ROC-Boosting: A Feature Selection Method for Health Identification Using Tongue Image

Algorithm 1

ROC-Boosting algorithm.

Input:     Example set with improved Haar-like feature filtered by -test

Output: Feature set selected

()             Do

()              For each feature that is not selected

()               Compute area under ROC curve for this feature

()               If the feature is concave

()                Use negative feature value

()               End If

()               Exclude features whose ROC curve cross random guess line in ROC space

()              Next

()              Select one feature using some conditions in ROC space

()           Exclude examples correctly classified by this feature

()           If these conditions are not fulfilled

()            Exit Do

()           End if

()          Loop