8888206
710
William Raynaut
9954
Supervised Classification
8311
weka.kf.HoeffdingTree(1)
6835536
mDataExp
Modelage
study_107
1491
one-hundred-plants-margin
https://www.openml.org/data/download/1592283/phpCsX3fx
-1
18692226
description
https://api.openml.org/data/download/18692226/description963247977466755263.xml
-1
18692227
predictions
https://api.openml.org/data/download/18692227/predictions8423245934425663980.arff
area_under_roc_curve
0.987252 [0.995561,1,1,0.96875,0.968711,0.967507,1,1,0.999014,0.96875,0.999369,1,1,0.874132,1,0.999842,1,0.959616,0.925623,0.942649,0.999566,1,0.96733,1,0.999428,0.959142,0.989781,0.999763,0.999428,1,1,1,0.999921,0.992582,1,0.967606,0.995462,0.990491,0.999842,0.999961,0.935961,0.999566,1,0.999961,0.999566,0.999961,0.999645,0.998935,0.999763,0.968415,0.999171,0.998323,0.968395,0.996784,0.99779,0.925979,1,0.999645,0.997711,0.997396,0.999921,0.999803,0.998185,0.999921,0.999467,0.967862,0.990885,1,0.967527,0.966836,0.968099,0.999684,0.964883,1,0.935527,0.999921,0.999724,0.931424,1,1,0.998382,0.967823,0.999684,0.998106,0.999507,0.968316,1,0.96804,0.999527,1,0.999329,0.999388,0.999605,0.99929,0.999882,0.999961,0.999803,0.999329,0.926807,1]
average_cost
0
f_measure
0.843727 [0.733333,0.967742,1,0.967742,0.933333,0.774194,1,0.969697,0.787879,0.967742,0.903226,1,0.967742,0.733333,1,0.903226,1,0.344828,0.514286,0.205128,0.909091,1,0.758621,1,0.909091,0.444444,0.457143,0.941176,0.909091,0.967742,0.967742,1,0.933333,0.580645,0.969697,0.848485,0.8125,0.533333,0.903226,0.969697,0.722222,0.909091,1,0.9375,0.941176,0.967742,0.875,0.8125,0.888889,0.83871,0.875,0.75,0.909091,0.764706,0.733333,0.413793,1,0.9375,0.625,0.758621,0.914286,0.914286,0.727273,0.9375,0.903226,0.875,0.457143,1,0.774194,0.848485,0.882353,0.903226,0.685714,1,0.764706,0.969697,0.903226,0.666667,1,1,0.727273,0.903226,0.909091,0.666667,0.83871,0.866667,1,0.866667,0.83871,1,0.758621,0.875,0.866667,0.827586,0.9375,0.967742,0.864865,0.882353,0.5,1]
kappa
0.84154
kb_relative_information_score
1400.591464
mean_absolute_error
0.003231
mean_prior_absolute_error
0.0198
number_of_instances
1600 [16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16]
precision
0.850092 [0.785714,1,1,1,1,0.8,1,0.941176,0.764706,1,0.933333,1,1,0.785714,1,0.933333,1,0.384615,0.473684,0.173913,0.882353,1,0.846154,1,0.882353,0.4,0.421053,0.888889,0.882353,1,1,1,1,0.6,0.941176,0.823529,0.8125,0.571429,0.933333,0.941176,0.65,0.882353,1,0.9375,0.888889,1,0.875,0.8125,0.8,0.866667,0.875,0.75,0.882353,0.722222,0.785714,0.461538,1,0.9375,0.625,0.846154,0.842105,0.842105,0.705882,0.9375,0.933333,0.875,0.421053,1,0.8,0.823529,0.833333,0.933333,0.631579,1,0.722222,0.941176,0.933333,0.818182,1,1,0.705882,0.933333,0.882353,0.647059,0.866667,0.928571,1,0.928571,0.866667,1,0.846154,0.875,0.928571,0.923077,0.9375,1,0.761905,0.833333,0.75,1]
predictive_accuracy
0.843125
prior_entropy
6.643856
recall
0.843125 [0.6875,0.9375,1,0.9375,0.875,0.75,1,1,0.8125,0.9375,0.875,1,0.9375,0.6875,1,0.875,1,0.3125,0.5625,0.25,0.9375,1,0.6875,1,0.9375,0.5,0.5,1,0.9375,0.9375,0.9375,1,0.875,0.5625,1,0.875,0.8125,0.5,0.875,1,0.8125,0.9375,1,0.9375,1,0.9375,0.875,0.8125,1,0.8125,0.875,0.75,0.9375,0.8125,0.6875,0.375,1,0.9375,0.625,0.6875,1,1,0.75,0.9375,0.875,0.875,0.5,1,0.75,0.875,0.9375,0.875,0.75,1,0.8125,1,0.875,0.5625,1,1,0.75,0.875,0.9375,0.6875,0.8125,0.8125,1,0.8125,0.8125,1,0.6875,0.875,0.8125,0.75,0.9375,0.9375,1,0.9375,0.375,1]
relative_absolute_error
0.163174
root_mean_prior_squared_error
0.099499
root_mean_squared_error
0.05191
root_relative_squared_error
0.521711
total_cost
0
area_under_roc_curve
0.982717 [0.987421,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.993671,0.735759,0.987421,1,1,1,1,1,0.996835,0.990506,1,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.748418,1,1,1,1,0.993711,1,1,1,0.993711,1,1,1,0.993671,1,1,1,0.990506,1,1,0.974843,1,1,1,1,0.993711,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,0.993671,0.737342,1]
area_under_roc_curve
0.989381 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,0.743671,0.990506,0.993711,1,1,1,1,1,0.990506,0.990506,1,1,1,1,1,1,1,1,0.993711,0.987421,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.484277,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,0.974684,1]
area_under_roc_curve
0.985366 [0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.69462,1,1,0.743671,1,1,0.984177,1,1,1,1,1,1,1,0.969937,1,1,1,0.968553,1,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,0.992089,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.742089,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,1]
area_under_roc_curve
0.988472 [1,1,1,1,0.75,1,1,1,0.993671,1,1,1,1,1,1,1,1,0.981013,0.468553,0.955696,1,1,1,1,1,0.990506,1,1,1,1,1,1,1,0.990506,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,0.971519,1,1,1,0.748418,1,0.981132,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,0.993711,1]
area_under_roc_curve
0.985841 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,0.993671,1,0.993671,0.993671,1,1,1,1,1,0.971519,1,1,1,1,1,1,1,1,1,1,0.987342,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,0.987421,0.75,0.987421,0.992089,0.731013,1,0.996835,0.996835,1,1,1,1,1,1,1,0.987421,1,1,0.746835,1,1,1,1,0.748418,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1]
area_under_roc_curve
0.989004 [0.987342,1,1,1,1,0.748418,1,1,1,0.75,0.996835,1,1,1,1,1,1,1,1,0.96519,1,1,0.996835,1,0.996835,0.990506,0.987342,1,1,1,1,1,1,1,1,0.748418,1,0.990506,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,0.990506,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.993671,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.987421,1]
area_under_roc_curve
0.991776 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993711,0.971519,0.977848,1,1,0.996835,1,0.996835,0.474843,0.968553,1,1,1,1,1,1,0.981132,1,1,0.993671,0.987342,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,1,1,1,0.984177,1,1,1,1,1,1,1,1,1,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.5,1,1,1,1,0.996835,1,1,1,1,1,0.987342,1]
area_under_roc_curve
0.985743 [0.990506,1,1,0.75,1,1,1,1,1,1,1,1,1,1,1,1,1,0.974843,0.990506,0.974684,0.996835,1,1,1,1,0.993711,1,1,0.996855,1,1,1,1,1,1,1,0.977848,1,1,1,1,1,1,1,0.996855,1,1,1,1,1,0.993711,0.996835,1,1,1,0.990506,1,1,1,1,1,1,1,1,1,0.493711,0.987421,1,1,0.996835,1,1,1,1,0.995253,1,1,0.468553,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,1,1,1,1,1,1,0.996835,1]
area_under_roc_curve
0.992426 [0.993711,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,0.993671,0.993711,1,1,1,1,1,0.993711,0.993711,1,1,1,1,1,1,1,1,1,0.993671,0.981013,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.996835,1,0.990506,1,0.993711,1,1,1,0.993671,1,1,1,1,1,1,0.993671,1,1,1,1,0.993711,0.987342,1,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,0.996835,1,1,1,1,1,1,1,1,1,1,0.742089,1]
area_under_roc_curve
0.98333 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.75,1,1,1,0.993711,1,0.987421,1,1,1,1,1,0.981132,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.993671,1,1,1,0.990506,1,0.996855,1,0.993671,1,0.748418,0.993711,1,1,0.738924,1,0.748418,1,1,1,1,1,1,0.490566,1,0.987421,1,0.996835,1,1,1,1,0.996835,0.996835,1,1,1,1,1,1,1,1]
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
0.802708 [0,0.666667,1,1,0.666667,1,1,0.666667,1,1,0.666667,1,1,0,1,1,1,0,0.5,0,1,1,1,1,1,0.8,0.5,0.8,1,1,1,1,0.666667,0,1,0.666667,1,0.666667,1,1,0.666667,0.666667,1,1,1,1,1,0.5,1,0.666667,1,1,1,1,0,0,1,1,0,1,1,0.666667,0.5,0.8,1,1,0.4,1,0.666667,0,1,1,1,1,0,1,0.666667,0,1,1,1,1,1,0.666667,1,0.666667,1,1,0.666667,1,1,1,1,0.666667,1,1,0.666667,0.666667,0.5,1]
f_measure
0.843125 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,0.666667,1,0.666667,0.5,0.666667,1,1,1,1,1,0.5,0.5,1,0.8,1,1,1,1,1,1,0.666667,0,0.666667,1,1,0.5,1,1,1,1,1,1,1,0.8,1,1,0.666667,0.666667,1,1,0,1,1,1,0.666667,0.666667,0.666667,0.666667,1,1,0.666667,1,1,0,1,0.666667,1,1,1,1,1,0.666667,1,1,1,0,0.8,0.666667,1,0.5,1,1,0.8,0,1,0.666667,1,0.666667,0.666667,1,1,1,1,0,1]
f_measure
0.847917 [0.666667,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,0,1,1,0,1,1,0.333333,1,1,1,1,1,1,0.666667,0,1,1,1,0,1,1,0.5,1,1,1,0.8,1,0.666667,1,1,1,1,1,1,0.8,1,0,1,1,0.666667,0.666667,1,1,1,1,1,0.8,0,1,0,1,1,1,0.666667,1,0.666667,1,1,0.5,1,1,0.666667,1,1,0.666667,1,1,1,1,0.8,1,1,1,1,0.666667,1,1,0.8,1,0,1]
f_measure
0.832083 [1,1,1,1,0.666667,0.666667,1,1,0.5,1,1,1,1,0.666667,1,1,1,0,0,0,1,1,1,1,0,0.4,0.8,1,1,1,1,1,1,0.666667,1,0.666667,1,0.666667,0.666667,1,0.8,0.666667,1,1,1,1,0.666667,1,0.8,1,1,0.666667,1,0.666667,1,0.666667,1,1,0.666667,1,0.666667,1,1,1,1,1,0,1,1,1,0.666667,1,0,1,1,1,1,0.666667,1,1,1,1,1,0.666667,0,1,1,1,1,1,0.666667,1,0,0.8,1,0,1,0.8,0,1]
f_measure
0.812708 [0.666667,1,1,1,1,0.8,1,1,0,1,1,1,1,0.666667,1,1,1,0,0.4,0.5,0.5,1,0.666667,1,1,1,0,1,0.666667,0.666667,1,1,1,0.666667,1,1,1,0.4,1,1,0.8,1,1,0,1,0,1,0.666667,1,1,0,0,0.666667,0.5,0.666667,0.5,1,0.8,0.8,1,1,1,1,1,0.666667,1,0,1,1,0.666667,1,1,0.666667,1,0.666667,1,1,0.666667,1,1,0.666667,1,1,0.666667,0.666667,1,1,1,1,1,1,0.5,1,0,0.666667,1,0.8,1,0.666667,1]
f_measure
0.850625 [0.666667,1,1,1,1,0,1,1,0.666667,0.666667,0.8,1,0,0.666667,1,1,1,1,1,0.4,1,1,0.666667,1,0.8,0.4,0.4,1,1,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0.8,1,1,0.666667,1,1,1,0.666667,1,0.666667,1,1,0.8,1,0,0.5,1,1,0.5,1,1,1,0.5,1,1,1,0.666667,1,1,1,1,0.666667,1,1,1,1,0.8,0.666667,1,1,1,0.666667,1,0.5,1,1,1,1,0.8,1,1,1,1,1,1,1,0.8,1,0,1]
f_measure
0.808333 [0.8,1,1,1,1,0.666667,1,1,0.666667,1,1,1,1,0.666667,1,0.666667,1,0,0.4,0,1,1,0.5,1,0.8,0,0,1,1,1,0.666667,1,1,0,1,1,0.8,0,1,1,1,0.666667,1,1,1,1,1,0.666667,1,0.666667,1,0.8,1,0.666667,0.666667,0.5,1,0.666667,0,1,0.8,0.8,1,0.666667,0.666667,1,0.666667,1,1,1,1,1,1,1,0.666667,0.666667,1,1,1,1,0.666667,1,0.8,0.666667,1,0.666667,1,0,1,1,0.666667,1,0.666667,1,1,1,1,1,0,1]
f_measure
0.825685 [0.666667,1,1,0.666667,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,0,0.571429,0,0.8,1,0.8,1,1,0,0.666667,0.8,0,1,1,1,1,1,0.8,1,0,1,1,0.666667,0.666667,1,1,1,0.666667,1,1,1,0.666667,0,0.666667,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,0,0,1,0.666667,0.8,1,1,0.8,1,0.8,1,1,0,1,1,0.666667,1,0.666667,1,0.666667,0.666667,1,0,1,1,0,1,1,1,1,1,0.8,1,0.666667,1]
f_measure
0.828393 [0.666667,1,1,1,1,0.5,1,1,0.5,1,0,1,1,1,1,1,1,0.666667,0.666667,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0.666667,1,1,0.8,0,0.666667,1,0,1,1,1,1,1,0.666667,0.8,0.666667,1,0.666667,0.666667,1,0.5,0.666667,0,1,1,0.666667,0,1,1,0.666667,1,1,1,0.8,1,0.8,1,1,0,0.5,1,1,1,1,1,1,1,0.571429,1,1,0.5,1,1,1,0.666667,1,1,0.666667,0.666667,1,1,0.666667,1,1,0.666667,0.666667,1]
f_measure
0.860625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,0,0,0.4,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,1,0.666667,1,0.666667,0.666667,1,1,1,1,1,1,1,0.666667,1,1,0.666667,1,1,1,0.666667,1,1,1,1,0.4,0.666667,1,1,0.4,1,0.666667,1,0.5,1,0.666667,0.666667,0.666667,1,0,1,0.666667,1,1,1,1,1,1,0,1,0,1,0.8,1,1,1,1,0.5,0.8,1,1,1,1,1,1,1,1]
kappa
0.816818
kappa
0.854718
kappa
0.854666
kappa
0.835722
kappa
0.823107
kappa
0.861001
kappa
0.823107
kappa
0.842041
kappa
0.835755
kappa
0.867335
kb_relative_information_score
135.203355
kb_relative_information_score
140.82432
kb_relative_information_score
140.898627
kb_relative_information_score
140.991564
kb_relative_information_score
138.453993
kb_relative_information_score
143.685633
kb_relative_information_score
136.297634
kb_relative_information_score
139.34836
kb_relative_information_score
142.529611
kb_relative_information_score
142.358367
mean_absolute_error
0.003775
mean_absolute_error
0.002992
mean_absolute_error
0.003035
mean_absolute_error
0.003229
mean_absolute_error
0.003436
mean_absolute_error
0.002854
mean_absolute_error
0.003743
mean_absolute_error
0.003238
mean_absolute_error
0.003206
mean_absolute_error
0.002801
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 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1]
number_of_instances
160 [1,2,2,1,2,1,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,1,1,1,2,2,2,2,1,2,2,2,2,2,1,1,1,1,2,1,1,2,2,2,2,1,1,2,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,1,2,2,1,1,1,2,1,2,2,1,2,2,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,1,2,2,1]
number_of_instances
160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2]
number_of_instances
160 [2,2,2,1,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,2,1,1,2,1,1,2,2,1,2,2,1,2,2,2,1,1,1,1,1,2,2,1,1,1,2,1,2,1,2,2,2,1,1,2,1,2,1,2,1,2,1,1,2,1,2,2,2,2,1,2,2,2,1,2,1,2,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,1,1,2,2,1,2,2,1,2]
number_of_instances
160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2]
number_of_instances
160 [2,1,2,2,1,2,1,2,1,2,2,2,1,1,1,2,2,2,1,2,2,2,2,2,2,2,2,1,1,2,1,1,2,2,1,2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,1,1,2,1,2,2,1,2,2,1,2,2,1,1,2,2,1,2,2,2,2,2,1,1,2,1,2,2,2,1,1,2,2,2,1,1,1,1,2,2,1,2,1,1,2,1,2,1,1,2]
number_of_instances
160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2]
number_of_instances
160 [2,1,1,2,1,2,2,2,1,2,1,1,2,1,1,2,1,1,2,2,2,2,2,2,2,1,1,2,1,2,2,1,1,1,2,2,2,2,2,1,2,2,2,2,1,2,2,2,1,1,1,2,2,1,2,2,2,2,2,1,2,2,1,2,2,1,1,2,2,2,1,2,2,1,2,1,1,1,1,1,2,1,2,2,2,2,2,1,1,2,1,2,2,1,1,2,2,1,2,2]
number_of_instances
160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1]
number_of_instances
160 [1,2,1,2,2,1,2,1,2,1,1,1,2,2,2,1,1,1,2,1,2,2,1,2,2,1,1,2,2,1,2,2,1,1,2,2,2,2,2,1,1,2,2,2,2,2,1,2,1,1,2,2,2,2,2,1,2,1,2,2,2,2,2,2,1,1,2,1,2,1,1,1,2,2,2,2,1,1,1,2,2,1,1,1,2,2,2,2,1,2,2,2,2,2,1,2,1,2,2,1]
precision
0.821875 [0,1,1,1,1,1,1,0.5,1,1,1,1,1,0,1,1,1,0,0.5,0,1,1,1,1,1,0.666667,0.5,0.666667,1,1,1,1,1,0,1,0.5,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.333333,1,1,1,1,1,1,0,0,1,1,0,1,1,0.5,0.5,0.666667,1,1,0.333333,1,0.5,0,1,1,1,1,0,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,0.5,1]
precision
0.866667 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1,0.666667,1,1,1,1,1,1,0.5,0,0.5,1,1,0.333333,1,1,1,1,1,1,1,0.666667,1,1,1,0.5,1,1,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0,1,0.5,1,1,1,1,1,1,1,1,1,0,0.666667,0.5,1,0.5,1,1,0.666667,0,1,1,1,1,1,1,1,1,1,0,1]
precision
0.863542 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0.25,1,1,1,1,1,1,1,0,1,1,1,0,1,1,0.5,1,1,1,0.666667,1,1,1,1,1,1,1,1,0.666667,1,0,1,1,0.5,1,1,1,1,1,1,0.666667,0,1,0,1,1,1,0.5,1,0.5,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,1,0.666667,1,0,1]
precision
0.861458 [1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0.333333,0.666667,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,0.666667,0.5,1,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0.666667,1,0,1,0.666667,0,1]
precision
0.843229 [1,1,1,1,1,0.666667,1,1,0,1,1,1,1,0.5,1,1,1,0,0.25,0.5,0.5,1,1,1,1,1,0,1,0.5,1,1,1,1,1,1,1,1,0.333333,1,1,0.666667,1,1,0,1,0,1,1,1,1,0,0,1,0.333333,0.5,0.5,1,0.666667,0.666667,1,1,1,1,1,1,1,0,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0,1,1,0.666667,1,0.5,1]
precision
0.872917 [1,1,1,1,1,0,1,1,0.5,1,0.666667,1,0,0.5,1,1,1,1,1,0.333333,1,1,1,1,0.666667,0.333333,0.333333,1,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,1,1,1,1,1,0.666667,1,0,0.5,1,1,0.5,1,1,1,0.333333,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,1,1,1,0.5,1,1,1,1,0.666667,1,1,1,1,1,1,1,0.666667,1,0,1]
precision
0.834375 [0.666667,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0.333333,0,1,1,0.5,1,0.666667,0,0,1,1,1,1,1,1,0,1,1,0.666667,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0.666667,1,0.5,1,0.5,1,1,0,1,0.666667,0.666667,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,0.666667,0.5,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,0,1]
precision
0.845625 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0.4,0,0.666667,1,0.666667,1,1,0,0.5,0.666667,0,1,1,1,1,1,0.666667,1,0,1,1,0.5,1,1,1,1,0.5,1,1,1,0.5,0,0.5,0.5,1,1,1,0.5,1,1,1,0.333333,1,1,1,1,1,0,0,1,1,0.666667,1,1,0.666667,1,0.666667,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,0.666667,1,1,1]
precision
0.86125 [0.5,1,1,1,1,0.333333,1,1,0.5,1,0,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,0.5,1,1,0.666667,0,1,1,0,1,1,1,1,1,0.5,0.666667,0.5,1,1,1,1,0.5,1,0,1,1,1,0,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0,0.5,1,1,1,1,1,1,1,0.4,1,1,0.333333,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1]
precision
0.881771 [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0.25,1,1,1,1,1,0,0,1,1,1,1,1,1,0.333333,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.333333,1,1,1,0.333333,1,0.5,1,0.5,1,1,0.5,0.5,1,0,1,1,1,1,1,1,1,1,0,1,0,1,0.666667,1,1,1,1,0.5,0.666667,1,1,1,1,1,1,1,1]
predictive_accuracy
0.81875
predictive_accuracy
0.85625
predictive_accuracy
0.85625
predictive_accuracy
0.8375
predictive_accuracy
0.825
predictive_accuracy
0.8625
predictive_accuracy
0.825
predictive_accuracy
0.84375
predictive_accuracy
0.8375
predictive_accuracy
0.86875
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
prior_entropy
6.643856
recall
0.81875 [0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,0,1,1,1,0,0.5,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0,1,1,0,1,1,1,0.5,1,1,1,0.5,1,1,0,1,1,1,1,0,1,0.5,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,1]
recall
0.85625 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,0,1,0.5,1,0.5,0.5,1,1,1,1,0,1]
recall
0.85625 [0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,1,0,1,1,0.5,1,1,1,1,1,1,0.5,0,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1]
recall
0.8375 [1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,0,0,0,1,1,1,1,0,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,1,0.5,0,1,1,1,1,1,0.5,1,0,1,1,0,1,1,0,1]
recall
0.825 [0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,0.5,0.5,1,0.5,1,1,1,0,1,1,0.5,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,0,1,0,1,0.5,1,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1]
recall
0.8625 [0.5,1,1,1,1,0,1,1,1,0.5,1,1,0,1,1,1,1,1,1,0.5,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1]
recall
0.825 [1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0.5,1,0,0.5,0,1,1,0.5,1,1,0,0,1,1,1,0.5,1,1,0,1,1,1,0,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,0,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0,1,1,1,1,0.5,1,1,1,1,1,0,1]
recall
0.84375 [0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,1,1,0,1,1,0.5,1,0.5,1,0.5,0.5,1,0,1,1,0,1,1,1,1,1,1,1,0.5,1]
recall
0.8375 [1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0.5,1,0,1,1,1,1,1,1,1,1,1,0.5,0.5,1,0.5,0.5,0,1,1,0.5,0,1,1,0.5,1,1,1,1,1,1,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,1,1,0.5,0.5,1]
recall
0.86875 [1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,0.5,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1]
relative_absolute_error
0.190648
relative_absolute_error
0.151093
relative_absolute_error
0.153301
relative_absolute_error
0.163056
relative_absolute_error
0.173527
relative_absolute_error
0.144165
relative_absolute_error
0.189065
relative_absolute_error
0.163532
relative_absolute_error
0.161907
relative_absolute_error
0.141445
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
0.057316
root_mean_squared_error
0.050656
root_mean_squared_error
0.04981
root_mean_squared_error
0.051015
root_mean_squared_error
0.054551
root_mean_squared_error
0.047678
root_mean_squared_error
0.05532
root_mean_squared_error
0.052561
root_mean_squared_error
0.050585
root_mean_squared_error
0.048792
root_relative_squared_error
0.576045
root_relative_squared_error
0.509107
root_relative_squared_error
0.500611
root_relative_squared_error
0.512721
root_relative_squared_error
0.548254
root_relative_squared_error
0.479186
root_relative_squared_error
0.555984
root_relative_squared_error
0.528257
root_relative_squared_error
0.508397
root_relative_squared_error
0.490379
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