More features in FFS-to-be-selected feature set would be added into the FFS-selected feature set one by one. The FFS-to-beselected feature set with M features covers the features with mRMR ranks between k+1 and k+1+M, where M is a user-defined positive integer smaller than N{k with N to be the size of the original feature set. In each round of FFS, each feature in FFS-tobe-selected feature set would be taken out and added to the FFSselected feature set. Each predictor based on each new FFSselected feature set would be tested, and the feature set obtained the highest overall accurate rate would be used as the new FFSselected feature set. This process would be run for M times, until the FFS-to-be-selected feature set becomes a null set. An FFS curve similar to the IFS curve could be drawn with x-axis as the index and y-axis as the overall accurate rate.