.5,1,0.666667,1,1,1,1,1,1,1,1,0.8,1,1,0.8,1,0.5,1,1,0.666667,0.666667,0.666667,1,0.666667,1,1,0.666667,1,1,1,1,0.8,0.666667,1,1,1,0.666667,0.666667,1,1,0.666667,0.8,1,0.8,1]
f_measure
0.737768 [0.666667,0.8,0.666667,1,0.666667,1,1,0,0,0,1,0,0,1,0,1,0.5,0.666667,1,1,1,0,0.666667,1,0,0.5,0.5,1,0.4,1,1,1,0.571429,0.8,1,1,0.8,1,0.666667,0,1,0.8,0.5,0,0.4,0.666667,0.8,0.666667,1,0.666667,0.666667,1,1,0,0.666667,0.666667,1,0.5,1,1,1,1,1,0.8,0.666667,1,1,1,1,1,1,1,1,0.666667,1,1,0.666667,0.666667,1,0.8,0,1,0.666667,0,1,1,0.5,0.666667,1,0.5,0,0.666667,1,0,1,0.666667,1,1,0.666667,0.8]
f_measure
0.780268 [1,0.8,0.666667,0,0.4,1,0.666667,0.666667,1,1,1,0,1,1,1,1,1,1,0.666667,1,1,0,0.8,1,0,0.8,0.666667,0,1,0.8,0,1,0.666667,0.8,0.666667,1,0.666667,1,1,1,1,0.666667,0,0.8,0.666667,1,0.333333,0,1,0.666667,0.571429,0,0.666667,1,0.5,0.666667,1,0.666667,1,1,1,1,0.666667,1,1,1,1,1,0.8,1,1,0,1,1,1,1,1,1,0.666667,1,1,0,0,1,0.666667,1,1,1,1,0.5,1,0.666667,0.666667,1,1,1,0.666667,0.8,1,1]
f_measure
0.760625 [0.666667,1,1,1,1,1,1,0.666667,1,0.666667,0.666667,0,1,1,1,1,1,1,1,1,1,0,0,1,0,1,0.666667,0,1,0.8,0,0.8,0.5,1,0.666667,0.5,0.5,0.8,0.666667,1,1,1,0.666667,0.666667,0,1,0.666667,0.666667,1,1,0.8,1,0.666667,0,1,0,1,0.8,0.8,1,1,1,1,0.4,1,1,1,1,1,0.666667,1,1,1,0,1,0.666667,0.666667,0.8,0.666667,0.8,1,0,0,0,1,1,0,1,1,0.666667,1,0,1,1,0.5,1,0.666667,0.8,0.666667,1]
f_measure
0.71881 [0,1,0.5,1,0.666667,1,1,0.4,0,0,0.666667,0,1,1,1,1,0,0.666667,1,0.666667,1,1,1,1,0,1,0.666667,0,1,0.666667,0,1,0,1,1,0,0.8,0.8,0.666667,1,1,0,0,0,1,1,0.5,1,1,1,0.666667,0.666667,0.8,1,1,0.5,1,0.666667,0.666667,0.666667,1,0.666667,1,1,0.666667,0.666667,1,0.5,1,0.666667,0.666667,1,1,1,1,0,1,0.8,0,0.5,1,1,0.571429,0,0.5,1,0,1,1,1,1,1,0.666667,1,1,0.666667,0.666667,1,1,1]
f_measure
0.723601 [0,0.8,1,0,0.666667,0.8,1,0.666667,1,0.8,1,0,1,1,0.666667,1,0,1,1,1,0.666667,0,1,1,0.4,1,1,0,1,0.666667,0.666667,0.8,0,0.666667,1,0.666667,0.5,0.666667,0.8,0.666667,1,0.666667,0,0,0,0.666667,1,1,0.666667,0.666667,1,0.5,0.666667,0.666667,0.5,0.4,0.666667,0.666667,1,1,1,1,1,1,0.666667,1,1,1,1,0,0.666667,0,0.666667,0.571429,1,1,1,1,0,0.5,0.666667,0.5,0.5,0,1,1,1,1,1,0.8,1,1,0.666667,1,1,1,1,0,1,1]
f_measure
0.806499 [1,0,1,0.5,0,1,0.666667,0.666667,1,0.8,1,0,0.666667,1,1,1,0.666667,1,1,1,0.666667,0.666667,1,1,0.666667,1,1,0,1,1,1,1,1,0.5,1,0,1,0.666667,0.5,1,1,0.666667,0.666667,0,0,0.666667,0,1,1,0.666667,0.5,1,1,1,1,1,0.8,0.4,1,1,1,0.8,1,1,1,0.666667,1,0.8,1,1,1,0.8,1,0.8,1,1,0.8,1,0.666667,1,1,1,0.8,0.666667,1,1,1,0.666667,1,0.8,1,1,1,1,0.8,0.8,1,1,1,1]
kappa
0.760073
kappa
0.760016
kappa
0.77262
kappa
0.804169
kappa
0.766202
kappa
0.79151
kappa
0.791486
kappa
0.753603
kappa
0.753681
kappa
0.828356
kb_relative_information_score
23.530794
kb_relative_information_score
23.541013
kb_relative_information_score
23.763265
kb_relative_information_score
23.699444
kb_relative_information_score
23.625646
kb_relative_information_score
23.71709
kb_relative_information_score
23.654976
kb_relative_information_score
23.335815
kb_relative_information_score
23.714324
kb_relative_information_score
23.500121
mean_absolute_error
0.019606
mean_absolute_error
0.019606
mean_absolute_error
0.019604
mean_absolute_error
0.019604
mean_absolute_error
0.019605
mean_absolute_error
0.019604
mean_absolute_error
0.019605
mean_absolute_error
0.019608
mean_absolute_error
0.019604
mean_absolute_error
0.019604
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
0.775729 [1,1,0,1,1,0.5,0,0.5,1,0.666667,0.5,0,0.666667,1,0.5,1,0.666667,1,1,1,1,0,1,1,1,1,1,1,1,0,0.666667,1,0,1,1,1,0.5,1,0.5,1,1,0.25,0.5,1,0.5,1,1,1,1,0.5,0.25,0.666667,1,0,0.2,0,1,0.25,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.666667,0.5,1,1,1,1,1,1,0.5,0.5,1,0,1,1,1,0,0.666667,1,0.666667,1,1,0.5,1,1,0.5,0.5,1,1,1]
precision
0.775 [1,1,1,1,0.5,0,1,1,1,0.666667,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,0,0,0.333333,1,0.666667,1,1,0.5,0.333333,0.5,0.5,1,0.5,0.666667,1,1,0.5,0,0,1,1,0,0.5,1,1,0.5,0.666667,0.333333,1,0.5,0.5,0.5,0.333333,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.333333,1,1,1,1,1,0,1,0.5,1,0,1,1,1,1,1,1,0.5,1,0.666667,0,0.5,1,0]
precision
0.770625 [1,1,1,1,0.4,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,1,0.5,0,1,1,1,1,0,1,1,0.5,0.5,1,0.5,0,1,0.5,1,1,0,1,1,1,1,0.333333,0.5,0.666667,0.5,1,0.5,0,1,0,1,1,1,0.5,0,0,1,1,1,1,1,0.5,0.666667,0.333333,1,1,1,1,1,1,1,0.666667,1,0,0,1,0.333333,1,0,1,1,1,1,0,1,1,0.666667,1,1,0.666667,1,0.5]
precision
0.8375 [1,1,1,0.666667,0.666667,1,1,0,0.5,1,1,0,1,1,1,1,0.666667,0.666667,1,1,1,0.333333,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0,0.333333,1,0,1,1,0.5,0,0.5,1,0.666667,1,1,0,0.333333,1,0.666667,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,0.666667,1,1,0.666667,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,0.5,1,1,1,1,1,1,1,0.5,0.666667,1,0.666667,1]
precision
0.753958 [1,0.666667,1,1,0.5,1,1,0,0,0,1,0,0,1,0,1,0.5,1,1,1,1,0,1,1,0,0.5,0.5,1,0.333333,1,1,1,0.4,0.666667,1,1,0.666667,1,0.5,0,1,0.666667,0.5,0,0.333333,1,0.666667,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.666667,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,0.666667,0,1,0.5,0,1,1,0.5,0.5,1,0.333333,0,1,1,0,1,0.5,1,1,1,0.666667]
precision
0.822188 [1,0.666667,1,0,0.25,1,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0.666667,1,0,0.666667,1,0,1,0.666667,0,1,1,0.666667,1,1,0.5,1,1,1,1,1,0,0.666667,1,1,0.25,0,1,0.5,0.4,0,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0.333333,1,1,1,1,1,1,1,0.666667,1,1]
precision
0.76875 [0.5,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,0,1,0.666667,0,0.666667,0.5,1,1,0.5,0.5,0.666667,1,1,1,1,1,0.5,0,1,0.5,1,1,1,0.666667,1,1,0,1,0,1,0.666667,0.666667,1,1,1,1,0.333333,1,1,1,1,1,0.5,1,1,1,0,1,0.5,0.5,0.666667,1,0.666667,1,0,0,0,1,1,0,1,1,0.5,1,0,1,1,0.333333,1,0.5,0.666667,0.5,1]
precision
0.727917 [0,1,0.5,1,0.5,1,1,0.333333,0,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,0,1,0.5,0,1,0,1,1,0,0.666667,0.666667,1,1,1,0,0,0,1,1,0.333333,1,1,1,1,0.5,0.666667,1,1,0.333333,1,0.5,1,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0.5,0.5,1,1,1,1,0,1,0.666667,0,0.5,1,1,0.4,0,0.5,1,0,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1]
precision
0.748229 [0,0.666667,1,0,1,0.666667,1,0.5,1,0.666667,1,0,1,1,1,1,0,1,1,1,0.5,0,1,1,0.333333,1,1,0,1,0.5,1,0.666667,0,0.5,1,1,0.5,0.5,0.666667,1,1,1,0,0,0,0.5,1,1,1,1,1,0.333333,0.5,1,0.5,0.25,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0.5,0.4,1,1,1,1,0,0.333333,1,0.333333,0.5,0,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,1,0,1,1]
precision
0.821803 [1,0,1,0.5,0,1,1,0.5,1,0.666667,1,0,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.333333,1,0,1,0.5,0.5,1,1,1,1,0,0,0.5,0,1,1,1,0.5,1,1,1,1,1,0.666667,0.333333,1,1,1,0.666667,1,1,1,1,1,0.666667,1,1,1,0.666667,1,0.666667,1,1,0.666667,1,0.5,1,1,1,0.666667,1,1,1,1,1,1,0.666667,1,1,1,1,0.666667,0.666667,1,1,1,1]
predictive_accuracy
0.7625
predictive_accuracy
0.7625
predictive_accuracy
0.775
predictive_accuracy
0.80625
predictive_accuracy
0.76875
predictive_accuracy
0.79375
predictive_accuracy
0.79375
predictive_accuracy
0.75625
predictive_accuracy
0.75625
predictive_accuracy
0.830189
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
0.7625 [1,1,0,1,0.5,0.5,0,1,1,1,1,0,1,1,0.5,1,1,1,1,0.5,1,0,1,0.5,0.5,1,1,1,1,0,1,1,0,1,1,0.5,1,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,0.5,0.5,1,1,1,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,0,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1]
recall
0.7625 [1,1,1,0.5,0.5,0,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0,0,0,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,0,0,1,1,0,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0,1,1,1,0,1,1,1,1,0.5,1,1,1,1,0,1,1,0]
recall
0.775 [1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0.5,0,1,0.5,1,0.5,1,1,1,0.5,1,1,0,1,0,1,1,1,1,0,0,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0,0.5,1,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1]
recall
0.80625 [1,1,0.5,1,1,1,0.5,0,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,0.5,1,1,0,1,1,0,0.5,1,1,1,0.5,1,1,0,1,1,0,1,1,1,0,1,0.5,1,1,0.5,0,1,1,1,0.5,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,0.5,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1]
recall
0.76875 [0.5,1,0.5,1,1,1,1,0,0,0,1,0,0,1,0,1,0.5,0.5,1,1,1,0,0.5,1,0,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0,0.5,0.5,1,0.5,1,1,0.5,1,1,0,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0.5,1,1,1,0,0.5,1,0,1,1,1,1,0.5,1]
recall
0.79375 [1,1,0.5,0,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,1,1,0,1,0.5,0,1,1,0,1,0.5,1,0.5,1,1,1,1,1,1,0.5,0,1,0.5,1,0.5,0,1,1,1,0,0.5,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,0,1,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1]
recall
0.79375 [1,1,1,1,1,1,1,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0,0,1,0,1,0.5,0,1,1,0,1,0.5,1,0.5,0.5,0.5,1,0.5,1,1,1,0.5,1,0,1,1,0.5,1,1,1,1,0.5,0,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0.5,1,1,0,0,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1]
recall
0.75625 [0,1,0.5,1,1,1,1,0.5,0,0,0.5,0,1,1,1,1,0,0.5,1,0.5,1,1,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0,1,1,0.5,1,1,0,0,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,0,0.5,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1]
recall
0.75625 [0,1,1,0,0.5,1,1,1,1,1,1,0,1,1,0.5,1,0,1,1,1,1,0,1,1,0.5,1,1,0,1,1,0.5,1,0,1,1,0.5,0.5,1,1,0.5,1,0.5,0,0,0,1,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,0,1,1,1,1,1,1,0,1,0.5,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1]
recall
0.830189 [1,0,1,0.5,0,1,0.5,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0,1,1,0.5,1,1,0.5,0.5,0,0,1,0,1,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1]
relative_absolute_error
0.990187
relative_absolute_error
0.990197
relative_absolute_error
0.99008
relative_absolute_error
0.990115
relative_absolute_error
0.990155
relative_absolute_error
0.9901
relative_absolute_error
0.990134
relative_absolute_error
0.990311
relative_absolute_error
0.990103
relative_absolute_error
0.990124
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
0.098679
root_mean_squared_error
0.098679
root_mean_squared_error
0.098667
root_mean_squared_error
0.098671
root_mean_squared_error
0.098675
root_mean_squared_error
0.098669
root_mean_squared_error
0.098672
root_mean_squared_error
0.098691
root_mean_squared_error
0.09867
root_mean_squared_error
0.098672
root_relative_squared_error
0.991759
root_relative_squared_error
0.99176
root_relative_squared_error
0.991642
root_relative_squared_error
0.991677
root_relative_squared_error
0.991719
root_relative_squared_error
0.991663
root_relative_squared_error
0.991693
root_relative_squared_error
0.991881
root_relative_squared_error
0.991668
root_relative_squared_error
0.991689
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