## Generated by BioDiscML (Leclercq et al. 2018)##
# Project: dlbcl
# ID: bayes.NaiveBayes_AUC_FB_6_0.987_129
# Classifier: bayes.NaiveBayes 
# Optimizer: AUC
# Feature search mode: FB

# 10 fold cross validation performance
ACC: 0.987
AUC: 1
AUPRC: 1
TPR: 0.987
TNR: 0.9604
MCC: 0.965
BER: 0.0263
FPR: 0.0396
FNR: 0.013
PPV: 0.9872
FDR: 0.0128
recall: 0.987
Fscore: 0.9869
kappa: 0.9644
matrix: [58 0] [1 18] 

# LOOCV (Leave-One-Out Cross Validation) performance
ACC: 0.987
AUC: 1
AUPRC: 1
TPR: 0.987
TNR: 0.9604
MCC: 0.965
BER: 0.0263
FPR: 0.0396
FNR: 0.013
PPV: 0.9872
FDR: 0.0128
recall: 0.987
Fscore: 0.9869
kappa: 0.9644
matrix: [58 0] [1 18] 

#Repeated Holdout evaluation performance on TRAIN set, 100 times weighted average (and standard deviation) on random seeds
Average weighted ACC: 0.981
Average weighted AUC: 0.999
Average weighted AUPRC: 0.999
Average weighted SEN: 0.981
Average weighted SPE: 0.961
Average weighted MCC: 0.95
Average weighted BER: 0.029

#Bootstrap evaluation performance on TRAIN set, 100 times weighted average (and standard deviation) on random seeds
Average weighted ACC: 0.985
Average weighted AUC: 0.998
Average weighted AUPRC: 0.998
Average weighted SEN: 0.985
Average weighted SPE: 0.962
Average weighted MCC: 0.959
Average weighted BER: 0.027

#Bootstrap .632+ rule calculated on TRAIN set, 100 folds with random seeds
0.011

# Selected Attributes	(Total attributes:6). Occurrences are shown if you chose combined model
D26361_at
M12963_s_at
M23323_s_at
M31724_at
M63835_at
U63743_at

# Attribute ranking by merit calculated by information gain
0.511	U63743_at 
0.34	M63835_at 
0.264	M31724_at 
0.256	M12963_s_at 
0.242	D26361_at 
0.215	M23323_s_at 

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

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


## End of file ##