521124
64
Rafael Gomes Mantovani
9956
Supervised Classification
2605
classif.sda(7)
3510
seed
1
2605
kind
Mersenne-Twister
2605
normal.kind
Inversion
2605
study_7
1493
one-hundred-plants-texture
https://www.openml.org/data/download/1592285/phpoOxxNn
-1
1791609
description
https://api.openml.org/data/download/1791609/file3c9b2133f4e0
-1
1791610
predictions
https://api.openml.org/data/download/1791610/file3c9b622f676b
area_under_roc_curve
0.884082 [0.864457,0.968118,0.875,0.875,0.746526,0.874684,0.811868,0.717171,0.905618,0.937184,0.936868,0.528407,0.968118,0.936552,0.843434,0.968434,0.778091,0.904987,0.905934,0.90625,0.999368,0.686868,0.874052,0.9375,0.684026,0.842171,0.778723,0.623737,0.905618,0.967171,0.749368,0.999368,0.810921,0.935605,0.812184,0.716539,0.935289,0.904671,0.904039,0.84375,0.999684,0.779987,0.713696,0.778407,0.780302,0.937184,0.779039,0.96875,0.90625,0.966855,0.904039,0.999052,0.904987,0.874684,0.903091,0.809657,0.999368,0.86963,0.936552,1,1,0.936552,0.843434,0.905302,0.905934,0.905618,0.999052,0.936868,0.9375,0.903091,0.936552,0.748421,0.999368,0.904039,0.9375,0.874684,0.905618,0.905618,0.905618,0.874368,0.937184,0.811237,0.714328,0.935605,0.966855,0.96875,0.780934,0.999052,0.9375,0.966539,0.9375,0.780618,0.936552,0.96875,0.936552,0.904671,0.904671,0.936868,0.90625,0.936552]
average_cost
0
f_measure
0.770374 [0.666667,0.909091,0.857143,0.857143,0.457143,0.827586,0.714286,0.5,0.83871,0.903226,0.875,0.076923,0.909091,0.848485,0.785714,0.9375,0.514286,0.787879,0.866667,0.896552,0.941176,0.5,0.774194,0.933333,0.363636,0.6875,0.545455,0.333333,0.83871,0.833333,0.615385,0.941176,0.645161,0.777778,0.740741,0.466667,0.756757,0.764706,0.722222,0.814815,0.969697,0.62069,0.358974,0.529412,0.642857,0.903226,0.5625,0.967742,0.896552,0.810811,0.722222,0.914286,0.787879,0.827586,0.666667,0.571429,0.941176,0.533333,0.848485,1,1,0.848485,0.785714,0.8125,0.866667,0.83871,0.914286,0.875,0.933333,0.666667,0.848485,0.551724,0.941176,0.722222,0.933333,0.827586,0.83871,0.83871,0.83871,0.8,0.903226,0.666667,0.378378,0.777778,0.810811,0.967742,0.692308,0.914286,0.933333,0.789474,0.933333,0.666667,0.848485,0.967742,0.848485,0.764706,0.764706,0.875,0.896552,0.848485]
kappa
0.768163
kb_relative_information_score
1231.191171
mean_absolute_error
0.00459
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
0.786074 [0.611111,0.882353,1,1,0.421053,0.923077,0.833333,0.583333,0.866667,0.933333,0.875,0.1,0.882353,0.823529,0.916667,0.9375,0.473684,0.764706,0.928571,1,0.888889,0.75,0.8,1,0.352941,0.6875,0.529412,0.5,0.866667,0.75,0.8,0.888889,0.666667,0.7,0.909091,0.5,0.666667,0.722222,0.65,1,0.941176,0.692308,0.304348,0.5,0.75,0.933333,0.5625,1,1,0.714286,0.65,0.842105,0.764706,0.923077,0.565217,0.526316,0.888889,0.413793,0.823529,1,1,0.823529,0.916667,0.8125,0.928571,0.866667,0.842105,0.875,1,0.565217,0.823529,0.615385,0.888889,0.65,1,0.923077,0.866667,0.866667,0.866667,0.857143,0.933333,0.714286,0.333333,0.7,0.714286,1,0.9,0.842105,1,0.681818,1,0.818182,0.823529,1,0.823529,0.722222,0.722222,0.875,1,0.823529]
predictive_accuracy
0.770482
prior_entropy
6.643831
recall
0.770482 [0.733333,0.9375,0.75,0.75,0.5,0.75,0.625,0.4375,0.8125,0.875,0.875,0.0625,0.9375,0.875,0.6875,0.9375,0.5625,0.8125,0.8125,0.8125,1,0.375,0.75,0.875,0.375,0.6875,0.5625,0.25,0.8125,0.9375,0.5,1,0.625,0.875,0.625,0.4375,0.875,0.8125,0.8125,0.6875,1,0.5625,0.4375,0.5625,0.5625,0.875,0.5625,0.9375,0.8125,0.9375,0.8125,1,0.8125,0.75,0.8125,0.625,1,0.75,0.875,1,1,0.875,0.6875,0.8125,0.8125,0.8125,1,0.875,0.875,0.8125,0.875,0.5,1,0.8125,0.875,0.75,0.8125,0.8125,0.8125,0.75,0.875,0.625,0.4375,0.875,0.9375,0.9375,0.5625,1,0.875,0.9375,0.875,0.5625,0.875,0.9375,0.875,0.8125,0.8125,0.875,0.8125,0.875]
relative_absolute_error
0.231837
root_mean_prior_squared_error
0.099499
root_mean_squared_error
0.067752
root_relative_squared_error
0.680936
total_cost
0
usercpu_time_millis
2.358
usercpu_time_millis_testing
0.0679999999999996
usercpu_time_millis_training
2.29
area_under_roc_curve
0.889658 [1,1,0.5,1,0.75,0.746835,0.5,0.5,1,1,0.996855,0.493671,0.996835,1,0.75,1,0.987342,0.996855,1,1,1,0.75,1,0.75,0.75,1,0.993711,0.5,1,0.5,0.746835,1,1,1,0.5,1,0.996855,1,0.746835,0.75,1,0.993711,0.493711,0.75,1,1,0.75,1,1,0.996835,0.996855,1,0.996855,1,0.993711,0.75,1,0.487421,1,1,1,1,1,1,0.75,1,1,1,1,1,0.75,1,0.996855,1,1,1,0.75,1,1,0.996855,0.996855,0.75,0.996835,0.75,1,1,0.5,1,1,0.996835,0.75,0.75,1,1,0.75,0.746835,0.996855,1,1,1]
area_under_roc_curve
0.877 [1,1,1,1,0.496835,0.5,1,0.996855,1,1,1,0.746835,1,1,0.75,1,0.746835,1,1,0.75,1,0.75,0.993671,1,0.743671,0.496835,0.493711,0.743671,0.75,0.996835,0.5,1,0.993711,0.993711,0.496855,0.746835,1,0.996855,1,0.75,1,0.5,0.496855,0.746835,1,1,0.746835,1,1,1,0.996855,1,0.996855,0.996835,0.993711,1,0.996855,0.990566,1,1,1,0.75,0.996855,0.496855,1,0.75,1,0.5,1,0.75,1,0.75,1,1,1,0.75,0.746835,1,1,1,1,0.996835,0.496855,1,1,1,0.5,0.996835,0.75,1,1,0.75,1,1,1,0.75,0.5,1,1,1]
area_under_roc_curve
0.880165 [1,1,1,1,0.990506,1,1,1,1,1,1,0.496855,1,0.75,0.996835,1,0.746835,0.75,1,1,1,0.746835,0.75,1,0.496855,0.75,1,0.75,1,1,0.75,1,0.5,0.75,0.75,0.493711,1,1,0.993711,0.5,1,1,0.996855,0.75,0.743671,0.75,0.496835,1,0.75,0.993711,0.996855,0.996835,0.75,1,0.996855,0.75,1,0.493711,1,1,1,1,0.5,0.996855,1,0.75,0.996835,1,1,0.746835,0.996835,0.75,1,1,1,0.75,1,1,1,0.75,1,0.5,0.490566,0.996835,0.990566,0.75,0.75,1,0.75,1,1,0.75,0.996835,1,0.996835,1,1,0.996835,1,0.996855]
area_under_roc_curve
0.861177 [0.75,1,0.75,1,0.996835,0.5,0.5,0.496835,0.996855,1,0.996835,0.5,1,0.75,0.75,1,0.75,0.993671,0.75,1,1,0.496835,1,1,0.490566,0.746835,0.996855,0.5,1,0.996835,1,0.996855,0.75,1,0.75,0.496855,0.990566,0.75,0.496855,1,1,0.496855,0.496855,0.990506,0.75,1,0.996835,1,0.5,0.993711,1,1,0.75,0.75,0.746835,0.743671,1,0.993711,1,1,1,0.5,1,0.5,1,0.996855,0.996835,1,1,0.990506,0.996835,0.496835,1,1,0.75,0.75,0.75,0.5,0.75,1,1,0.746835,0.5,1,1,1,1,0.996855,1,1,1,1,0.75,1,1,0.996855,0.996835,0.75,1,0.996855]
area_under_roc_curve
0.886295 [0.996835,0.996835,0.75,1,0.993711,1,1,0.5,1,0.5,1,0.5,0.5,1,1,1,0.5,1,1,0.5,1,0.5,1,0.5,0.5,0.746835,0.746835,0.996855,0.743671,1,1,1,0.996835,0.996835,1,1,1,1,0.996855,0.5,0.996835,0.996835,0.743671,0.746835,0.746835,0.75,0.75,1,1,0.996855,0.75,1,1,0.5,0.746835,0.75,1,1,1,1,1,1,1,0.996835,0.996855,1,1,1,1,0.987342,1,1,1,0.740506,1,1,0.996855,1,1,1,0.5,1,0.493711,1,0.996835,1,0.75,1,1,0.996855,0.5,0.75,1,0.5,1,0.996855,0.75,1,0.5,0.996835]
area_under_roc_curve
0.908546 [1,1,1,0.5,0.990566,1,1,0.75,1,1,1,0.5,1,1,1,0.996855,0.996835,1,0.75,1,1,0.5,0.746835,1,0.993711,1,0.5,0.5,1,1,0.496855,1,0.996835,1,0.75,0.996855,0.996835,1,1,1,1,0.75,0.75,0.996835,0.75,1,0.746835,0.75,1,1,0.993671,0.996855,1,1,0.746835,0.993671,1,0.75,0.75,1,1,1,0.5,1,1,1,1,1,1,1,1,0.993711,1,1,0.75,1,1,1,1,1,1,0.5,0.5,0.993711,0.75,1,1,0.996855,1,0.996855,1,0.746835,0.75,1,1,0.996855,0.75,0.996835,1,1]
area_under_roc_curve
0.892564 [0.993711,1,1,1,0.5,1,0.5,0.75,0.996835,1,0.75,0.496835,1,1,0.5,1,0.5,1,1,1,1,1,0.5,1,0.746835,0.996835,0.75,0.5,0.5,0.996835,0.5,1,0.746835,1,0.75,0.746835,0.746835,0.993671,0.996835,1,1,1,0.737342,0.996855,0.5,1,1,1,1,1,0.996835,1,0.746835,0.5,1,0.5,0.996835,0.993671,1,1,1,1,1,0.75,0.5,1,1,1,0.5,0.996855,1,0.996855,1,0.496835,1,0.996855,1,0.743671,1,1,1,1,0.5,1,1,1,1,1,1,0.993671,1,0.5,1,1,0.993711,1,0.996835,1,1,1]
area_under_roc_curve
0.854789 [0.493711,1,0.75,1,0.496855,1,0.493711,0.996835,0.5,0.5,0.75,0.493671,1,0.996855,1,1,0.493711,0.746835,0.496855,0.75,1,0.5,1,1,0.496835,1,0.743671,0.496855,1,0.996855,0.5,1,0.5,1,1,0.5,0.996835,0.5,0.75,1,1,0.5,0.493671,0.5,1,1,0.993711,1,1,1,0.75,1,0.996835,1,0.996835,0.493711,1,0.996835,0.746835,1,1,0.993671,1,1,1,0.996835,0.996855,0.746835,1,1,0.996855,0.5,1,1,1,0.5,1,0.75,0.746835,0.496835,1,1,0.987342,1,0.996835,1,0.496855,1,1,0.75,1,1,1,1,1,0.746835,0.993671,1,1,0.75]
area_under_roc_curve
0.880105 [0.493711,0.996835,1,0.5,0.75,1,1,0.493671,0.75,1,1,0.496835,0.996835,0.996855,0.75,0.75,1,1,1,1,0.996855,0.75,1,1,0.746835,1,1,0.5,1,0.996855,0.75,0.996835,1,0.996855,1,0.746835,0.75,0.996855,1,0.75,1,0.75,0.996835,0.496855,0.5,0.996855,0.996855,1,0.75,0.75,1,0.996855,1,0.75,0.996835,0.990566,1,0.996835,1,1,1,1,0.5,1,0.75,1,1,1,1,0.5,0.75,0.496835,0.996855,0.990506,1,1,1,1,0.5,1,1,0.493711,0.743671,0.993671,0.996835,1,1,1,1,1,1,1,0.996855,1,0.75,1,1,0.5,1,0.75]
area_under_roc_curve
0.91107 [0.5,0.75,1,0.75,0.5,1,1,1,1,0.996815,1,0.496815,1,0.996835,1,1,0.996835,0.5,1,1,0.996835,0.75,0.5,1,0.75,0.996835,0.75,0.75,1,1,1,1,1,0.493671,1,0.5,1,0.996835,0.996815,1,1,0.75,0.743631,0.496835,1,1,0.5,1,1,1,0.746815,1,1,1,1,1,1,0.743631,0.993631,1,1,0.996815,1,1,1,0.75,1,0.996815,1,0.996835,1,0.75,1,1,1,1,1,1,0.996835,0.5,1,1,0.996815,0.746815,1,1,1,1,1,0.993631,1,0.496835,0.996835,1,1,1,1,1,0.5,1]
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
0.772292 [1,1,0,1,0.666667,0.5,0,0,1,1,0.666667,0,0.8,1,0.666667,1,0.5,0.666667,1,1,1,0.666667,1,0.666667,0.666667,1,0.5,0,1,0,0.5,1,1,1,0,1,0.666667,1,0.5,0.666667,1,0.5,0,0.666667,1,1,0.666667,1,1,0.8,0.666667,1,0.666667,1,0.5,0.666667,1,0,1,1,1,1,1,1,0.666667,1,1,1,1,1,0.666667,1,0.666667,1,1,1,0.666667,1,1,0.666667,0.666667,0.666667,0.8,0.666667,1,1,0,1,1,0.8,0.666667,0.666667,1,1,0.666667,0.5,0.666667,1,1,1]
f_measure
0.741042 [1,1,1,1,0,0,1,0.666667,1,1,1,0.5,1,1,0.666667,1,0.5,1,1,0.666667,1,0.666667,0.666667,1,0.4,0,0,0.4,0.666667,0.8,0,1,0.5,0.5,0,0.5,1,0.666667,1,0.666667,1,0,0,0.5,1,1,0.5,1,1,1,0.666667,1,0.666667,0.8,0.5,1,0.666667,0.4,1,1,1,0.666667,0.666667,0,1,0.666667,1,0,1,0.666667,1,0.666667,1,1,1,0.666667,0.5,1,1,1,1,0.8,0,1,1,1,0,0.8,0.666667,1,1,0.666667,1,1,1,0.666667,0,1,1,1]
f_measure
0.759226 [1,1,1,1,0.571429,1,1,1,1,1,1,0,1,0.666667,0.8,1,0.5,0.666667,1,1,1,0.5,0.666667,1,0,0.666667,1,0.666667,1,1,0.666667,1,0,0.666667,0.666667,0,1,1,0.5,0,1,1,0.666667,0.666667,0.4,0.666667,0,1,0.666667,0.5,0.666667,0.8,0.666667,1,0.666667,0.666667,1,0,1,1,1,1,0,0.666667,1,0.666667,0.8,1,1,0.5,0.8,0.666667,1,1,1,0.666667,1,1,1,0.666667,1,0,0,0.8,0.4,0.666667,0.666667,1,0.666667,1,1,0.666667,0.8,1,0.8,1,1,0.8,1,0.666667]
f_measure
0.704286 [0.666667,1,0.666667,1,0.8,0,0,0,0.666667,1,0.8,0,1,0.666667,0.666667,1,0.666667,0.666667,0.666667,1,1,0,1,1,0,0.5,0.666667,0,1,0.8,1,0.666667,0.666667,1,0.666667,0,0.4,0.666667,0,1,1,0,0,0.571429,0.666667,1,0.8,1,0,0.5,1,1,0.666667,0.666667,0.5,0.4,1,0.5,1,1,1,0,1,0,1,0.666667,0.8,1,1,0.571429,0.8,0,1,1,0.666667,0.666667,0.666667,0,0.666667,1,1,0.5,0,1,1,1,1,0.666667,1,1,1,1,0.666667,1,1,0.666667,0.8,0.666667,1,0.666667]
f_measure
0.740625 [0.8,0.8,0.666667,1,0.5,1,1,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,1,0,0,0.5,0.5,0.666667,0.4,1,1,1,0.8,0.8,1,1,1,1,0.666667,0,0.8,0.8,0.4,0.5,0.5,0.666667,0.666667,1,1,0.666667,0.666667,1,1,0,0.5,0.666667,1,1,1,1,1,1,1,0.8,0.666667,1,1,1,1,0.5,1,1,1,0.333333,1,1,0.666667,1,1,1,0,1,0,1,0.8,1,0.666667,1,1,0.666667,0,0.666667,1,0,1,0.666667,0.666667,1,0,0.8]
f_measure
0.799375 [1,1,1,0,0.4,1,1,0.666667,1,1,1,0,1,1,1,0.666667,0.8,1,0.666667,1,1,0,0.5,1,0.5,1,0,0,1,1,0,1,0.8,1,0.666667,0.666667,0.8,1,1,1,1,0.666667,0.666667,0.8,0.666667,1,0.5,0.666667,1,1,0.666667,0.666667,1,1,0.5,0.666667,1,0.666667,0.666667,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,0.666667,1,1,1,1,1,1,0,0,0.5,0.666667,1,1,0.666667,1,0.666667,1,0.5,0.666667,1,1,0.666667,0.666667,0.8,1,1]
f_measure
0.749405 [0.5,1,1,1,0,1,0,0.666667,0.8,1,0.666667,0,1,1,0,1,0,1,1,1,1,1,0,1,0.5,0.8,0.666667,0,0,0.8,0,1,0.5,1,0.666667,0.5,0.5,0.666667,0.8,1,1,1,0.285714,0.666667,0,1,1,1,1,1,0.8,1,0.5,0,1,0,0.8,0.666667,1,1,1,1,1,0.666667,0,1,1,1,0,0.666667,1,0.666667,1,0,1,0.666667,1,0.4,1,1,1,1,0,1,1,1,1,1,1,0.666667,1,0,1,1,0.5,1,0.8,1,1,1]
f_measure
0.684375 [0,1,0.666667,1,0,1,0,0.8,0,0,0.666667,0,1,0.666667,1,1,0,0.5,0,0.666667,1,0,1,1,0,1,0.4,0,1,0.666667,0,1,0,1,1,0,0.8,0,0.666667,1,1,0,0,0,1,1,0.5,1,1,1,0.666667,1,0.8,1,0.8,0,1,0.8,0.5,1,1,0.666667,1,1,1,0.8,0.666667,0.5,1,1,0.666667,0,1,1,1,0,1,0.666667,0.5,0,1,1,0.5,1,0.8,1,0,1,1,0.666667,1,1,1,1,1,0.5,0.666667,1,1,0.666667]
f_measure
0.742976 [0,0.8,1,0,0.666667,1,1,0,0.666667,1,1,0,0.8,0.666667,0.666667,0.666667,1,1,1,1,0.666667,0.666667,1,1,0.5,1,1,0,1,0.666667,0.666667,0.8,1,0.666667,1,0.5,0.666667,0.666667,1,0.666667,1,0.666667,0.8,0,0,0.666667,0.666667,1,0.666667,0.666667,1,0.666667,1,0.666667,0.8,0.4,1,0.8,1,1,1,1,0,1,0.666667,1,1,1,1,0,0.666667,0,0.666667,0.571429,1,1,1,1,0,1,1,0,0.4,0.666667,0.8,1,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0,1,0.666667]
f_measure
0.802516 [0,0.666667,1,0.666667,0,1,1,1,1,0.8,1,0,1,0.666667,1,1,0.666667,0,1,1,0.666667,0.666667,0,1,0.666667,0.666667,0.666667,0.666667,1,1,1,1,1,0,1,0,1,0.666667,0.8,1,1,0.666667,0.4,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.4,0.666667,1,1,0.8,1,1,1,0.666667,1,0.8,1,0.666667,1,0.666667,1,1,1,1,1,1,0.666667,0,1,1,0.8,0.5,1,1,1,1,1,0.666667,1,0,0.666667,1,1,1,1,1,0,1]
kappa
0.778962
kappa
0.753681
kappa
0.760006
kappa
0.722058
kappa
0.772503
kappa
0.816818
kappa
0.785116
kappa
0.709367
kappa
0.759978
kappa
0.82197
kb_relative_information_score
124.934403
kb_relative_information_score
120.926164
kb_relative_information_score
121.928224
kb_relative_information_score
115.90283
kb_relative_information_score
123.932343
kb_relative_information_score
130.933597
kb_relative_information_score
125.923298
kb_relative_information_score
113.885546
kb_relative_information_score
121.902024
kb_relative_information_score
130.922745
mean_absolute_error
0.004375
mean_absolute_error
0.004875
mean_absolute_error
0.00475
mean_absolute_error
0.0055
mean_absolute_error
0.0045
mean_absolute_error
0.003625
mean_absolute_error
0.00425
mean_absolute_error
0.00575
mean_absolute_error
0.00475
mean_absolute_error
0.003522
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
0.821875 [1,1,0,1,1,0.5,0,0,1,1,0.5,0,0.666667,1,1,1,0.333333,0.5,1,1,1,1,1,1,1,1,0.333333,0,1,0,0.5,1,1,1,0,1,0.5,1,0.5,1,1,0.333333,0,1,1,1,1,1,1,0.666667,0.5,1,0.5,1,0.333333,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.666667,1,1,1,0,1,1,0.666667,1,1,1,1,1,0.5,0.5,1,1,1]
precision
0.774479 [1,1,1,1,0,0,1,0.5,1,1,1,0.5,1,1,1,1,0.5,1,1,1,1,1,0.5,1,0.333333,0,0,0.333333,1,0.666667,0,1,0.333333,0.333333,0,0.5,1,0.5,1,1,1,0,0,0.5,1,1,0.5,1,1,1,0.5,1,0.5,0.666667,0.333333,1,0.5,0.25,1,1,1,1,0.5,0,1,1,1,0,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.666667,0,1,1,1,0,0.666667,1,1,1,1,1,1,1,1,0,1,1,1]
precision
0.822187 [1,1,1,1,0.4,1,1,1,1,1,1,0,1,1,0.666667,1,0.5,1,1,1,1,0.5,1,1,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0.333333,0,1,1,0.5,1,0.333333,1,0,1,1,0.333333,0.5,0.666667,1,1,0.5,1,1,0,1,1,1,1,0,0.5,1,1,0.666667,1,1,0.5,0.666667,1,1,1,1,1,1,1,1,1,1,0,0,0.666667,0.25,1,1,1,1,1,1,1,0.666667,1,0.666667,1,1,0.666667,1,0.5]
precision
0.750104 [1,1,1,1,0.666667,0,0,0,0.5,1,0.666667,0,1,1,1,1,1,0.5,1,1,1,0,1,1,0,0.5,0.5,0,1,0.666667,1,0.5,1,1,1,0,0.25,1,0,1,1,0,0,0.4,1,1,0.666667,1,0,0.333333,1,1,1,1,0.5,0.333333,1,0.333333,1,1,1,0,1,0,1,0.5,0.666667,1,1,0.4,0.666667,0,1,1,1,1,1,0,1,1,1,0.5,0,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,0.666667,1,1,0.5]
precision
0.745833 [0.666667,0.666667,1,1,0.333333,1,1,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,1,0,0,0.5,0.5,0.5,0.333333,1,1,1,0.666667,0.666667,1,1,1,1,0.5,0,0.666667,0.666667,0.333333,0.5,0.5,1,1,1,1,0.5,1,1,1,0,0.5,1,1,1,1,1,1,1,1,0.666667,0.5,1,1,1,1,0.333333,1,1,1,0.25,1,1,0.5,1,1,1,0,1,0,1,0.666667,1,1,1,1,0.5,0,1,1,0,1,0.5,1,1,0,0.666667]
precision
0.830729 [1,1,1,0,0.25,1,1,1,1,1,1,0,1,1,1,0.5,0.666667,1,1,1,1,0,0.5,1,0.333333,1,0,0,1,1,0,1,0.666667,1,1,0.5,0.666667,1,1,1,1,1,1,0.666667,1,1,0.5,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0.333333,1,1,1,1,1,1,1,1,1,0,0,0.333333,1,1,1,0.5,1,0.5,1,0.5,1,1,1,0.5,1,0.666667,1,1]
precision
0.744167 [0.333333,1,1,1,0,1,0,1,0.666667,1,1,0,1,1,0,1,0,1,1,1,1,1,0,1,0.5,0.666667,1,0,0,0.666667,0,1,0.5,1,1,0.5,0.5,0.5,0.666667,1,1,1,0.2,0.5,0,1,1,1,1,1,0.666667,1,0.5,0,1,0,0.666667,0.5,1,1,1,1,1,1,0,1,1,1,0,0.5,1,0.5,1,0,1,0.5,1,0.333333,1,1,1,1,0,1,1,1,1,1,1,0.5,1,0,1,1,0.333333,1,0.666667,1,1,1]
precision
0.69375 [0,1,1,1,0,1,0,0.666667,0,0,1,0,1,0.5,1,1,0,0.5,0,1,1,0,1,1,0,1,0.333333,0,1,0.5,0,1,0,1,1,0,0.666667,0,1,1,1,0,0,0,1,1,0.333333,1,1,1,1,1,0.666667,1,0.666667,0,1,0.666667,0.5,1,1,0.5,1,1,1,0.666667,0.5,0.5,1,1,0.5,0,1,1,1,0,1,1,0.5,0,1,1,0.333333,1,0.666667,1,0,1,1,1,1,1,1,1,1,0.5,0.5,1,1,1]
precision
0.781562 [0,0.666667,1,0,1,1,1,0,1,1,1,0,0.666667,0.5,1,1,1,1,1,1,0.5,1,1,1,0.5,1,1,0,1,0.5,1,0.666667,1,0.5,1,0.5,1,0.5,1,1,1,1,0.666667,0,0,0.5,0.5,1,1,1,1,0.5,1,1,0.666667,0.25,1,0.666667,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0.5,0.4,1,1,1,1,0,1,1,0,0.333333,0.5,0.666667,1,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1]
precision
0.81761 [0,1,1,1,0,1,1,1,1,0.666667,1,0,1,0.5,1,1,0.5,0,1,1,0.5,1,0,1,1,0.5,1,1,1,1,1,1,1,0,1,0,1,0.5,0.666667,1,1,1,0.333333,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.333333,0.5,1,1,0.666667,1,1,1,1,1,0.666667,1,0.5,1,1,1,1,1,1,1,1,0.5,0,1,1,0.666667,0.5,1,1,1,1,1,0.5,1,0,0.5,1,1,1,1,1,0,1]
predictive_accuracy
0.78125
predictive_accuracy
0.75625
predictive_accuracy
0.7625
predictive_accuracy
0.725
predictive_accuracy
0.775
predictive_accuracy
0.81875
predictive_accuracy
0.7875
predictive_accuracy
0.7125
predictive_accuracy
0.7625
predictive_accuracy
0.823899
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
0.78125 [1,1,0,1,0.5,0.5,0,0,1,1,1,0,1,1,0.5,1,1,1,1,1,1,0.5,1,0.5,0.5,1,1,0,1,0,0.5,1,1,1,0,1,1,1,0.5,0.5,1,1,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,0.5,1,0.5,1,1,0,1,1,1,0.5,0.5,1,1,0.5,0.5,1,1,1,1]
recall
0.75625 [1,1,1,1,0,0,1,1,1,1,1,0.5,1,1,0.5,1,0.5,1,1,0.5,1,0.5,1,1,0.5,0,0,0.5,0.5,1,0,1,1,1,0,0.5,1,1,1,0.5,1,0,0,0.5,1,1,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,0,1,0.5,1,0,1,0.5,1,0.5,1,1,1,0.5,0.5,1,1,1,1,1,0,1,1,1,0,1,0.5,1,1,0.5,1,1,1,0.5,0,1,1,1]
recall
0.7625 [1,1,1,1,1,1,1,1,1,1,1,0,1,0.5,1,1,0.5,0.5,1,1,1,0.5,0.5,1,0,0.5,1,0.5,1,1,0.5,1,0,0.5,0.5,0,1,1,1,0,1,1,1,0.5,0.5,0.5,0,1,0.5,1,1,1,0.5,1,1,0.5,1,0,1,1,1,1,0,1,1,0.5,1,1,1,0.5,1,0.5,1,1,1,0.5,1,1,1,0.5,1,0,0,1,1,0.5,0.5,1,0.5,1,1,0.5,1,1,1,1,1,1,1,1]
recall
0.725 [0.5,1,0.5,1,1,0,0,0,1,1,1,0,1,0.5,0.5,1,0.5,1,0.5,1,1,0,1,1,0,0.5,1,0,1,1,1,1,0.5,1,0.5,0,1,0.5,0,1,1,0,0,1,0.5,1,1,1,0,1,1,1,0.5,0.5,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0.5,0,0.5,1,1,0.5,0,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,0.5,1,1]
recall
0.775 [1,1,0.5,1,1,1,1,0,1,0,1,0,0,1,1,1,0,1,1,0,1,0,1,0,0,0.5,0.5,1,0.5,1,1,1,1,1,1,1,1,1,1,0,1,1,0.5,0.5,0.5,0.5,0.5,1,1,1,0.5,1,1,0,0.5,0.5,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,1,0,1,1,1,0.5,1,1,1,0,0.5,1,0,1,1,0.5,1,0,1]
recall
0.81875 [1,1,1,0,1,1,1,0.5,1,1,1,0,1,1,1,1,1,1,0.5,1,1,0,0.5,1,1,1,0,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,0.5,1,0.5,1,0.5,0.5,1,1,1,1,1,1,0.5,1,1,0.5,0.5,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,1,1,1,1,0,0,1,0.5,1,1,1,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1]
recall
0.7875 [1,1,1,1,0,1,0,0.5,1,1,0.5,0,1,1,0,1,0,1,1,1,1,1,0,1,0.5,1,0.5,0,0,1,0,1,0.5,1,0.5,0.5,0.5,1,1,1,1,1,0.5,1,0,1,1,1,1,1,1,1,0.5,0,1,0,1,1,1,1,1,1,1,0.5,0,1,1,1,0,1,1,1,1,0,1,1,1,0.5,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1]
recall
0.7125 [0,1,0.5,1,0,1,0,1,0,0,0.5,0,1,1,1,1,0,0.5,0,0.5,1,0,1,1,0,1,0.5,0,1,1,0,1,0,1,1,0,1,0,0.5,1,1,0,0,0,1,1,1,1,1,1,0.5,1,1,1,1,0,1,1,0.5,1,1,1,1,1,1,1,1,0.5,1,1,1,0,1,1,1,0,1,0.5,0.5,0,1,1,1,1,1,1,0,1,1,0.5,1,1,1,1,1,0.5,1,1,1,0.5]
recall
0.7625 [0,1,1,0,0.5,1,1,0,0.5,1,1,0,1,1,0.5,0.5,1,1,1,1,1,0.5,1,1,0.5,1,1,0,1,1,0.5,1,1,1,1,0.5,0.5,1,1,0.5,1,0.5,1,0,0,1,1,1,0.5,0.5,1,1,1,0.5,1,1,1,1,1,1,1,1,0,1,0.5,1,1,1,1,0,0.5,0,1,1,1,1,1,1,0,1,1,0,0.5,1,1,1,1,1,1,1,1,1,1,1,0.5,1,1,0,1,0.5]
recall
0.823899 [0,0.5,1,0.5,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,0.5,0,1,0.5,1,0.5,0.5,1,1,1,1,1,0,1,0,1,1,1,1,1,0.5,0.5,0,1,1,0,1,1,1,0.5,1,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0.5,1,1,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,0.5,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1]
relative_absolute_error
0.220959
relative_absolute_error
0.246212
relative_absolute_error
0.239899
relative_absolute_error
0.277777
relative_absolute_error
0.227272
relative_absolute_error
0.183081
relative_absolute_error
0.214647
relative_absolute_error
0.290405
relative_absolute_error
0.2399
relative_absolute_error
0.17788
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
0.066144
root_mean_squared_error
0.069821
root_mean_squared_error
0.06892
root_mean_squared_error
0.074162
root_mean_squared_error
0.067082
root_mean_squared_error
0.060208
root_mean_squared_error
0.065192
root_mean_squared_error
0.075829
root_mean_squared_error
0.06892
root_mean_squared_error
0.059347
root_relative_squared_error
0.664769
root_relative_squared_error
0.701728
root_relative_squared_error
0.692673
root_relative_squared_error
0.745355
root_relative_squared_error
0.674199
root_relative_squared_error
0.605114
root_relative_squared_error
0.655206
root_relative_squared_error
0.762109
root_relative_squared_error
0.692676
root_relative_squared_error
0.596456
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