Table A3.

Logistic regression’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	0.86	0.77	0.81	-	-	-	True label	Predicted label
	Class 1	0.64	0.76	0.69	-	-	-		77	23
	Average	0.75	0.76	0.77	0.84	0.81	0.76		13	41
Fold 2	Class 0	0.88	0.76	0.82	-	-	-	True label	Predicted label
	Class 1	0.65	0.81	0.72	-	-	-		76	24
	Average	0.77	0.79	0.77	0.83	0.80	0.77		10	44
Fold 3	Class 0	0.86	0.83	0.85	-	-	-	True label	Predicted label
	Class 1	0.71	0.76	0.73	-	-	-		83	17
	Average	0.79	0.79	0.79	0.88	0.79	0.80		13	41
Fold 4	Class 0	0.91	0.84	0.87	-	-	-	True label	Predicted label
	Class 1	0.74	0.85	0.79	-	-	-		84	16
	Average	0.83	0.84	0.83	0.89	0.80	0.84		8	45
Fold 5	Class 0	0.87	0.77	0.81	-	-	-	True label	Predicted label
	Class 1	0.64	0.77	0.70	-	-	-		77	23
	Average	0.75	0.77	0.76	0.86	0.81	0.77		12	41
	All folds’ average	0.78	0.79	0.78	0.86	0.80	0.78