Maximum Relevance Minimum Redundancy Algorithm for Feature Selection
The Maximum Relevance Minimum Redundancy (mRMR) feature selection algorithm utilizes information theory metrics to optimize feature subsets.
Explore MATLAB source code curated for "信息理论" with clean implementations, documentation, and examples.
The Maximum Relevance Minimum Redundancy (mRMR) feature selection algorithm utilizes information theory metrics to optimize feature subsets.
Information Theory and Coding - MATLAB Simulation Program for Linear Block Code Encoding and Decoding with Implementation Analysis