Table A5.

XGBoost classifier’s performance for the five-fold cross-validation.

	Target Class	Precision	Recall	F1-Score	AUC Score	Accuracy		Confusion Matrix
						Train	Test
Fold 1	Class 0	0.92	0.90	0.91	-	-	-	True label	Predicted label
	Class 1	0.82	0.85	0.84	-	-	-		90	10
	Average	0.87	0.88	0.87	0.91	0.99	0.88		8	46
Fold 2	Class 0	0.93	0.86	0.90	-	-	-	True label	Predicted label
	Class 1	0.77	0.89	0.83	-	-	-		86	14
	Average	0.85	0.87	0.86	0.91	1.00	87		6	48
Fold 3	Class 0	0.94	0.90	0.92	-	-	-	True label	Predicted label
	Class 1	0.83	0.89	0.86	-	-	-		90	10
	Average	0.88	0.89	0.89	0.94	0.99	0.89		6	48
Fold 4	Class 0	0.94	0.91	0.92	-	-	-	True label	Predicted label
	Class 1	0.84	0.89	0.86	-	-	-		91	9
	Average	0.89	0.90	0.89	0.93	0.99	0.90		6	47
Fold 5	Class 0	0.93	0.93	0.93	-	-	-	True label	Predicted label
	Class 1	0.87	0.87	0.87	-	-	-		93	7
	Average	0.90	0.90	0.90	0.92	0.99	0.90		7	46
	All folds’ average	0.88	0.89	0.88	0.92	0.99	0.88