Table 2.

Predictive modeling results using validation data.

Model	Data	Accuracy	Precision	Specificity	Sensitivity	F1-score	AUC
Logistic Regression	Original	0.95	1	1	0.25	0.93	0.62
	SMOTE	0.9	0.86	0.85	0.96	0.9	0.9
Decision Tree Classifier	Original	0.88	0.29	0.9	0.5	0.89	0.7
	SMOTE	0.93	0.89	0.88	0.98	0.93	0.93
SVC	Original	0.93	0	1	0	0.89	0.5
	SMOTE	0.88	0.82	0.79	0.96	0.87	0.88
Gradient Boosting Classifier	Original	0.93	0.5	0.96	0.5	0.93	0.73
	SMOTE	0.93	0.91	0.9	0.96	0.93	0.93
Ensemble	Original	0.95	0.67	0.98	0.5	0.94	0.74
	SMOTE	0.92	0.88	0.87	0.98	0.92	0.92

AUC: Area Under the Curve of the Receiver Operating Characteristic curve.

SVC: support-vector machines.

Source: elaborated by the authors based on the data of the study