Table 6.

Ensembling of deep-learning models.

Boosting Model	Recall	Precision	F1-score	Accuracy	AUCa
Ensemble voting (MLPb, DTc, NBd)	95.81	97.28	96.54	94.91	0.955
Proposed model (AdaBooste-MLP)	97.99	95.9	96.93	95.41	0.999

^aAUC: area under the receiver operating characteristic curve.

^bMLP: multilayer perceptron.

^cDT: decision tree.

^dNB: naïve Bayes.

^eAdaBoost: adaptive boosting.