8874380
710
William Raynaut
9956
Supervised Classification
7850
weka.kf.RandomSubspace(1)
6833437
mDataExp
Modelage
study_107
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
18664577
description
https://api.openml.org/data/download/18664577/description1307968313743120906.xml
-1
18664578
predictions
https://api.openml.org/data/download/18664578/predictions3839405528245382734.arff
area_under_roc_curve
0.980495 [0.986364,0.998658,0.879422,0.99542,0.932111,0.984661,0.994275,0.989656,0.992893,0.997789,0.987464,0.95732,0.999487,0.998658,0.971968,0.998934,0.978364,0.996841,0.99769,0.994196,0.998895,0.953056,0.998381,0.999605,0.872809,0.974021,0.995815,0.927175,1,0.999289,0.954536,0.999605,0.890813,0.999052,0.99013,0.953253,0.99692,0.997631,0.96873,0.999013,0.99617,0.960676,0.979154,0.934914,0.952503,0.996131,0.926228,0.995578,0.992183,0.992104,0.985925,0.955859,0.994275,0.982865,0.981522,0.998263,1,0.925537,0.998263,1,0.999921,0.998539,0.999368,0.998421,0.997434,0.995993,0.999408,0.957833,0.995815,0.91085,0.996407,0.979667,1,0.952207,0.994157,0.999131,0.975087,0.998816,0.994611,0.995144,0.991669,0.977554,0.966302,0.993051,0.988965,0.999368,0.916298,0.993367,0.999605,0.998184,0.958899,0.964901,0.993328,0.999842,0.961209,0.971277,0.996151,0.997256,0.995223,0.999566]
average_cost
0
f_measure
0.656738 [0.518519,0.731707,0.454545,0.774194,0.296296,0.521739,0.645161,0.625,0.545455,0.764706,0.75,0.827586,0.842105,0.8125,0.518519,0.857143,0.37037,0.580645,0.909091,0.742857,0.909091,0.210526,0.810811,0.842105,0.222222,0.774194,0.814815,0.222222,0.914286,0.909091,0.866667,0.882353,0.166667,0.75,0.564103,0.166667,0.666667,0.810811,0.24,0.909091,0.8,0.6,0.26087,0.37037,0.32,0.685714,0.48,0.742857,0.564103,0.647059,0.666667,0.6,0.578947,0.727273,0.518519,0.756757,0.969697,0.6,0.702703,1,0.969697,0.75,0.882353,0.75,0.848485,0.722222,0.888889,0.482759,0.8,0.3,0.647059,0.4,0.941176,0.705882,0.833333,0.769231,0.538462,0.882353,0.875,0.538462,0.642857,0.606061,0.444444,0.594595,0.533333,0.848485,0.413793,0.585366,0.864865,0.685714,0.736842,0.117647,0.756757,0.933333,0.636364,0.307692,0.666667,0.848485,0.727273,0.857143]
kappa
0.67846
kb_relative_information_score
1057.747801
mean_absolute_error
0.014055
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
0.687348 [0.583333,0.6,0.833333,0.8,0.363636,0.857143,0.666667,0.625,0.529412,0.722222,0.75,0.923077,0.727273,0.8125,0.636364,0.789474,0.454545,0.6,0.882353,0.684211,0.882353,0.666667,0.714286,0.727273,1,0.8,1,1,0.842105,0.882353,0.928571,0.833333,0.25,0.625,0.478261,0.25,0.565217,0.714286,0.333333,0.882353,0.857143,0.642857,0.428571,0.454545,0.444444,0.631579,0.666667,0.684211,0.478261,0.611111,0.647059,0.5,0.5,0.705882,0.636364,0.666667,0.941176,0.642857,0.619048,1,0.941176,0.625,0.833333,0.625,0.823529,0.65,0.8,0.538462,0.736842,0.75,0.611111,0.555556,0.888889,0.666667,0.75,0.652174,0.7,0.833333,0.875,0.7,0.75,0.588235,0.545455,0.52381,0.571429,0.823529,0.461538,0.48,0.761905,0.631579,0.636364,1,0.666667,1,0.5,0.4,0.538462,0.823529,0.705882,0.789474]
predictive_accuracy
0.681676
prior_entropy
6.643831
recall
0.681676 [0.466667,0.9375,0.3125,0.75,0.25,0.375,0.625,0.625,0.5625,0.8125,0.75,0.75,1,0.8125,0.4375,0.9375,0.3125,0.5625,0.9375,0.8125,0.9375,0.125,0.9375,1,0.125,0.75,0.6875,0.125,1,0.9375,0.8125,0.9375,0.125,0.9375,0.6875,0.125,0.8125,0.9375,0.1875,0.9375,0.75,0.5625,0.1875,0.3125,0.25,0.75,0.375,0.8125,0.6875,0.6875,0.6875,0.75,0.6875,0.75,0.4375,0.875,1,0.5625,0.8125,1,1,0.9375,0.9375,0.9375,0.875,0.8125,1,0.4375,0.875,0.1875,0.6875,0.3125,1,0.75,0.9375,0.9375,0.4375,0.9375,0.875,0.4375,0.5625,0.625,0.375,0.6875,0.5,0.875,0.375,0.75,1,0.75,0.875,0.0625,0.875,0.875,0.875,0.25,0.875,0.875,0.75,0.9375]
relative_absolute_error
0.709848
root_mean_prior_squared_error
0.099499
root_mean_squared_error
0.076848
root_relative_squared_error
0.772352
total_cost
0
area_under_roc_curve
0.970243 [1,1,0.512579,1,0.96519,0.977848,1,0.981132,0.993671,1,1,1,1,1,0.844937,1,0.996835,1,1,1,1,0.971519,1,1,0.89557,1,1,1,1,0.993711,1,1,0.987421,1,0.993711,0.837025,1,1,0.952532,0.996835,0.996835,1,1,0.968354,1,1,0.640823,0.955975,0.993671,1,1,1,0.974843,1,0.930818,1,1,0.974843,1,1,1,1,1,0.993711,1,1,1,0.993711,0.993711,0.996835,1,0.984177,1,1,0.996835,1,0.971519,1,1,1,0.993711,0.996835,0.952532,0.996835,0.987421,1,0.867089,0.990506,1,1,0.705696,0.933544,1,1,0.708861,0.852848,1,1,1,1]
area_under_roc_curve
0.985476 [1,1,1,0.996835,0.971519,0.968354,1,1,1,0.993671,1,1,1,1,1,0.996835,0.958861,0.993711,1,0.984177,1,0.958861,1,1,0.949367,0.905063,0.987421,0.990506,1,1,1,1,1,1,0.968553,0.952532,1,1,0.981013,1,1,1,0.899371,0.762658,1,1,0.952532,1,1,1,0.993711,1,0.993711,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.963608,1,0.90566,1,0.841772,1,0.990506,1,1,1,1,1,0.990506,1,0.993711,1,0.984177,0.937107,1,1,1,0.990506,0.968354,1,1,1,0.974684,1,1,0.996835,0.990506,0.987421,1,1,1]
area_under_roc_curve
0.981117 [1,1,0.990506,1,0.981013,1,1,1,1,1,1,1,0.993671,0.993671,0.996835,0.996835,1,1,1,1,1,0.96519,0.993671,1,0.987421,1,1,0.962025,1,1,1,1,0.852848,1,1,0.974843,1,1,0.962264,1,1,0.987421,1,0.89557,0.943038,0.987342,1,0.996835,0.996835,0.943396,1,0.68038,1,1,1,1,1,0.698113,1,1,1,1,1,1,1,1,1,0.855346,0.981132,0.879747,1,0.96519,1,1,0.996835,1,1,1,1,0.993671,1,0.871835,0.993711,0.996835,1,1,0.901899,1,1,0.987421,1,0.977848,1,1,1,0.987421,1,1,1,1]
area_under_roc_curve
0.984727 [0.996835,0.993711,0.990506,1,0.987342,0.962264,0.974684,0.993671,1,1,0.93038,0.993711,1,1,0.924051,1,0.968354,0.996835,0.968354,1,1,0.949367,1,1,0.792453,1,1,0.968354,1,1,1,1,0.933544,1,1,1,1,1,0.91195,1,1,0.993711,1,0.996835,0.933544,1,1,0.984177,1,1,1,0.996835,1,0.905063,0.955696,1,1,1,1,1,1,0.987421,1,1,1,1,1,0.987421,1,0.993671,0.993671,0.958861,1,1,0.968354,0.993671,0.879747,1,0.966772,1,1,0.993671,1,0.993671,0.993711,1,1,1,1,1,1,0.93038,0.949367,1,1,0.993711,1,1,0.996835,1]
area_under_roc_curve
0.989341 [0.971519,1,0.96519,1,1,1,0.993711,0.974684,0.968553,0.993711,1,1,1,1,0.930818,1,0.946203,0.996835,1,1,1,0.836478,1,1,0.993711,0.971519,1,1,1,1,1,1,1,1,1,0.987421,1,1,1,0.981132,1,1,0.943038,0.890823,0.939873,0.996835,0.936709,1,1,1,0.966772,0.993671,1,0.981132,0.977848,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.993711,1,1,0.996835,1,1,0.937107,1,1,0.993671,1,0.977848,0.974843,0.993711,1,1,0.990506,1,1,1,0.962264,0.990506,1,1,1,0.943396,1,1,0.996835,1]
area_under_roc_curve
0.981985 [0.993711,0.993671,0.987342,1,0.949686,1,1,0.996835,1,1,1,1,1,1,1,1,0.990506,1,1,1,1,0.955975,1,1,0.955975,1,0.990506,0.289308,1,1,0.358491,1,0.993671,1,0.984177,0.981132,1,1,0.962264,1,1,0.996835,0.996835,0.987342,0.962025,1,1,1,1,1,0.993671,0.993711,1,1,0.993671,0.993671,1,0.818038,1,1,1,1,1,1,1,1,1,0.843354,0.977848,0.977848,0.993711,1,1,0.990506,1,1,1,1,1,0.993671,0.977848,0.993711,0.977848,1,0.974684,1,0.990506,0.981132,1,1,1,1,1,1,1,1,0.977848,1,0.993671,1]
area_under_roc_curve
0.974578 [0.974843,1,0.941456,0.974843,1,0.958861,0.993711,1,1,1,0.984177,0.670886,1,1,1,1,0.993711,1,1,1,1,0.874214,1,1,0.93038,1,1,0.987421,1,1,1,0.996835,0.560127,1,0.958861,0.987342,0.993671,0.981013,0.968354,1,1,0.996835,0.990506,1,0.911392,1,0.993711,0.996835,0.993711,1,1,1,0.990506,1,1,0.987421,1,0.797468,0.996835,1,1,1,1,0.996835,0.993711,1,1,0.996835,0.993671,0.930818,1,1,1,0.65981,1,1,0.993711,1,1,0.996835,1,1,0.898734,1,1,1,1,0.996835,1,1,1,0.987421,1,1,0.993711,0.977848,1,1,1,1]
area_under_roc_curve
0.979769 [0.955975,1,0.553797,1,0.993711,0.990506,0.987421,0.990506,0.974684,0.987421,1,1,1,1,1,1,0.943396,0.990506,1,0.990506,1,0.981132,1,1,0.824367,1,0.996835,1,1,1,0.968553,1,0.825949,1,1,0.949367,1,1,0.96519,1,1,0.990506,1,0.987421,0.996835,1,1,1,1,0.993671,0.993671,0.974843,0.996835,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.996835,1,0.893082,1,0.968553,1,0.977848,1,1,1,0.996835,0.993671,0.987342,1,1,0.990506,0.993711,0.974684,1,0.320755,0.996835,1,0.996835,1,1,1,1,1,0.993671,1,0.990506,0.974843,1]
area_under_roc_curve
0.988932 [0.968553,1,1,0.990506,0.968354,0.987342,1,0.987342,0.993671,1,1,1,1,1,0.996835,0.993671,1,1,1,1,0.993711,0.968354,1,1,0.920886,0.974843,1,0.96519,1,1,1,0.996835,0.924528,1,1,1,0.993671,1,0.981013,1,0.981132,1,0.993671,1,0.899371,1,0.993711,1,0.984177,0.987342,0.952532,1,1,0.955696,0.993671,0.993711,1,1,1,1,1,1,0.996835,0.993671,0.981013,1,1,1,1,0.707547,0.987342,0.971519,1,1,1,1,0.990506,1,1,1,0.977848,1,0.968354,1,0.993671,1,0.937107,1,1,1,0.996835,0.962264,1,1,1,0.993671,1,0.981132,0.993711,0.996835]
area_under_roc_curve
0.976609 [1,1,0.734177,0.996815,0.640127,1,1,1,1,1,0.949367,0.990446,1,1,1,1,0.981013,0.993671,1,0.990446,1,0.990446,0.993671,1,0.613057,1,1,0.961783,1,1,1,1,1,1,1,0.987261,1,1,0.980892,1,0.987342,0.734076,0.984076,0.879747,1,0.987342,0.848101,1,0.964968,0.990446,0.993631,0.984076,0.993671,1,0.987342,1,1,0.996815,0.990446,1,1,1,1,1,1,1,0.993671,0.952229,1,0.620253,1,1,1,1,1,1,1,1,1,1,1,0.987261,0.993631,0.974522,1,1,1,1,1,0.993631,1,0.955696,1,1,1,0.996815,1,1,1,1]
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
0.565625 [0,0.666667,0,1,0,0,0,0,0.8,1,1,0.666667,0.8,1,0,0.8,0.666667,0.666667,1,1,1,0,0.666667,1,0,1,1,0,1,0,1,1,0,0,0,0,0.5,0.5,0,1,0.8,0.666667,0.666667,0,0,0.333333,0,0,0.8,1,0.5,1,0,1,0,0.666667,1,0,0.666667,1,1,0.666667,1,0.666667,0.5,0.8,1,0.5,0.5,0,0.666667,0.5,1,1,0.8,0.8,0,1,1,0.666667,0,0.8,0,0.666667,0,1,0.5,0.5,1,0.8,0.5,0,0.5,1,0.333333,0,0.5,0.666667,0.666667,1]
f_measure
0.629851 [1,0.666667,0,0.5,0,0,0.666667,0.666667,0.5,0.666667,1,0.8,1,0.5,0,1,0,0.5,1,0.666667,1,0,1,1,0,0,0,0,1,0.8,1,0.8,0,1,0,0,1,1,0,1,0.666667,1,0,0,1,1,0,0.333333,0.8,0.5,1,1,0.4,1,0.666667,1,1,0.666667,1,1,1,0.571429,1,1,1,0.5,1,0,0.666667,0,1,0.5,1,1,1,1,0.666667,0.5,1,0.666667,0.666667,0.8,0,0.666667,0.5,1,0.666667,0.333333,1,1,1,0,0.5,1,0.666667,0,0.4,1,1,1]
f_measure
0.725833 [1,1,1,1,0.666667,1,1,1,1,1,0.8,1,0.666667,0.5,1,1,0.666667,0.666667,0.666667,1,1,0,0.8,1,1,1,1,0.666667,0.8,1,1,1,0,1,0.8,0,1,1,0,0.666667,0.666667,0.666667,0.666667,0,0,0.666667,0.666667,0.666667,0.5,0,0,0.4,0.666667,1,0.666667,1,1,0,1,1,1,1,0.666667,1,1,0.666667,1,0,0.666667,0.666667,0.8,0.666667,1,0.4,1,1,0.666667,1,1,0.666667,1,0.666667,0.666667,0.8,0,0.666667,0,1,0.666667,0,1,0,1,1,0.666667,0,1,1,0.666667,0.666667]
f_measure
0.605238 [0.666667,0.285714,0,1,0,0,0,0.666667,0.666667,0.8,0,1,1,0.666667,0,1,0,0,0.666667,0.666667,1,0,1,1,0,0.8,1,0,1,1,1,1,0,1,1,0,0.5,0.8,0,1,0.8,0,0.666667,0.8,0,0.666667,0,0.666667,1,0.333333,1,0.571429,0.666667,0.5,0.666667,0.8,1,1,0.666667,1,1,0.666667,0.666667,1,1,1,0.571429,0,1,0.666667,0.5,0,1,1,0.5,0.4,0.666667,1,0.666667,0.666667,0.666667,0,1,0.8,0,1,0.5,0.666667,1,0.666667,0.666667,0,0.666667,0,0.666667,0.666667,0.8,1,1,0.5]
f_measure
0.625268 [0.4,1,0,0.5,1,0.666667,0.666667,0,0,0,1,0,1,1,0,0.666667,0,0.666667,1,1,1,0,0.666667,0.666667,0,0.666667,1,1,0.8,1,1,1,1,1,0.666667,0,0.571429,1,1,0,1,0.8,0,0.666667,0.4,0,0,1,0,1,0,0.666667,0.8,0,0,1,1,0.5,0.666667,1,1,1,1,0.666667,1,0.666667,1,1,1,0.5,0.666667,1,1,0.5,0.8,0.5,0,0.666667,0.8,0,0,0.5,0,0.5,1,1,0.666667,0.5,0.8,0,0,0,1,0,0.5,0,0.8,1,0.666667,0.8]
f_measure
0.650208 [0,0.666667,0.666667,1,0,1,1,0.666667,0.666667,1,1,1,1,1,0.5,1,0.333333,0.5,1,1,1,0,0.8,1,0,0.8,0.666667,0,1,1,0,1,0,0.8,0.5,0,0.666667,1,0,1,1,0.666667,0,0.4,0.5,0.8,1,1,0.5,1,0.8,0,0.4,1,0.666667,0.8,1,0.666667,0.666667,1,0.8,0.5,1,0.8,1,1,0.8,0,0.5,0,0,0,0.8,0.8,1,1,0.666667,0.666667,1,0.666667,0,0,0,0.5,0,1,0.666667,0,1,0.666667,1,0,0.666667,1,0.5,0.666667,0,1,0.666667,1]
f_measure
0.651458 [0,1,0.666667,0,1,0,0.666667,0.8,0.5,0.4,0.666667,0.666667,0.666667,1,0,1,0.666667,1,1,0.666667,1,0,1,0.666667,0,1,1,0,1,1,1,0.8,0,0.8,0.5,0.666667,0.5,0.5,0,1,1,0.5,0,0,0,0.8,0.666667,0.8,0,0.8,1,0.666667,0.4,1,0.666667,0,1,0.666667,1,1,1,1,1,0.666667,0.666667,0.5,1,0.666667,0.666667,0,0.666667,0,1,0,1,1,0,1,0.666667,0.666667,1,1,0,0.666667,0.666667,1,0,0.666667,0.666667,0.666667,1,0,1,1,0,0,0.8,1,1,1]
f_measure
0.642976 [0,0.8,0,1,0.4,0,0,0.5,0,0,0.666667,1,1,1,1,1,0,0.4,1,0.666667,0.5,0,0.666667,0.8,0,1,0.666667,0,0.666667,1,0,1,0,0.571429,1,0,1,0.666667,0.666667,1,1,0.666667,0,0,0.666667,1,0.666667,1,0.666667,0.8,0.666667,0,1,1,1,0.666667,1,0.666667,0.5,1,1,0.8,1,0.8,1,0.666667,1,0.666667,1,0,0.5,0,1,0.666667,1,1,1,1,0.8,0,1,1,0.5,0,0.333333,0,0,0.666667,1,0.666667,0.8,1,0.8,1,1,0,0.8,0.4,0,1]
f_measure
0.565119 [0,1,1,0.666667,0,0.666667,0.8,0.666667,0,1,0.666667,1,0.8,0.666667,0.666667,0.4,1,1,1,0.8,0,0,1,0.8,0,0,0,0,1,0.666667,0.666667,0.5,0,0.4,0.333333,0,0.666667,1,0.666667,1,0,0.666667,0,1,0,1,0.666667,0.666667,0.5,0,0,0.4,0,0.4,0,0.666667,1,0.8,0.571429,1,1,1,0.666667,0.4,0.666667,1,1,0.5,1,0,0,0,0.666667,0.8,0.666667,0.571429,0.5,1,1,1,0,0.666667,0.5,0.666667,0.666667,0.4,0,0.666667,0.666667,1,0.666667,0,0.5,1,0.8,0.666667,1,0,0.5,0.666667]
f_measure
0.689428 [0.666667,0.666667,0,0.666667,0,1,1,1,1,0.8,0,0.666667,0.8,1,1,1,0,0,1,0.4,1,1,0.666667,0.8,0.666667,0.666667,1,0,1,1,1,1,0,0.666667,1,0.666667,0.666667,1,0,0.8,0,0,0,0,0,0.666667,0,1,0.4,0.666667,0.8,0.666667,0.666667,0.5,0,0.5,0.8,0.666667,0.666667,1,1,0.666667,0.8,1,0.8,0.666667,1,0.666667,1,0,0.8,0.666667,1,1,0.666667,1,0.666667,1,1,0,1,0.4,1,0.333333,1,1,0.285714,0.8,1,0.5,0.8,0,1,1,1,0.666667,0.5,1,0.666667,1]
kappa
0.627452
kappa
0.671678
kappa
0.753593
kappa
0.646395
kappa
0.671536
kappa
0.696754
kappa
0.696754
kappa
0.684044
kappa
0.621093
kappa
0.713914
kb_relative_information_score
103.138796
kb_relative_information_score
106.164219
kb_relative_information_score
106.045818
kb_relative_information_score
103.293018
kb_relative_information_score
106.831756
kb_relative_information_score
107.659661
kb_relative_information_score
105.578602
kb_relative_information_score
107.159128
kb_relative_information_score
105.492699
kb_relative_information_score
106.384104
mean_absolute_error
0.014135
mean_absolute_error
0.013967
mean_absolute_error
0.014211
mean_absolute_error
0.014303
mean_absolute_error
0.01398
mean_absolute_error
0.013757
mean_absolute_error
0.014102
mean_absolute_error
0.013855
mean_absolute_error
0.014295
mean_absolute_error
0.013944
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
0.552292 [0,0.5,0,1,0,0,0,0,0.666667,1,1,1,0.666667,1,0,0.666667,1,0.5,1,1,1,0,0.5,1,0,1,1,0,1,0,1,1,0,0,0,0,0.333333,0.333333,0,1,0.666667,0.5,0.5,0,0,0.2,0,0,0.666667,1,0.333333,1,0,1,0,1,1,0,0.5,1,1,0.5,1,0.5,0.5,0.666667,1,0.333333,0.333333,0,1,0.5,1,1,0.666667,0.666667,0,1,1,0.5,0,0.666667,0,1,0,1,0.5,0.5,1,0.666667,0.5,0,0.333333,1,0.25,0,0.333333,0.5,1,1]
precision
0.632292 [1,0.5,0,0.5,0,0,1,0.5,0.5,1,1,0.666667,1,0.5,0,1,0,0.333333,1,1,1,0,1,1,0,0,0,0,1,0.666667,1,0.666667,0,1,0,0,1,1,0,1,1,1,0,0,1,1,0,0.2,0.666667,0.5,1,1,0.25,1,0.5,1,1,0.5,1,1,1,0.4,1,1,1,0.5,1,0,0.5,0,1,0.5,1,1,1,1,1,0.5,1,0.5,0.5,0.666667,0,1,0.333333,1,1,0.25,1,1,1,0,0.333333,1,0.5,0,0.25,1,1,1]
precision
0.755729 [1,1,1,1,1,1,1,1,1,1,0.666667,1,0.5,0.5,1,1,1,1,0.5,1,1,0,0.666667,1,1,1,1,1,0.666667,1,1,1,0,1,0.666667,0,1,1,0,0.5,1,0.5,0.5,0,0,1,1,1,0.5,0,0,0.333333,0.5,1,0.5,1,1,0,1,1,1,1,0.5,1,1,1,1,0,0.5,1,0.666667,1,1,0.25,1,1,1,1,1,1,1,1,0.5,0.666667,0,1,0,1,0.5,0,1,0,1,1,0.5,0,1,1,0.5,0.5]
precision
0.624792 [1,0.166667,0,1,0,0,0,1,0.5,0.666667,0,1,1,1,0,1,0,0,1,0.5,1,0,1,1,0,0.666667,1,0,1,1,1,1,0,1,1,0,0.333333,0.666667,0,1,0.666667,0,0.5,0.666667,0,1,0,1,1,0.2,1,0.4,1,0.5,1,0.666667,1,1,0.5,1,1,0.5,0.5,1,1,1,0.4,0,1,1,0.5,0,1,1,0.5,0.333333,1,1,1,1,0.5,0,1,0.666667,0,1,0.5,0.5,1,0.5,0.5,0,1,0,0.5,0.5,0.666667,1,1,0.333333]
precision
0.624792 [0.333333,1,0,0.333333,1,0.5,0.5,0,0,0,1,0,1,1,0,0.5,0,1,1,1,1,0,1,0.5,0,1,1,1,0.666667,1,1,1,1,1,1,0,0.4,1,1,0,1,0.666667,0,1,0.333333,0,0,1,0,1,0,0.5,0.666667,0,0,1,1,0.5,1,1,1,1,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,0.5,0.666667,0.333333,0,0.5,0.666667,0,0,0.5,0,0.333333,1,1,1,0.333333,0.666667,0,0,0,1,0,0.333333,0,0.666667,1,1,0.666667]
precision
0.654167 [0,0.5,1,1,0,1,1,1,0.5,1,1,1,1,1,0.333333,1,0.25,0.5,1,1,1,0,0.666667,1,0,0.666667,1,0,1,1,0,1,0,0.666667,0.5,0,0.5,1,0,1,1,1,0,0.333333,0.5,0.666667,1,1,0.333333,1,0.666667,0,0.333333,1,1,0.666667,1,1,0.5,1,0.666667,0.333333,1,0.666667,1,1,0.666667,0,0.5,0,0,0,0.666667,0.666667,1,1,0.5,0.5,1,1,0,0,0,0.333333,0,1,1,0,1,0.5,1,0,1,1,0.333333,0.5,0,1,1,1]
precision
0.656771 [0,1,1,0,1,0,0.5,0.666667,0.5,0.25,0.5,1,0.5,1,0,1,0.5,1,1,0.5,1,0,1,0.5,0,1,1,0,1,1,1,0.666667,0,0.666667,0.5,1,0.5,0.5,0,1,1,0.5,0,0,0,0.666667,0.5,0.666667,0,0.666667,1,0.5,0.333333,1,1,0,1,1,1,1,1,1,1,0.5,0.5,0.333333,1,1,1,0,0.5,0,1,0,1,1,0,1,1,1,1,1,0,0.5,1,1,0,0.5,0.5,0.5,1,0,1,1,0,0,0.666667,1,1,1]
precision
0.653437 [0,0.666667,0,1,0.25,0,0,0.5,0,0,1,1,1,1,1,1,0,0.333333,1,1,0.333333,0,0.5,0.666667,0,1,1,0,0.5,1,0,1,0,0.4,1,0,1,0.5,1,1,1,1,0,0,1,1,0.5,1,0.5,0.666667,0.5,0,1,1,1,0.5,1,1,0.5,1,1,0.666667,1,0.666667,1,0.5,1,1,1,0,0.333333,0,1,1,1,1,1,1,0.666667,0,1,1,0.5,0,0.25,0,0,1,1,1,0.666667,1,0.666667,1,1,0,0.666667,0.333333,0,1]
precision
0.578437 [0,1,1,1,0,1,0.666667,0.5,0,1,0.5,1,0.666667,0.5,1,0.333333,1,1,1,0.666667,0,0,1,0.666667,0,0,0,0,1,0.5,1,0.5,0,0.25,0.2,0,1,1,1,1,0,1,0,1,0,1,0.5,0.5,0.5,0,0,0.25,0,0.333333,0,0.5,1,0.666667,0.4,1,1,1,1,0.333333,1,1,1,0.5,1,0,0,0,0.5,0.666667,0.5,0.4,0.5,1,1,1,0,0.5,0.5,1,1,0.25,0,0.5,0.5,1,0.5,0,0.333333,1,0.666667,1,1,0,0.333333,1]
precision
0.72327 [0.5,1,0,1,0,1,1,1,1,0.666667,0,1,0.666667,1,1,1,0,0,1,0.333333,1,1,0.5,0.666667,1,0.5,1,0,1,1,1,1,0,0.5,1,1,1,1,0,0.666667,0,0,0,0,0,0.5,0,1,0.333333,1,0.666667,1,0.5,0.5,0,0.333333,0.666667,1,1,1,1,1,0.666667,1,0.666667,1,1,1,1,0,0.666667,1,1,1,0.5,1,1,1,1,0,1,0.333333,1,0.25,1,1,0.166667,0.666667,1,0.5,0.666667,0,1,1,1,1,0.333333,1,0.5,1]
predictive_accuracy
0.63125
predictive_accuracy
0.675
predictive_accuracy
0.75625
predictive_accuracy
0.65
predictive_accuracy
0.675
predictive_accuracy
0.7
predictive_accuracy
0.7
predictive_accuracy
0.6875
predictive_accuracy
0.625
predictive_accuracy
0.716981
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
0.63125 [0,1,0,1,0,0,0,0,1,1,1,0.5,1,1,0,1,0.5,1,1,1,1,0,1,1,0,1,1,0,1,0,1,1,0,0,0,0,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0.5,1,0,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,0.5,1,1,1,1,0,1,1,1,0,1,0,0.5,0,1,0.5,0.5,1,1,0.5,0,1,1,0.5,0,1,1,0.5,1]
recall
0.675 [1,1,0,0.5,0,0,0.5,1,0.5,0.5,1,1,1,0.5,0,1,0,1,1,0.5,1,0,1,1,0,0,0,0,1,1,1,1,0,1,0,0,1,1,0,1,0.5,1,0,0,1,1,0,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0,1,0.5,1,1,1,1,0.5,0.5,1,1,1,1,0,0.5,1,1,0.5,0.5,1,1,1,0,1,1,1,0,1,1,1,1]
recall
0.75625 [1,1,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0,1,1,0,1,0.5,1,1,0,0,0.5,0.5,0.5,0.5,0,0,0.5,1,1,1,1,1,0,1,1,1,1,1,1,1,0.5,1,0,1,0.5,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0,0.5,0,1,1,0,1,0,1,1,1,0,1,1,1,1]
recall
0.65 [0.5,1,0,1,0,0,0,0.5,1,1,0,1,1,0.5,0,1,0,0,0.5,1,1,0,1,1,0,1,1,0,1,1,1,1,0,1,1,0,1,1,0,1,1,0,1,1,0,0.5,0,0.5,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,0.5,0,1,1,0.5,0.5,0.5,1,0.5,0.5,1,0,1,1,0,1,0.5,1,1,1,1,0,0.5,0,1,1,1,1,1,1]
recall
0.675 [0.5,1,0,1,1,1,1,0,0,0,1,0,1,1,0,1,0,0.5,1,1,1,0,0.5,1,0,0.5,1,1,1,1,1,1,1,1,0.5,0,1,1,1,0,1,1,0,0.5,0.5,0,0,1,0,1,0,1,1,0,0,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,1,0,0,0.5,0,1,1,1,0.5,1,1,0,0,0,1,0,1,0,1,1,0.5,1]
recall
0.7 [0,1,0.5,1,0,1,1,0.5,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0,1,1,0,1,0.5,0,1,1,0,1,0,1,0.5,0,1,1,0,1,1,0.5,0,0.5,0.5,1,1,1,1,1,1,0,0.5,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0.5,0,0,0,1,1,1,1,1,1,1,0.5,0,0,0,1,0,1,0.5,0,1,1,1,0,0.5,1,1,1,0,1,0.5,1]
recall
0.7 [0,1,0.5,0,1,0,1,1,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,0,1,1,0,1,1,0,1,1,1,1,0,1,0.5,0.5,0.5,0.5,0,1,1,0.5,0,0,0,1,1,1,0,1,1,1,0.5,1,0.5,0,1,0.5,1,1,1,1,1,1,1,1,1,0.5,0.5,0,1,0,1,0,1,1,0,1,0.5,0.5,1,1,0,1,0.5,1,0,1,1,1,1,0,1,1,0,0,1,1,1,1]
recall
0.6875 [0,1,0,1,1,0,0,0.5,0,0,0.5,1,1,1,1,1,0,0.5,1,0.5,1,0,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0,1,1,0.5,1,1,0.5,0,0,0.5,1,1,1,1,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,0,1,0,1,0.5,1,1,1,1,1,0,1,1,0.5,0,0.5,0,0,0.5,1,0.5,1,1,1,1,1,0,1,0.5,0,1]
recall
0.625 [0,1,1,0.5,0,0.5,1,1,0,1,1,1,1,1,0.5,0.5,1,1,1,1,0,0,1,1,0,0,0,0,1,1,0.5,0.5,0,1,1,0,0.5,1,0.5,1,0,0.5,0,1,0,1,1,1,0.5,0,0,1,0,0.5,0,1,1,1,1,1,1,1,0.5,0.5,0.5,1,1,0.5,1,0,0,0,1,1,1,1,0.5,1,1,1,0,1,0.5,0.5,0.5,1,0,1,1,1,1,0,1,1,1,0.5,1,0,1,0.5]
recall
0.716981 [1,0.5,0,0.5,0,1,1,1,1,1,0,0.5,1,1,1,1,0,0,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,0,1,1,0.5,0.5,1,0,1,0,0,0,0,0,1,0,1,0.5,0.5,1,0.5,1,0.5,0,1,1,0.5,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,0,1,0.5,1,1,1,1,0.5,1,1,0,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1]
relative_absolute_error
0.713897
relative_absolute_error
0.705408
relative_absolute_error
0.717749
relative_absolute_error
0.722364
relative_absolute_error
0.706047
relative_absolute_error
0.694784
relative_absolute_error
0.712241
relative_absolute_error
0.699747
relative_absolute_error
0.721958
relative_absolute_error
0.704253
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
0.077669
root_mean_squared_error
0.07662
root_mean_squared_error
0.076867
root_mean_squared_error
0.077849
root_mean_squared_error
0.0767
root_mean_squared_error
0.075601
root_mean_squared_error
0.0769
root_mean_squared_error
0.075761
root_mean_squared_error
0.078033
root_mean_squared_error
0.076439
root_relative_squared_error
0.780602
root_relative_squared_error
0.770054
root_relative_squared_error
0.772538
root_relative_squared_error
0.782414
root_relative_squared_error
0.770858
root_relative_squared_error
0.759824
root_relative_squared_error
0.772872
root_relative_squared_error
0.761426
root_relative_squared_error
0.784267
root_relative_squared_error
0.76824
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