Table 3.

Classification performance of the three classification trees using different misclassification costs and the logistic regression models using different cut-off points

Classification trees	Misclassification costs
	Tree 1:1	Tree 5:1	Tree 10:1	Tree 20:1
Sensitivity	0%	16%	64.3%	91%
PPV	0%	23.2%	15%.	11.9%
Specificity	100%	95%	65.5%	36.1%
NPV	91.3%	65.8%	95%	97.7%
Error rate	8.7%	11.9%	34.6%	59.1%
AUC		71%	71%	67.6%
Logistic regression	Classification cut-offs
	0.5	0.3	0.2	0.1
Sensitivity	0%	1.1%	10.8%	65.5%
PPV	0%	22.3%	27.6%	15.5%
Specificity	100%	99.7%	97.4%	67.3%
NPV	91.64%	91.7%	92.3%	95.5%
Error rate	8.4%	8.6%	9.8%	32.8%
AUC	72%	72%	72%	72%