Performance measurements estimated on the test set (hold-out estimation) of the best classifiers based on HRV features.

Class.: Classifier
AB: Adaboost
MLP: Multilayer Perceptron
NB: Naïve Bayes classifier
RF: Random Forest
SVM: Support Vector Machine
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
Χ2-FS: chi squared feature selection algorithm (a subset of 10 HRV features)
CFS: correlation-based feature selection algorithm (a subset of 8 HRV features)
AUC: area under the curve
ACC: accuracy
CI: confidence interval
SEN: sensitivity
SPE: specificity.
Performance measurements estimated on the test set (hold-out estimation) of the best classifiers based on HRV features.