Information Theoretic Feature Selection

Implementation for state-of-the-art mutual information based feature selection methods

Description:
Code (Matlab/C++ Mex) for the following MI based feature selection approaches:
- Maximum relevance (maxRel)
- Minimum redundancy maximum relevance (MRMR)
- Minimum redundancy (minRed)
- Quadratic programming feature selection (QPFS)
- Mutual information quotient (MIQ)
- Maximum relevance minimum total redundancy (MRMTR) or extended MRMR (EMRMR)
- Spectral relaxation global Conditional Mutual Information (SPEC_CMI)
- Conditional mutual information minimization (CMIM)
- Conditional Infomax Feature Extraction (CIFE)
Reference:
[1] Nguyen X. Vinh, Jeffrey Chan, Simone Romano and James Bailey, "Effective Global Approaches for Mutual Information based Feature Selection". To appear in Proceeedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14), August 24-27, New York City, 2014.