MATLAB Source Code for Data Reduction Algorithms in Rough Set Theory

This article presents MATLAB source code implementations for data reduction algorithms based on rough set theory. We provide detailed discussions on the fundamental principles and practical applications of these algorithms, accompanied by demonstration examples showcasing their effectiveness. The implementation includes key functions for handling attribute reduction, core attribute identification, and dependency degree calculations. The code structure follows rough set methodology with proper discretization techniques and decision rule generation. Additionally, we compare common data reduction techniques and analyze their similarities and differences with rough set approaches. Key MATLAB functions demonstrated include: data preprocessing routines, dependency measure calculations, and reduction set generation algorithms. Through studying this material, you will gain deeper insights into rough set algorithms and learn to apply them flexibly in practical scenarios with proper MATLAB implementation strategies.