Table 2. Parameters to quantify the performance of the classifier.

Observed	Predicted
	1	2	Percent Correct
1	TP	FN	Sensitivity
2	FP	TN	Specificity
Overall Percentage			Generalization Rate

Note: 1 and 2 represents two conditions. TP (true positive) is the number of LT symptoms correctly predicted; TN (true negative) is the number of MT symptoms correctly predicted; FP (false positive) is the number of MT symptoms classified as LT symptoms; FN (false negative) is the number of LT symptoms classified as MT symptoms. Sensitivity indicates the proportion of LT symptoms correctly predicted, the specificity indicates the proportion of MT symptoms correctly predicted, and generalization rate is the overall proportion of samples correctly predicted. These were calculated as follows: Specificity  =  TN/(TN + FP); Sensitivity  =  TP/(TP + FN); Generalization Rate  =  (TP + TN)/(TP + FN + TN + FP).