Knowledge Reduction Algorithms Based on Rough Sets and Regression-Based Knowledge Reduction Representations

Exploration of rough set-based knowledge reduction algorithms and regression-based knowledge reduction representations with implementation insights

Rough Set Theory: A Framework for Uncertain Real-World Descriptions

Rough Set Theory provides a mathematical framework for handling uncertain descriptions of real-world data, with attribute reduction being one of its core components. This article elucidates the principles of Rough Set Theory and presents a heuristic-based knowledge reduction algorithm. The feasibility and effectiveness of the algorithm are demonstrated through MATLAB implementation examples, highlighting key functions and computational approaches.