## Generated by BioDiscML (Leclercq et al. 2018)##
# Project: colon
# ID: trees.HoeffdingTree_AUC_FB_10_0.9516_99
# Classifier: trees.HoeffdingTree  -L 2 -S 1 -E 1.0E-7 -H 0.05 -M 0.01 -G 200.0 -N 0.0
# Optimizer: AUC
# Feature search mode: FB

# 10 fold cross validation performance
ACC: 0.9516
AUC: 0.9977
AUPRC: 0.9979
TPR: 0.9516
TNR: 0.9529
MCC: 0.8959
BER: 0.0477
FPR: 0.0471
FNR: 0.0484
PPV: 0.9526
FDR: 0.0474
recall: 0.9516
Fscore: 0.9518
kappa: 0.8954
matrix: [21 1] [2 38] 

# LOOCV (Leave-One-Out Cross Validation) performance
ACC: 0.9677
AUC: 0.9955
AUPRC: 0.9957
TPR: 0.9677
TNR: 0.9823
MCC: 0.9332
BER: 0.025
FPR: 0.0177
FNR: 0.0323
PPV: 0.9704
FDR: 0.0296
recall: 0.9677
Fscore: 0.968
kappa: 0.931
matrix: [22 0] [2 38] 

#Repeated Holdout evaluation performance on TRAIN set, 100 times weighted average (and standard deviation) on random seeds
Average weighted ACC: 0.945
Average weighted AUC: 0.993
Average weighted AUPRC: 0.994
Average weighted SEN: 0.945
Average weighted SPE: 0.935
Average weighted MCC: 0.883
Average weighted BER: 0.06

#Bootstrap evaluation performance on TRAIN set, 100 times weighted average (and standard deviation) on random seeds
Average weighted ACC: 0.939
Average weighted AUC: 0.991
Average weighted AUPRC: 0.992
Average weighted SEN: 0.939
Average weighted SPE: 0.933
Average weighted MCC: 0.868
Average weighted BER: 0.064

#Bootstrap .632+ rule calculated on TRAIN set, 100 folds with random seeds
0.043

# Selected Attributes	(Total attributes:10). Occurrences are shown if you chose combined model
V1067
V1110
V1256
V14
V1668
V1843
V279
V453
V698
V732

# Attribute ranking by merit calculated by information gain
0.401	V1843 
0.342	V14 
0.273	V1256 
0.245	V698 
0.245	V453 
0.234	V1668 
0.234	V1067 
0.228	V1110 
0.227	V732 
0.219	V279 

# Correlated features (Spearman)
FeatureInSignature	SpearmanCorrelationScore	CorrelatedFeature
#nothing found !

# Correlated features (Pearson)
FeatureInSignature	SpearmanCorrelationScore	CorrelatedFeature
#nothing found !


## End of file ##