 On the other hand features can be selected to be mutually far away from each other while still having "high" correlation to the classification variable.This scheme, termed as "Minimum Redundancy Maximum Relevance" (mRMR) selection has been found to be more powerful than the maximum relevance selection.As a special case, the "correlation" can be replaced by the statistical dependency between variables.