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

Class.: ClassifierAB: AdaboostMLP: Multilayer PerceptronNB: Naïve Bayes classifierRF: Random ForestSVM: Support Vector MachineNI: number of iterationML: minimum number of instances per leaf.CF: confidence factor for pruningLR: learning rateM: momentumNE: number of epochNT: number of treesNF: number of randomly chosen featuresG: gammaΧ2-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 curveACC: accuracyCI: confidence intervalSEN: sensitivitySPE: specificity.Performance measurements estimated on the test set (hold-out estimation) of the best classifiers based on HRV features.