1645381
1
Jan van Rijn
9956
Supervised Classification
1728
weka.HoeffdingTree(4)
2371
weka.classifiers.trees.HoeffdingTree -- -L 2 -S 1 -E 1.0E-7 -H 0.05 -M 0.01 -G 200.0 -N 0.0
L
2
1728
S
1
1728
E
1.0E-7
1728
H
0.05
1728
M
0.01
1728
G
200.0
1728
N
0.0
1728
weka
weka_3.7.13
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
4184604
description
https://api.openml.org/data/download/4184604/weka_generated_run4889418874362352620.xml
-1
4184607
model_readable
https://api.openml.org/data/download/4184607/WekaModel_weka.classifiers.trees.HoeffdingTree527245656563530559.model
-1
4184606
model_serialized
https://api.openml.org/data/download/4184606/WekaSerialized_weka.classifiers.trees.HoeffdingTree7427801242454564251.model
-1
4184605
predictions
https://api.openml.org/data/download/4184605/weka_generated_predictions8291989699127287214.arff
area_under_roc_curve
0.926838 [0.898611,0.968691,0.87346,0.936592,0.902183,0.936592,0.873243,0.936039,0.873342,0.968454,0.967427,0.805946,0.905954,0.968316,0.873835,0.96873,0.872374,0.936829,1,0.905618,0.968395,0.77288,0.935763,0.937342,0.743387,0.905776,0.87421,0.681834,1,0.937066,0.935526,0.968434,0.870973,0.968079,0.967684,0.806913,0.936079,0.999645,0.873283,0.875,0.999961,0.903072,0.904533,0.902697,0.807604,0.968493,0.807328,0.874052,0.872868,0.96573,0.966776,0.968256,0.998934,0.935625,0.869058,0.96571,0.96873,0.901966,0.999961,0.9375,1,0.968651,0.937184,0.967783,0.999684,0.936671,0.968691,0.936552,0.968612,0.901394,0.968474,0.932802,0.96875,0.936552,0.906191,0.968651,0.967131,0.999645,0.968178,0.936079,0.936789,0.997394,0.777835,0.967743,0.873697,0.968474,0.869907,0.968158,1,0.967842,0.905816,0.84073,0.936888,0.937342,0.968632,0.905441,0.968079,0.96875,0.936908,0.998618]
average_cost
0
f_measure
0.777584 [0.685714,0.909091,0.6875,0.848485,0.628571,0.8,0.6875,0.764706,0.666667,0.875,0.823529,0.4,0.866667,0.875,0.827586,0.967742,0.555556,0.848485,0.967742,0.83871,0.9375,0.333333,0.756757,0.866667,0.4375,0.787879,0.827586,0.363636,1,0.875,0.705882,0.9375,0.625,0.882353,0.875,0.512821,0.823529,0.941176,0.758621,0.857143,0.967742,0.615385,0.692308,0.580645,0.466667,0.83871,0.529412,0.774194,0.727273,0.647059,0.731707,0.882353,0.909091,0.625,0.4375,0.714286,0.967742,0.5625,0.969697,0.933333,1,0.9375,0.903226,0.8125,0.909091,0.848485,0.909091,0.827586,0.903226,0.333333,0.909091,0.55,0.967742,0.777778,0.896552,0.882353,0.787879,0.969697,0.83871,0.8125,0.8125,0.705882,0.4,0.83871,0.733333,0.848485,0.529412,0.833333,0.941176,0.823529,0.866667,0.538462,0.875,0.896552,0.9375,0.75,0.83871,0.933333,0.83871,0.833333]
kappa
0.777639
kb_relative_information_score
1265.302501
mean_absolute_error
0.004447
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
0.788405 [0.6,0.882353,0.6875,0.823529,0.578947,0.857143,0.6875,0.722222,0.818182,0.875,0.777778,0.428571,0.928571,0.875,0.923077,1,0.5,0.823529,1,0.866667,0.9375,0.357143,0.666667,0.928571,0.4375,0.764706,0.923077,0.666667,1,0.875,0.666667,0.9375,0.625,0.833333,0.875,0.434783,0.777778,0.888889,0.846154,1,1,0.8,0.9,0.6,0.5,0.866667,0.5,0.8,0.705882,0.611111,0.6,0.833333,0.882353,0.625,0.4375,0.576923,1,0.5625,0.941176,1,1,0.9375,0.933333,0.8125,0.882353,0.823529,0.882353,0.923077,0.933333,0.5,0.882353,0.458333,1,0.7,1,0.833333,0.764706,0.941176,0.866667,0.8125,0.8125,0.666667,0.555556,0.866667,0.785714,0.823529,0.5,0.75,0.888889,0.777778,0.928571,0.7,0.875,1,0.9375,0.75,0.866667,1,0.866667,0.75]
predictive_accuracy
0.779862
prior_entropy
6.643831
recall
0.779862 [0.8,0.9375,0.6875,0.875,0.6875,0.75,0.6875,0.8125,0.5625,0.875,0.875,0.375,0.8125,0.875,0.75,0.9375,0.625,0.875,0.9375,0.8125,0.9375,0.3125,0.875,0.8125,0.4375,0.8125,0.75,0.25,1,0.875,0.75,0.9375,0.625,0.9375,0.875,0.625,0.875,1,0.6875,0.75,0.9375,0.5,0.5625,0.5625,0.4375,0.8125,0.5625,0.75,0.75,0.6875,0.9375,0.9375,0.9375,0.625,0.4375,0.9375,0.9375,0.5625,1,0.875,1,0.9375,0.875,0.8125,0.9375,0.875,0.9375,0.75,0.875,0.25,0.9375,0.6875,0.9375,0.875,0.8125,0.9375,0.8125,1,0.8125,0.8125,0.8125,0.75,0.3125,0.8125,0.6875,0.875,0.5625,0.9375,1,0.875,0.8125,0.4375,0.875,0.8125,0.9375,0.75,0.8125,0.875,0.8125,0.9375]
relative_absolute_error
0.224615
root_mean_prior_squared_error
0.099499
root_mean_squared_error
0.064848
root_relative_squared_error
0.65175
total_cost
0
area_under_roc_curve
0.936197 [1,1,0.496855,1,0.993671,0.993671,0.496835,1,1,1,0.996855,0.993671,1,1,1,1,1,1,1,1,0.5,0.745253,0.996835,0.75,0.487342,1,1,1,1,0.5,1,1,1,1,1,1,0.996855,1,1,0.5,1,1,0.993711,0.996835,1,1,0.748418,0.996855,0.746835,0.992089,1,1,1,1,0.974843,1,1,0.993711,1,1,1,1,1,0.993711,1,0.995253,1,1,1,1,1,0.993671,1,1,1,1,1,1,1,1,1,1,0.75,1,0.496855,1,0.748418,1,1,1,0.75,0.748418,1,1,0.75,0.748418,1,1,1,1]
area_under_roc_curve
0.914025 [1,1,1,1,1,0.745253,1,1,0.496835,1,1,0.990506,1,1,1,1,0.75,0.996855,1,0.746835,1,0.746835,0.996835,1,0.740506,0.5,0.5,0.746835,1,1,1,1,1,0.996855,0.493711,0.490506,1,1,1,1,1,1,0.493711,1,1,1,0.490506,1,1,1,1,1,1,0.990506,1,0.996835,1,0.987421,1,1,1,0.75,1,1,1,0.748418,1,0.496855,1,0.746835,0.75,0.996835,1,1,1,1,0.996835,0.993671,1,1,0.996855,0.995253,0.493711,1,1,1,1,0.746835,1,1,0.75,0.743671,1,1,1,0.75,0.993711,1,1,1]
area_under_roc_curve
0.932517 [1,1,1,1,0.990506,1,1,1,1,1,1,1,0.748418,0.75,1,1,0.996835,0.75,1,1,1,0.481013,0.746835,1,1,1,1,0.745253,1,1,1,1,1,0.75,1,0.993711,1,1,1,1,1,1,1,0.748418,0.481013,1,0.740506,0.75,0.743671,0.993711,1,0.748418,0.996835,1,0.981132,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.990506,1,0.737342,1,1,1,1,1,1,1,0.748418,1,1,1,0.995253,0.993711,1,0.738924,1,1,1,1,0.493671,1,1,1,1,1,1,1,0.996855]
area_under_roc_curve
0.923914 [1,1,0.996835,1,1,0.5,0.75,1,1,1,1,0.493711,1,1,0.5,1,0.75,1,1,1,1,0.742089,1,1,0.490566,1,1,0.490506,1,1,1,1,0.738924,1,1,0.490566,0.996855,1,0.493711,1,1,1,0.490566,0.988924,0.75,1,1,0.75,1,0.993711,1,1,1,0.746835,0.75,0.996835,1,0.993711,1,1,1,1,1,1,1,1,1,1,1,1,1,0.748418,1,1,0.75,0.75,0.745253,1,1,1,1,1,1,1,1,0.75,1,1,1,1,1,1,0.75,1,1,1,0.996835,1,1,1]
area_under_roc_curve
0.904749 [0.748418,1,0.745253,1,1,1,1,0.496835,0.5,0.5,0.995253,0.496855,0.5,1,0.5,1,0.748418,1,1,1,1,0.968553,1,0.5,1,0.746835,1,1,1,1,1,1,1,1,1,1,1,1,0.490566,0.5,1,0.995253,1,0.746835,0.738924,0.75,0.748418,0.996835,1,1,0.746835,1,1,1,0.487342,0.748418,1,0.748418,1,1,1,1,1,1,1,1,1,1,1,0.996835,1,1,0.75,1,0.75,1,0.996855,1,1,0.993671,0.996835,1,0.987421,1,1,1,0.740506,1,1,1,0.5,1,1,0.496855,1,1,1,1,0.5,0.995253]
area_under_roc_curve
0.939362 [1,1,0.748418,1,0.993711,1,1,1,1,1,1,0.496855,1,1,1,1,0.996835,1,1,1,1,0.496855,0.993671,1,0.487421,1,0.75,0.493711,1,1,0.496855,1,1,1,1,0.981132,1,1,1,1,1,0.993671,0.748418,1,1,1,1,1,1,1,0.990506,1,0.993671,1,1,0.987342,1,0.75,1,1,1,1,0.75,1,1,1,1,1,1,0.745253,1,0.987421,1,0.996835,1,1,1,1,1,1,0.496835,0.993711,0.5,1,0.496835,1,1,1,1,0.996855,1,1,0.75,1,1,1,0.748418,1,1,1]
area_under_roc_curve
0.936336 [0.996855,1,1,0.5,1,1,1,1,1,1,0.748418,0.745253,1,1,1,1,1,1,1,0.996835,1,0.981132,0.5,1,1,1,0.748418,0.484277,1,0.748418,0.987421,1,0.746835,1,1,1,0.75,1,1,1,1,1,1,1,0.493671,1,0.996855,0.748418,1,1,1,1,1,1,1,1,1,0.745253,1,1,1,1,1,0.995253,1,1,1,1,0.75,0.981132,1,1,1,0.496835,1,1,1,1,1,1,1,1,0.490506,1,1,1,1,1,1,0.746835,0.996835,0.496855,1,1,1,0.996835,1,1,1,1]
area_under_roc_curve
0.920001 [0.496855,1,0.748418,1,0.490566,1,0.993711,1,0.745253,1,0.993671,0.727848,1,1,1,1,0.490566,0.75,1,0.75,1,1,1,1,0.496835,1,0.746835,0.496855,1,1,0.993711,1,0.496835,1,1,0.743671,1,0.996835,0.746835,1,1,0.493671,1,0.993711,1,1,0.981132,1,1,1,1,1,1,1,1,1,1,0.993671,1,0.75,1,1,1,1,1,0.996835,1,0.746835,1,0.993711,1,0.968553,1,1,1,1,1,1,0.748418,0.748418,1,0.993711,0.995253,1,0.746835,1,0.487421,1,1,1,1,1,1,1,1,1,0.996835,0.75,1,1]
area_under_roc_curve
0.926763 [0.490566,1,1,1,0.75,1,0.996835,1,0.993671,1,1,0.748418,1,1,0.75,0.75,0.987421,1,1,1,1,0.996835,1,1,1,1,1,0.487342,1,0.996855,0.743671,0.746835,0.993711,0.996855,1,0.743671,0.746835,1,1,0.75,1,0.993671,1,0.496855,0.993711,1,0.996855,0.5,0.746835,0.75,0.996835,1,1,0.746835,0.745253,0.987421,1,1,1,1,1,1,1,0.75,1,1,1,1,1,0.493711,1,1,1,1,0.5,1,1,1,1,1,1,0.996855,0.746835,1,1,1,1,1,1,1,1,0.993711,0.996855,1,1,0.75,1,1,1,1]
area_under_roc_curve
0.935568 [1,0.75,1,0.743631,0.745223,1,0.75,0.996835,1,1,1,0.984076,0.75,0.996835,0.996815,1,0.993671,1,1,0.75,0.996835,0.742038,1,1,0.745223,1,1,0.745223,1,1,1,1,1,1,1,0.745223,1,1,0.745223,1,1,0.748408,1,0.981013,0.993671,1,0.484177,1,0.748408,0.993631,0.996815,1,1,1,0.984177,1,0.75,1,1,0.75,1,1,0.996815,1,1,0.75,0.5,1,1,0.993671,1,1,1,1,1,1,0.996815,1,1,1,1,0.996815,1,0.75,1,1,1,1,1,1,1,1,1,0.75,1,1,1,1,1,0.996815]
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
0.764583 [1,1,0,1,0.5,0.5,0,1,1,1,0.666667,0.8,0.8,1,1,1,0.666667,1,1,1,0,0,0.8,0.666667,0,1,1,1,1,0,0.8,1,0.666667,1,1,1,0.666667,1,1,0,1,1,0.666667,0.5,1,1,0.666667,0.666667,0.666667,0.4,0.666667,1,1,0.666667,0.333333,1,1,0.666667,1,1,1,1,1,0.666667,0.666667,0.8,1,1,0.666667,1,1,0.5,1,1,1,1,0.666667,1,1,0.666667,0.666667,0.8,0,0.666667,0,1,0,1,1,0.8,0.666667,0.666667,1,0.666667,0.666667,0.5,1,1,1,0.666667]
f_measure
0.734643 [1,1,1,1,0.666667,0,1,0.666667,0,1,1,0.666667,1,1,1,1,0.666667,0.666667,1,0.5,1,0.5,0.571429,1,0,0,0,0.666667,1,1,1,1,1,0.5,0,0,1,0.666667,0.666667,1,1,1,0,1,0.5,1,0,1,1,0.8,0.666667,0.8,0.666667,0.4,1,0.8,1,0,1,1,1,0.666667,1,1,1,0.666667,1,0,1,0,0.666667,0.666667,1,0.666667,1,1,0.666667,0.8,1,0.666667,0.666667,0.8,0,0.666667,1,1,0.666667,0.5,1,1,0.666667,0.5,1,1,1,0.666667,0,1,0.8,1]
f_measure
0.776667 [0.8,1,0.8,1,0.666667,1,1,1,1,1,1,1,0.666667,0.666667,1,1,0.666667,0.666667,1,1,1,0,0.5,1,1,1,1,0,1,1,0.666667,1,0.666667,0.666667,1,0.5,0.666667,1,1,1,1,1,1,0.666667,0,1,0.5,0.666667,0.5,0,1,0.666667,0.8,0.8,0,1,1,0,1,1,1,0.666667,0,1,1,1,1,0,1,0,1,0.25,1,1,1,0.8,1,1,1,0.666667,1,0.666667,1,0.8,0,0.666667,0,1,1,1,1,0,1,1,1,1,1,1,1,0.666667]
f_measure
0.7575 [1,1,0.5,0.8,1,0,0,0.666667,1,0.8,1,0,1,0.666667,0,1,0.666667,0.8,0.666667,1,1,0.4,1,0,0,1,1,0,1,1,1,1,0.4,1,1,0,0.666667,1,0,1,1,1,0,0.333333,0.666667,0.666667,1,0.666667,0.666667,0.4,1,1,1,0.4,0.666667,0.8,1,0.666667,1,1,1,1,1,1,1,1,0.666667,1,1,0,1,0.5,1,0.666667,0.666667,0.666667,0.666667,1,1,1,1,0.666667,1,1,1,0.666667,0.8,0.4,1,1,1,1,0.666667,1,1,0.666667,0.5,1,0.666667,0.666667]
f_measure
0.717113 [0.5,1,0.4,1,0.666667,1,1,0,0,0,0.666667,0,0,1,0,1,0.666667,1,1,1,1,0,1,0,0.666667,0.4,0.8,1,1,1,1,1,0.666667,1,1,1,1,1,0,0,1,0.8,0.666667,0,0.285714,0,0.666667,0.8,0.666667,0.666667,0.4,1,1,0,0,0.666667,1,0.666667,1,1,1,1,1,0.8,0.5,1,1,1,1,0.5,1,1,0.666667,0.666667,0.666667,1,0.666667,1,0.8,0.8,0.5,1,0,1,1,0.8,0.4,1,1,1,0,0.666667,1,0,1,0.666667,1,1,0,0.8]
f_measure
0.802768 [0.666667,0.8,0.666667,1,0.666667,1,1,1,1,1,0.8,0,1,1,1,1,0.8,0.8,1,1,1,0,0.8,1,0,1,0.666667,0,1,1,0,1,0.8,1,0.666667,0.333333,1,1,1,1,1,0.666667,0.666667,1,0.666667,1,0.8,1,1,1,0.571429,1,0.666667,1,0.666667,0.666667,1,0.666667,1,1,1,1,0.666667,1,1,1,1,0.666667,0.666667,0.4,1,0.5,1,0.8,1,1,1,1,0.666667,1,0,0,0,1,0,0.8,1,1,0.8,0.666667,1,0.666667,0.666667,1,1,1,0.666667,1,1,1]
f_measure
0.77625 [0.666667,1,1,0,1,0.8,0.666667,1,0.666667,1,0.666667,0.5,1,1,1,1,1,1,1,0.8,1,0,0,1,1,0.8,0.666667,0,1,0.5,0,1,0.666667,1,1,0.8,0.666667,1,1,1,1,0,1,1,0,1,0.5,0.5,1,1,1,0.666667,1,0,0.666667,0.5,1,0.5,0.8,1,1,1,1,0.5,1,0.666667,1,1,0.666667,0,1,0.666667,1,0,1,1,1,1,1,0.666667,1,0,0,0.666667,1,1,1,0.8,0.666667,0.5,0.8,0,1,1,1,0.5,1,1,0.666667,1]
f_measure
0.769167 [0,1,0.5,1,0,1,0.5,1,0.5,0,0.666667,0,1,1,1,1,0,0.666667,1,0.666667,1,0,1,1,0,1,0.666667,0,1,1,0.666667,1,0,1,1,0.5,1,0.8,0.666667,1,1,0,0.666667,0.666667,1,1,0,1,1,1,0.8,0.666667,1,1,1,0.666667,1,0.4,1,0.666667,1,1,1,1,1,0.8,1,0.666667,1,0,0.5,0,1,0.8,1,1,1,1,0.5,0.666667,1,0.666667,0.5,1,0.5,1,0,1,1,1,1,1,0.8,1,1,1,0.8,0.666667,1,1]
f_measure
0.70375 [0,0.8,1,1,0,1,0.666667,0.666667,0,1,1,0,1,0.666667,0.666667,0.666667,0,1,1,1,1,0.8,0.666667,0.8,0.666667,0.666667,1,0,1,0.666667,0.5,0.5,0.666667,0.666667,1,0.666667,0.5,1,1,0.666667,1,0.666667,0,0,0,0.666667,0.5,0,0.4,0.666667,0.8,1,1,0.666667,0,0.4,1,0.666667,1,1,1,1,1,0,1,1,1,0.8,1,0,1,0.666667,1,1,0,0.8,0.8,1,0,1,1,0.5,0,1,1,1,1,1,1,0.8,1,0,0.666667,1,0.8,0.666667,1,0,1,0.666667]
f_measure
0.77065 [0.666667,0.666667,1,0.4,0.666667,1,0.666667,0.666667,1,0.8,1,0.333333,0.666667,0.666667,0.8,1,0,1,1,0.666667,0.666667,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,0.666667,1,0,0,1,0,0,0.666667,0,1,0.666667,0,0.8,1,1,0.8,0,0.666667,0.666667,0.8,1,0.666667,1,1,0.8,1,1,0.666667,0,1,1,0,1,1,1,1,1,0.8,0.666667,1,1,1,1,0.8,1,0.666667,1,0.666667,0.333333,1,1,0.666667,1,0,1,0.666667,1,1,1,1,1,0.8]
kappa
0.791576
kappa
0.759949
kappa
0.785176
kappa
0.766285
kappa
0.747215
kappa
0.816789
kappa
0.797836
kappa
0.778883
kappa
0.741008
kappa
0.790196
kb_relative_information_score
129.044176
kb_relative_information_score
122.006246
kb_relative_information_score
127.909551
kb_relative_information_score
125.109256
kb_relative_information_score
122.815898
kb_relative_information_score
132.129074
kb_relative_information_score
130.698855
kb_relative_information_score
126.209647
kb_relative_information_score
121.243253
kb_relative_information_score
128.136545
mean_absolute_error
0.004197
mean_absolute_error
0.004983
mean_absolute_error
0.004353
mean_absolute_error
0.004639
mean_absolute_error
0.004966
mean_absolute_error
0.003733
mean_absolute_error
0.003929
mean_absolute_error
0.004444
mean_absolute_error
0.005069
mean_absolute_error
0.004157
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
0.7825 [1,1,0,1,0.5,0.5,0,1,1,1,0.5,0.666667,0.666667,1,1,1,0.5,1,1,1,0,0,0.666667,1,0,1,1,1,1,0,0.666667,1,0.5,1,1,1,0.5,1,1,0,1,1,0.5,0.5,1,1,1,0.5,1,0.333333,0.5,1,1,1,0.2,1,1,0.5,1,1,1,1,1,0.5,1,0.666667,1,1,0.5,1,1,0.5,1,1,1,1,1,1,1,0.5,0.5,0.666667,0,1,0,1,0,1,1,0.666667,1,1,1,1,1,0.5,1,1,1,0.5]
precision
0.757083 [1,1,1,1,0.5,0,1,0.5,0,1,1,1,1,1,1,1,1,0.5,1,0.5,1,0.5,0.4,1,0,0,0,1,1,1,1,1,1,0.333333,0,0,1,0.5,1,1,1,1,0,1,0.333333,1,0,1,1,0.666667,0.5,0.666667,0.5,0.333333,1,0.666667,1,0,1,1,1,1,1,1,1,1,1,0,1,0,1,0.5,1,0.5,1,1,1,0.666667,1,0.5,0.5,0.666667,0,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,0,1,0.666667,1]
precision
0.807292 [0.666667,1,0.666667,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0.5,1,1,1,1,0,1,1,1,1,1,1,1,0.333333,0.5,1,1,1,1,1,1,1,0,1,0.5,1,0.5,0,1,1,0.666667,0.666667,0,1,1,0,1,1,1,0.5,0,1,1,1,1,0,1,0,1,0.166667,1,1,1,0.666667,1,1,1,1,1,1,1,0.666667,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,0.5]
precision
0.797917 [1,1,0.5,0.666667,1,0,0,1,1,0.666667,1,0,1,1,0,1,1,0.666667,1,1,1,0.333333,1,0,0,1,1,0,1,1,1,1,0.333333,1,1,0,0.5,1,0,1,1,1,0,0.25,1,1,1,1,0.5,0.25,1,1,1,0.333333,1,0.666667,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,0,1,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,0.666667,0.25,1,1,1,1,1,1,1,0.5,0.5,1,1,0.5]
precision
0.725417 [0.5,1,0.333333,1,0.5,1,1,0,0,0,0.5,0,0,1,0,1,1,1,1,1,1,0,1,0,0.5,0.333333,0.666667,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0.666667,1,0,0.2,0,1,0.666667,0.5,0.5,0.333333,1,1,0,0,1,1,1,1,1,1,1,1,0.666667,0.333333,1,1,1,1,0.5,1,1,1,0.5,1,1,0.5,1,0.666667,0.666667,0.5,1,0,1,1,0.666667,0.333333,1,1,1,0,1,1,0,1,0.5,1,1,0,0.666667]
precision
0.842708 [0.5,0.666667,1,1,0.5,1,1,1,1,1,0.666667,0,1,1,1,1,0.666667,0.666667,1,1,1,0,0.666667,1,0,1,1,0,1,1,0,1,0.666667,1,1,0.2,1,1,1,1,1,1,1,1,1,1,0.666667,1,1,1,0.4,1,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,0.333333,1,0.333333,1,0.666667,1,1,1,1,1,1,0,0,0,1,0,0.666667,1,1,0.666667,0.5,1,1,1,1,1,1,1,1,1,1]
precision
0.7875 [0.5,1,1,0,1,0.666667,0.5,1,1,1,1,0.5,1,1,1,1,1,1,1,0.666667,1,0,0,1,1,0.666667,1,0,1,0.5,0,1,1,1,1,0.666667,1,1,1,1,1,0,1,1,0,1,0.333333,0.5,1,1,1,0.5,1,0,1,0.333333,1,0.5,0.666667,1,1,1,1,0.5,1,0.5,1,1,1,0,1,0.5,1,0,1,1,1,1,1,1,1,0,0,0.5,1,1,1,0.666667,0.5,0.5,0.666667,0,1,1,1,0.5,1,1,0.5,1]
precision
0.792708 [0,1,0.5,1,0,1,0.333333,1,0.5,0,1,0,1,1,1,1,0,1,1,1,1,0,1,1,0,1,1,0,1,1,0.5,1,0,1,1,0.5,1,0.666667,1,1,1,0,1,0.5,1,1,0,1,1,1,0.666667,0.5,1,1,1,0.5,1,0.333333,1,1,1,1,1,1,1,0.666667,1,1,1,0,0.333333,0,1,0.666667,1,1,1,1,0.5,1,1,0.5,0.5,1,0.5,1,0,1,1,1,1,1,0.666667,1,1,1,0.666667,1,1,1]
precision
0.716146 [0,0.666667,1,1,0,1,0.5,0.5,0,1,1,0,1,0.5,1,1,0,1,1,1,1,0.666667,0.5,0.666667,0.5,0.5,1,0,1,0.5,0.5,0.5,0.5,0.5,1,1,0.5,1,1,1,1,1,0,0,0,0.5,0.333333,0,0.333333,1,0.666667,1,1,1,0,0.25,1,1,1,1,1,1,1,0,1,1,1,0.666667,1,0,1,1,1,1,0,0.666667,0.666667,1,0,1,1,0.333333,0,1,1,1,1,1,1,0.666667,1,0,0.5,1,0.666667,1,1,0,1,1]
precision
0.797904 [0.5,1,1,0.333333,1,1,1,0.5,1,0.666667,1,0.25,1,0.5,0.666667,1,0,1,1,1,0.5,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,1,1,0,0,1,0,0,0.5,0,1,1,0,0.666667,1,1,0.666667,0,0.5,1,0.666667,1,1,1,1,0.666667,1,1,1,0,1,1,0,1,1,1,1,1,0.666667,0.5,1,1,1,1,0.666667,1,1,1,0.5,0.2,1,1,1,1,0,1,1,1,1,1,1,1,0.666667]
predictive_accuracy
0.79375
predictive_accuracy
0.7625
predictive_accuracy
0.7875
predictive_accuracy
0.76875
predictive_accuracy
0.75
predictive_accuracy
0.81875
predictive_accuracy
0.8
predictive_accuracy
0.78125
predictive_accuracy
0.74375
predictive_accuracy
0.792453
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
0.79375 [1,1,0,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0,0.5,0,1,0,1,1,1,0.5,0.5,1,0.5,0.5,0.5,1,1,1,1]
recall
0.7625 [1,1,1,1,1,0,1,1,0,1,1,0.5,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0,0,0,0.5,1,1,1,1,1,1,0,0,1,1,0.5,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0.5,1,1,1,0.5,1,0,1,0,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,0.5,0,1,1,1]
recall
0.7875 [1,1,1,1,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,0,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0.5,0,1,0.5,0.5,0.5,0,1,0.5,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,0,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0,0.5,0,1,1,1,1,0,1,1,1,1,1,1,1,1]
recall
0.76875 [1,1,0.5,1,1,0,0,0.5,1,1,1,0,1,0.5,0,1,0.5,1,0.5,1,1,0.5,1,0,0,1,1,0,1,1,1,1,0.5,1,1,0,1,1,0,1,1,1,0,0.5,0.5,0.5,1,0.5,1,1,1,1,1,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,0.5,1,1,1,1,0.5,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,0.5,1]
recall
0.75 [0.5,1,0.5,1,1,1,1,0,0,0,1,0,0,1,0,1,0.5,1,1,1,1,0,1,0,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,0,0,1,1,0.5,0,0.5,0,0.5,1,1,1,0.5,1,1,0,0,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,1,1,0,1]
recall
0.81875 [1,1,0.5,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,1,0.5,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0.5,1,1,0.5,1,1,1,1,0.5,1,1,1,1,0.5,0.5,0.5,1,1,1,1,1,1,1,1,0.5,1,0,0,0,1,0,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1]
recall
0.8 [1,1,1,0,1,1,1,1,0.5,1,0.5,0.5,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0.5,0,1,0.5,0,1,0.5,1,1,1,0.5,1,1,1,1,0,1,1,0,1,1,0.5,1,1,1,1,1,0,0.5,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,0,1,1,1,0,1,1,1,1,1,0.5,1,0,0,1,1,1,1,1,1,0.5,1,0,1,1,1,0.5,1,1,1,1]
recall
0.78125 [0,1,0.5,1,0,1,1,1,0.5,0,0.5,0,1,1,1,1,0,0.5,1,0.5,1,0,1,1,0,1,0.5,0,1,1,1,1,0,1,1,0.5,1,1,0.5,1,1,0,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,0.5,1,1,1,1,1,1,1,0.5,1,0,1,0,1,1,1,1,1,1,0.5,0.5,1,1,0.5,1,0.5,1,0,1,1,1,1,1,1,1,1,1,1,0.5,1,1]
recall
0.74375 [0,1,1,1,0,1,1,1,0,1,1,0,1,1,0.5,0.5,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,1,1,1,0.5,0.5,1,1,0.5,1,0.5,0,0,0,1,1,0,0.5,0.5,1,1,1,0.5,0,1,1,0.5,1,1,1,1,1,0,1,1,1,1,1,0,1,0.5,1,1,0,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0.5,1,0,1,0.5]
recall
0.792453 [1,0.5,1,0.5,0.5,1,0.5,1,1,1,1,0.5,0.5,1,1,1,0,1,1,0.5,1,0.5,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0.5,1,1,0.5,1,0,0,1,0,0,1,0,1,0.5,0,1,1,1,1,0,1,0.5,1,1,0.5,1,1,1,1,1,0.5,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0,1,0.5,1,1,1,1,1,1]
relative_absolute_error
0.211986
relative_absolute_error
0.251661
relative_absolute_error
0.219869
relative_absolute_error
0.234297
relative_absolute_error
0.250814
relative_absolute_error
0.188559
relative_absolute_error
0.19844
relative_absolute_error
0.224445
relative_absolute_error
0.256012
relative_absolute_error
0.209971
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
0.063239
root_mean_squared_error
0.068927
root_mean_squared_error
0.063633
root_mean_squared_error
0.065972
root_mean_squared_error
0.068957
root_mean_squared_error
0.059004
root_mean_squared_error
0.061023
root_mean_squared_error
0.064627
root_mean_squared_error
0.069231
root_mean_squared_error
0.063008
root_relative_squared_error
0.635576
root_relative_squared_error
0.692738
root_relative_squared_error
0.639535
root_relative_squared_error
0.663042
root_relative_squared_error
0.693045
root_relative_squared_error
0.593018
root_relative_squared_error
0.613307
root_relative_squared_error
0.649529
root_relative_squared_error
0.695797
root_relative_squared_error
0.633253
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