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