Minimum redundancy maximum relevance feature selection in matlab

The following Matlab project contains the source code and Matlab examples used for minimum redundancy maximum relevance feature selection. Two source code files of the mRMR (minimum-redundancy maximum-relevancy) feature selection method in (Peng et al, 2005 and Ding & Peng, 2005, 2003), whose better performance over the conventional top-ranking method has been demonstrated on a number of data sets in recent publications.

The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.

Project Files: 

File NameSize
mrmr_mid_d.m 2831
mrmr_miq_d.m 2911