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.