Performance measurement (10-fold-crossvalidation estimation) of the proposed algorithms based on HRV features.

CFS: correlation-based feature selection algorithm (a subset of 8 HRV features)
Χ2-FS: chi-squared feature selection algorithm (a subset of 10 HRV features)
NI: number of iteration
ML: minimum number of instances per leaf.
CF: confidence factor for pruning
LR: learning rate
M: momentum
NE: number of epoch
NT: number of trees
NF: number of randomly chosen features
G: gamma
AUC: area under the curve
CI: confidence interval
ACC: accuracy
SEN: sensitivity
SPE: specificity
In bold: the best performances of each classifier.
Performance measurement (10-fold-crossvalidation estimation) of the proposed algorithms based on HRV features.