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

<p>Class.: Classifier</p><p>AB: Adaboost</p><p>MLP: Multilayer Perceptron</p><p>NB: Naïve Bayes classifier</p><p>RF: Random Forest</p><p>SVM: Support Vector Machine</p><p>NI: number of iteration</p><p>ML: minimum number of instances per leaf.</p><p>CF: confidence factor for pruning</p><p>LR: learning rate</p><p>M: momentum</p><p>NE: number of epoch</p><p>NT: number of trees</p><p>NF: number of randomly chosen features</p><p>G: gamma</p><p>Χ²-FS: chi squared feature selection algorithm (a subset of 10 HRV features)</p><p>CFS: correlation-based feature selection algorithm (a subset of 8 HRV features)</p><p>AUC: area under the curve</p><p>ACC: accuracy</p><p>CI: confidence interval</p><p>SEN: sensitivity</p><p>SPE: specificity.</p><p>Performance measurements estimated on the test set (hold-out estimation) of the best classifiers based on HRV features.