Receiver Operating Characteristic Curve (ROC Curve)

A ROC curve can be used to evaluate the goodness of fit for a binary classifier. It is a plot of the true positive rate (rate of events that are correctly predicted as events) against the false positive rate (rate of nonevents predicted to be events) for the different possible cutpoints.

A ROC curve demonstrates the following:

• The trade-off between sensitivity and specificity (any increase in sensitivity will be accompanied by a decrease in specificity).

• The closer the curve follows the left border and then the top border of the ROC space, the more accurate the test.

• The closer the curve comes to the 45-degree diagonal of the ROC space, the less accurate the test.