2040441
2742
Wouter Nuijten
145682
Supervised Classification
area_under_roc_curve
6138
weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_RandomForest(1)
181164
weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.unsupervised.attribute.InterquartileRange -R first-last -O 3.0 -E 6.0" -W weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.unsupervised.instance.RemoveWithValues -S 0.0 -C 103 -L 2" -W weka.classifiers.meta.FilteredClassifier -- -F "weka.filters.unsupervised.attribute.PrincipalComponents -R 0.95 -A 5 -M 16" -W weka.classifiers.trees.RandomForest -- -P 100 -I 1000 -num-slots 1 -K 0 -M 1.0 -V 0.001 -S 1
P
100
5923
I
1000
5923
num-slots
1
5923
K
0
5923
M
1.0
5923
V
0.001
5923
S
1
5923
F
weka.filters.unsupervised.attribute.PrincipalComponents -R 0.95 -A 5 -M 16
6105
W
weka.classifiers.trees.RandomForest
6105
F
weka.filters.unsupervised.instance.RemoveWithValues -S 0.0 -C 103 -L 2
6124
W
weka.classifiers.meta.FilteredClassifier
6124
F
weka.filters.unsupervised.attribute.InterquartileRange -R first-last -O 3.0 -E 6.0
6138
W
weka.classifiers.meta.FilteredClassifier
6138
weka
weka_3.8.1
313
spectrometer
https://www.openml.org/data/download/52217/phpHNcI2h
-1
5030723
description
https://api.openml.org/data/download/5030723/weka_generated_run1311763837423111172.xml
-1
5030725
model_readable
https://api.openml.org/data/download/5030725/WekaModel_weka.classifiers.meta.FilteredClassifier8120594205037962183.model
-1
5030724
model_serialized
https://api.openml.org/data/download/5030724/WekaSerialized_weka.classifiers.meta.FilteredClassifier2477571906180797239.model
-1
5030726
predictions
https://api.openml.org/data/download/5030726/weka_generated_predictions7595643672470181242.arff
area_under_roc_curve
0.929481 [0.761364,0.357547,0.704198,0.437736,0.797732,0.94476,0.978503,0.987385,0.980175,0.986031,0.996649,0.851034,0.918614,0.927065,0.955027,0.913292,0.934098,0.913479,0.914135,0.97987,0.951149,0.969674,0.958966,0.995731,0.941604,0.430189,0.39717,0.995581,0.996843,0.852892,0.95471,0.928131,0.980886,0.989734,0.431132,0.971172,0.39434,0.395283,0.430189,0.987058,0.982323,0.88327,0.454717,0.424528,0.997475,0.400943,0.446226,0.415094]
average_cost
0
f_measure
0.434971 [0,0,0,0,0,0,0.352941,0.727273,0.608696,0.592593,0.792453,0.333333,0.474576,0.346667,0.363636,0.153846,0.507463,0.266667,0.438095,0.680412,0.315789,0.5,0,0.333333,0,0,0,0.75,0.4,0,0.594595,0.25641,0.4375,0,0,0,0,0,0,0,0.4,0,0,0,0.666667,0,0,0]
kappa
0.426853
kb_relative_information_score
255.959077
mean_absolute_error
0.029559
mean_prior_absolute_error
0.039641
number_of_instances
531 [3,1,7,1,2,3,10,24,13,12,26,15,27,31,19,19,30,35,42,55,9,10,4,4,3,1,1,3,3,8,45,20,18,5,1,2,1,1,1,3,3,2,1,1,3,1,1,1]
precision
0.432828 [0,0,0,0,0,0,0.428571,0.645161,0.7,0.533333,0.777778,0.285714,0.4375,0.295455,0.428571,0.285714,0.459459,0.25,0.365079,0.785714,0.3,0.666667,0,0.5,0,0,0,0.6,0.5,0,0.5,0.263158,0.5,0,0,0,0,0,0,0,0.5,0,0,0,0.5,0,0,0]
predictive_accuracy
0.45951
prior_entropy
4.846691
recall
0.45951 [0,0,0,0,0,0,0.3,0.833333,0.538462,0.666667,0.807692,0.4,0.518519,0.419355,0.315789,0.105263,0.566667,0.285714,0.547619,0.6,0.333333,0.4,0,0.25,0,0,0,1,0.333333,0,0.733333,0.25,0.388889,0,0,0,0,0,0,0,0.333333,0,0,0,1,0,0,0]
relative_absolute_error
0.74565
root_mean_prior_squared_error
0.140616
root_mean_squared_error
0.118121
root_relative_squared_error
0.84003
total_cost
0
area_under_roc_curve
0.93415 [0.0,0.0,1,0.0,0.0,1,0.981132,1,0.981132,0.981132,1,0.961538,0.96732,0.934641,0.961538,0.971154,0.928105,0.94,0.93,0.979592,0.943396,1,0.0,1,0.0,0.0,0.0,0.0,0.0,0.632075,0.963265,1,0.985577,0.0,0.5,0.0,0.0,0.0,0.5,0.981132,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.5]
area_under_roc_curve
0.915711 [0.0,0.0,0.586538,0.5,0.865385,0.961538,1,1,0.980769,0.980769,0.993333,0.921569,0.973333,0.946667,0.960784,0.823529,0.9,0.94898,0.918367,0.970833,0.884615,1,0.0,0.980769,0.0,0.5,0.0,0.0,0.0,0.923077,0.923469,0.75,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
area_under_roc_curve
0.925958 [0.0,0.0,0.230769,0.0,0.884615,0.0,0.980769,1,1,0.980769,0.986667,0.485294,0.75,0.993333,1,0.897059,0.933333,0.98,0.959184,0.968085,0.923077,0.980769,0.0,1,0.0,0.0,0.0,1,0.0,0.971154,0.994898,0.95098,0.960784,0.980769,0.0,0.0,0.0,0.0,0.0,0.0,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
area_under_roc_curve
0.967801 [0.0,0.0,1,0.0,0.0,0.0,1,1,1,0.980769,0.993333,0.960784,0.966667,0.94,0.941176,0.882353,0.966667,0.926667,0.918367,0.994681,1,0.942308,0.961538,1,0.0,0.0,0.0,1,0.0,1,0.964286,1,0.980769,1,0.0,0.0,0.0,0.0,0.0,0.0,0.980769,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
area_under_roc_curve
0.9311 [0.0,0.5,0.451923,0.0,0.0,0.0,0.980769,0.993333,0.990196,1,1,0.573529,1,0.986667,0.911765,0.903846,0.926667,0.92,0.938776,0.992908,1,0.923077,0.980769,0.0,0.0,0.0,0.0,1,0.0,0.846154,0.938776,0.941176,0.980769,1,0.0,0.0,0.0,0.0,0.0,0.0,1,0.0,0.0,0.0,1,0.0,0.0,0.0]
area_under_roc_curve
0.951649 [0.0,0.0,0.980769,0.0,0.0,0.0,0.961538,0.973333,0.980392,0.942308,1,0.961538,0.882353,0.94,0.960784,0.980392,0.96,0.866667,0.933673,0.992908,0.951923,1,0.980769,0.0,0.0,0.0,0.0,0.0,1,0.817308,0.918367,0.872549,0.970588,0.961538,0.0,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1,0.0,0.0,0.0]
area_under_roc_curve
0.959205 [0.0,0.0,1,0.0,0.0,0.0,1,0.993333,0.916667,1,1,1,0.95098,0.953333,1,0.941176,0.953333,0.886667,0.872449,0.980496,0.0,0.942308,1,0.0,0.0,0.0,0.0,0.0,1,0.0,0.979167,0.901961,0.980392,0.980769,0.0,0.961538,0.0,0.0,0.0,0.0,0.0,0.942308,0.0,0.0,1,0.0,0.0,0.0]
area_under_roc_curve
0.916554 [0.923077,0.0,0.0,0.0,0.0,0.0,0.932692,0.990196,1,1,1,1,0.893333,0.918367,0.941176,0.921569,0.886667,0.806122,0.860417,0.995833,1,0.942308,0.0,0.0,0.961538,0.0,0.0,0.0,1,0.0,0.945833,0.980392,0.970588,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.961538,0.5,0.0,0.0,0.0,0.5,0.0]
area_under_roc_curve
0.920636 [0.817308,0.0,0.0,0.0,0.0,0.0,1,0.970588,1,1,1,0.961538,0.94,0.776667,1,0.892157,0.926667,0.961735,0.941667,0.958333,0.980769,1,0.0,0.0,1,0.0,0.0,0.0,0.0,0.884615,0.933333,0.990196,1,0.0,0.0,0.0,0.5,0.0,0.0,1,0.0,0.0,0.0,0.5,0.0,0.5,0.0,0.0]
area_under_roc_curve
0.940985 [0.798077,0.0,0.0,0.0,0.0,0.980769,0.942308,0.955882,1,1,1,0.942308,0.953333,0.913333,1,0.960784,0.933333,0.969388,0.928571,0.970833,0.980769,0.980769,0.0,0.0,0.961538,0.0,0.5,0.0,0.0,0.826923,0.983333,0.941176,0.990196,0.0,0.0,0.0,0.0,0.5,0.0,1,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
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
average_cost
0
f_measure
0.278643 [0,0,0,0,0,0,0.666667,0.666667,0,0,0.666667,0,0.4,0.25,0,0,0.444444,0.25,0.4,0.444444,0,0.666667,0,0,0,0,0,0,0,0,0.588235,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
f_measure
0.331207 [0,0,0,0,0,0,0,0.571429,0,0.5,0.5,0.4,0.5,0.4,0,0,0.4,0,0.4,0.666667,0,1,0,0,0,0,0,0,0,0,0.444444,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
f_measure
0.478192 [0,0,0,0,0,0,0,0.8,0.666667,0,0.857143,0,0.5,0.545455,0.666667,0,0.333333,0.545455,0.5,0.6,0,0,0,1,0,0,0,1,0,0,1,0.5,0.4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
f_measure
0.466038 [0,0,0,0,0,0,0,1,1,0,0.666667,0.5,0.4,0.444444,0,0,0.666667,0.4,0.5,0.8,0.5,0,0,0,0,0,0,1,0,0,0.666667,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
f_measure
0.517063 [0,0,0,0,0,0,0,0.857143,0.5,1,1,0,0.571429,0.5,0.5,0,0.571429,0,0.6,0.909091,0.5,0,0,0,0,0,0,1,0,0,0.363636,0.5,0.666667,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0]
f_measure
0.375502 [0,0,0,0,0,0,0,0.571429,0,0,0.857143,0,0.333333,0.285714,0,0,0.571429,0,0.5,0.8,0,1,0,0,0,0,0,0,1,0,0.444444,0,0.4,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
f_measure
0.461766 [0,0,0,0,0,0,1,0.857143,0.666667,0.666667,0.8,1,0.571429,0.285714,0,0.666667,0.571429,0,0.363636,0.666667,0,0,0,0,0,0,0,0,0,0,0.6,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
f_measure
0.350739 [0,0,0,0,0,0,0,0.666667,1,0.666667,0.8,0.666667,0.5,0.285714,0.5,0,0.285714,0.181818,0.285714,0.8,0,0,0,0,0,0,0,0,0,0,0.533333,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
f_measure
0.437788 [0,0,0,0,0,0,0.666667,0.666667,1,1,0.666667,0.666667,0.285714,0,0.666667,0,0.571429,0.545455,0.444444,0.5,0,1,0,0,0,0,0,0,0,0,0.545455,0.5,0.666667,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
f_measure
0.472727 [0,0,0,0,0,0,0,0.5,1,0.8,1,0.333333,0.666667,0.4,1,0.5,0.666667,0.25,0.363636,0.5,1,0,0,0,0,0,0,0,0,0,0.833333,0.4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
kappa
0.309463
kappa
0.340746
kappa
0.500377
kappa
0.460407
kappa
0.540693
kappa
0.379766
kappa
0.45857
kappa
0.357089
kappa
0.440422
kappa
0.480784
kb_relative_information_score
25.216264
kb_relative_information_score
21.992777
kb_relative_information_score
26.757101
kb_relative_information_score
28.757219
kb_relative_information_score
26.278952
kb_relative_information_score
27.064048
kb_relative_information_score
27.488169
kb_relative_information_score
22.023627
kb_relative_information_score
24.279986
kb_relative_information_score
26.100934
mean_absolute_error
0.030301
mean_absolute_error
0.03087
mean_absolute_error
0.028533
mean_absolute_error
0.02864
mean_absolute_error
0.029208
mean_absolute_error
0.029671
mean_absolute_error
0.028289
mean_absolute_error
0.030904
mean_absolute_error
0.029803
mean_absolute_error
0.029351
mean_prior_absolute_error
0.039681
mean_prior_absolute_error
0.039673
mean_prior_absolute_error
0.039638
mean_prior_absolute_error
0.039627
mean_prior_absolute_error
0.039672
mean_prior_absolute_error
0.039645
mean_prior_absolute_error
0.039604
mean_prior_absolute_error
0.039587
mean_prior_absolute_error
0.039629
mean_prior_absolute_error
0.039657
number_of_instances
54 [0,0,1,0,0,1,1,2,1,1,2,2,3,3,2,2,3,4,4,5,1,1,0,1,0,0,0,0,0,1,5,2,2,0,1,0,0,0,1,1,0,0,0,0,0,0,0,1]
number_of_instances
53 [0,0,1,1,1,1,1,2,1,1,3,2,3,3,2,2,3,4,4,5,1,1,0,1,0,1,0,0,0,1,4,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
number_of_instances
53 [0,0,1,0,1,0,1,2,1,1,3,2,3,3,2,2,3,3,4,6,1,1,0,1,0,0,0,1,0,1,4,2,2,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0]
number_of_instances
53 [0,0,1,0,0,0,1,3,1,1,3,2,3,3,2,2,3,3,4,6,1,1,1,1,0,0,0,1,0,1,4,2,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0]
number_of_instances
53 [0,1,1,0,0,0,1,3,2,1,3,2,2,3,2,1,3,3,4,6,1,1,1,0,0,0,0,1,0,1,4,2,1,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0]
number_of_instances
53 [0,0,1,0,0,0,1,3,2,1,3,1,2,3,2,2,3,3,4,6,1,1,1,0,0,0,0,0,1,1,4,2,2,1,0,1,0,0,0,0,0,0,0,0,1,0,0,0]
number_of_instances
53 [0,0,1,0,0,0,1,3,2,1,3,1,2,3,2,2,3,3,4,6,0,1,1,0,0,0,0,0,1,0,5,2,2,1,0,1,0,0,0,0,0,1,0,0,1,0,0,0]
number_of_instances
53 [1,0,0,0,0,0,1,2,1,1,2,1,3,4,2,2,3,4,5,5,1,1,0,0,1,0,0,0,1,0,5,2,2,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0]
number_of_instances
53 [1,0,0,0,0,0,1,2,1,2,2,1,3,3,1,2,3,4,5,5,1,1,0,0,1,0,0,0,0,1,5,2,2,0,0,0,1,0,0,1,0,0,0,1,0,1,0,0]
number_of_instances
53 [1,0,0,0,0,1,1,2,1,2,2,1,3,3,2,2,3,4,4,5,1,1,0,0,1,0,1,0,0,1,5,2,2,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0]
precision
0.259568 [0,0,0,0,0,0,0.5,0.5,0,0,1,0,0.5,0.2,0,0,0.333333,0.25,0.333333,0.5,0,0.5,0,0,0,0,0,0,0,0,0.416667,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
precision
0.369775 [0,0,0,0,0,0,0,0.4,0,0.333333,1,0.333333,1,0.285714,0,0,0.5,0,0.272727,0.75,0,1,0,0,0,0,0,0,0,0,0.4,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
precision
0.5 [0,0,0,0,0,0,0,0.666667,0.5,0,0.75,0,1,0.375,1,0,0.333333,0.375,0.5,0.75,0,0,0,1,0,0,0,1,0,0,1,0.5,0.333333,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
precision
0.476101 [0,0,0,0,0,0,0,1,1,0,0.666667,0.5,0.5,0.333333,0,0,0.666667,0.5,0.375,1,0.333333,0,0,0,0,0,0,1,0,0,0.6,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
precision
0.519362 [0,0,0,0,0,0,0,0.75,0.5,1,1,0,0.4,1,0.5,0,0.5,0,0.5,1,0.333333,0,0,0,0,0,0,1,0,0,0.285714,0.5,0.5,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0]
precision
0.363522 [0,0,0,0,0,0,0,0.5,0,0,0.75,0,0.25,0.25,0,0,0.5,0,0.375,1,0,1,0,0,0,0,0,0,1,0,0.4,0,0.333333,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
precision
0.47062 [0,0,0,0,0,0,1,0.75,1,0.5,1,1,0.4,0.25,0,1,0.5,0,0.285714,0.666667,0,0,0,0,0,0,0,0,0,0,0.6,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
precision
0.352606 [0,0,0,0,0,0,0,1,1,0.5,0.666667,0.5,0.4,0.333333,0.5,0,0.25,0.142857,0.5,0.8,0,0,0,0,0,0,0,0,0,0,0.4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
precision
0.449012 [0,0,0,0,0,0,0.5,1,1,1,0.5,0.5,0.25,0,0.5,0,0.5,0.428571,0.5,0.666667,0,1,0,0,0,0,0,0,0,0,0.5,0.5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
precision
0.466936 [0,0,0,0,0,0,0,0.5,1,0.666667,1,0.2,0.666667,0.5,1,0.5,0.666667,0.25,0.285714,0.666667,1,0,0,0,0,0,0,0,0,0,0.714286,0.333333,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
predictive_accuracy
0.351852
predictive_accuracy
0.377358
predictive_accuracy
0.528302
predictive_accuracy
0.490566
predictive_accuracy
0.566038
predictive_accuracy
0.415094
predictive_accuracy
0.490566
predictive_accuracy
0.396226
predictive_accuracy
0.471698
predictive_accuracy
0.509434
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
prior_entropy
4.846691
recall
0.351852 [0,0,0,0,0,0,1,1,0,0,0.5,0,0.333333,0.333333,0,0,0.666667,0.25,0.5,0.4,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.377358 [0,0,0,0,0,0,0,1,0,1,0.333333,0.5,0.333333,0.666667,0,0,0.333333,0,0.75,0.6,0,1,0,0,0,0,0,0,0,0,0.5,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.528302 [0,0,0,0,0,0,0,1,1,0,1,0,0.333333,1,0.5,0,0.333333,1,0.5,0.5,0,0,0,1,0,0,0,1,0,0,1,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.490566 [0,0,0,0,0,0,0,1,1,0,0.666667,0.5,0.333333,0.666667,0,0,0.666667,0.333333,0.75,0.666667,1,0,0,0,0,0,0,1,0,0,0.75,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.566038 [0,0,0,0,0,0,0,1,0.5,1,1,0,1,0.333333,0.5,0,0.666667,0,0.75,0.833333,1,0,0,0,0,0,0,1,0,0,0.5,0.5,1,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0]
recall
0.415094 [0,0,0,0,0,0,0,0.666667,0,0,1,0,0.5,0.333333,0,0,0.666667,0,0.75,0.666667,0,1,0,0,0,0,0,0,1,0,0.5,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
recall
0.490566 [0,0,0,0,0,0,1,1,0.5,1,0.666667,1,1,0.333333,0,0.5,0.666667,0,0.5,0.666667,0,0,0,0,0,0,0,0,0,0,0.6,0,0.5,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0]
recall
0.396226 [0,0,0,0,0,0,0,0.5,1,1,1,1,0.666667,0.25,0.5,0,0.333333,0.25,0.2,0.8,0,0,0,0,0,0,0,0,0,0,0.8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.471698 [0,0,0,0,0,0,1,0.5,1,1,1,1,0.333333,0,1,0,0.666667,0.75,0.4,0.4,0,1,0,0,0,0,0,0,0,0,0.6,0.5,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
recall
0.509434 [0,0,0,0,0,0,0,0.5,1,1,1,1,0.666667,0.333333,1,0.5,0.666667,0.25,0.5,0.4,1,0,0,0,0,0,0,0,0,0,1,0.5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
relative_absolute_error
0.763613
relative_absolute_error
0.77811
relative_absolute_error
0.719838
relative_absolute_error
0.722733
relative_absolute_error
0.736244
relative_absolute_error
0.748429
relative_absolute_error
0.714301
relative_absolute_error
0.780672
relative_absolute_error
0.752069
relative_absolute_error
0.74013
root_mean_prior_squared_error
0.140756
root_mean_prior_squared_error
0.140729
root_mean_prior_squared_error
0.140604
root_mean_prior_squared_error
0.140565
root_mean_prior_squared_error
0.140725
root_mean_prior_squared_error
0.140628
root_mean_prior_squared_error
0.140483
root_mean_prior_squared_error
0.14042
root_mean_prior_squared_error
0.14057
root_mean_prior_squared_error
0.140671
root_mean_squared_error
0.120259
root_mean_squared_error
0.122621
root_mean_squared_error
0.116229
root_mean_squared_error
0.113844
root_mean_squared_error
0.116879
root_mean_squared_error
0.119218
root_mean_squared_error
0.114686
root_mean_squared_error
0.121974
root_mean_squared_error
0.117595
root_mean_squared_error
0.117542
root_relative_squared_error
0.854378
root_relative_squared_error
0.871322
root_relative_squared_error
0.826644
root_relative_squared_error
0.809905
root_relative_squared_error
0.83055
root_relative_squared_error
0.847755
root_relative_squared_error
0.816367
root_relative_squared_error
0.868637
root_relative_squared_error
0.83656
root_relative_squared_error
0.835575
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