Table 4.

Classification results on the test sets. Accuracy, specificity and sensitivity are defined in Methods. See [25] for a description of the ROC area.

Coreceptor usage	SVM parameter C	Kernel parameter	Support vectors	Accuracy	Specificity	Sensitivity	ROC area
Blended spectrum kernel
CCR5	0.04	3	204	96.63%	85.33%	98.75%	98.68%
CXCR4	0.7	9	392	93.68%	96.00%	87.68%	96.59%
CCR5 and CXCR4	2	15	430	94.38%	98.16%	67.05%	90.16%
Local alignment kernel
CCR5	9	1	200	96.42%	87.55%	98.08%	98.12%
CXCR4	0.02	0.05	321	92.21%	97.56%	78.39%	95.11%
CCR5 and CXCR4	0.5	0.1	399	92.28%	97.20%	56.64%	87.49%
Distant segments kernel
CCR5	0.4	30	533	96.35%	83.55%	98.75%	98.95%
CXCR4	0.0001	30	577	94.80%	97.56%	87.68%	96.25%
CCR5 and CXCR4	0.2	35	698	95.15%	99.20%	65.89%	90.97%
Perfect deterministic classifier
CCR5	-	-	-	99.15%	99.55%	99.08%	-
CXCR4	-	-	-	98.66%	99.70%	95.97%	-
CCR5 and CXCR4	-	-	-	97.96%	99.68%	85.54%	-
Distant segments kernel trained on test set
CCR5	0.3	40	425	98.45%	92.88%	99.5%	99.17%
CXCR4	0.0001	35	611	98.66%	99.70%	95.97%	98.29%
CCR5 and CXCR4	0.0001	40	618	97.96%	99.68%	85.54%	96.27%