Table 4.

Definition of metrics for assessing the performance of the implemented classifiers.

Metric	Definition
Specificity	$\frac{\text{TN}}{\text{TN}+\text{FP}}$
Sensitivity	$\frac{\text{TP}}{\text{TP}+\text{FN}}$
Precision	$\frac{\text{TP}}{\text{TP}+\text{FP}}$
Fβ score	$(1+{\beta }^2)·\frac{\text{Precision}·\text{Sensitivity}}{({\beta }^2·\text{Precision})+\text{Sensitivity}}$, with either β = 2 (F2 score) or β = 1 (F1 score)
AUC score	Area Under the Receiver Operating Characteristic Curve

TN, true negatives; FP, false positives; FN, false negatives; TP, true positives.