Table 5. The performance of the Different Machine Learning Models evaluated using the 10-fold cross validation method using SMOTE.

The RTF model achieves the highest AUC (0.93), F-Score (86.70%), sensitivity (69,96%) and Specificity (91.71%).

	ANN	LB	LWB	RTF	BN	SVM
Sensitivity	30.06%	31.28%	37.22%	69.96%	36.26%	63.61%
Specificity	88.00%	88.56%	84.05%	91.71%	85.86%	78.97%
Precision	57.43%	59.53%	55.67%	81.69%	57.99%	61.95%
F-score	39.46%	41.01%	53%	86.70%	44.62%	62.77%
AUC	0.67	0.69	0.67	0.93	0.70	0.71
RMSE	0.46	0.54	0.46	0.34	0.45	0.51