Table A6.

AdaBoost 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	0.80	0.86	-	-	-	True label	Predicted label
	Class 1	0.70	0.87	0.78	-	-	-		80	20
	Average	0.81	0.84	0.82	0.95	0.86	0.82		7	47
Fold 2	Class 0	0.94	0.80	0.86	-	-	-	True label	Predicted label
	Class 1	0.71	0.91	0.80	-	-	-		80	20
	Average	0.83	0.85	0.83	0.95	0.87	0.83		5	49
Fold 3	Class 0	0.93	0.85	0.89	-	-	-	True label	Predicted label
	Class 1	0.76	0.89	0.82	-	-	-		85	15
	Average	0.85	0.87	0.86	0.95	0.87	0.86		6	48
Fold 4	Class 0	0.94	0.82	0.88	-	-	-	True label	Predicted label
	Class 1	0.73	0.91	0.81	-	-	-		82	18
	Average	0.83	0.86	0.84	0.95	0.88	0.85		5	48
Fold 5	Class 0	0.94	0.76	0.84	-	-	-	True label	Predicted label
	Class 1	0.67	0.91	0.77	-	-	-		76	24
	Average	0.80	0.83	0.80	0.96	0.86	0.81		5	48
	All folds’ average	0.82	0.85	0.83	0.95	0.86	0.83