Attribute Reduction in Decision Systems Using MATLAB with Complete Source Code

We provide a comprehensive Word document containing complete source code for implementing attribute reduction in decision systems using MATLAB. Attribute reduction serves as a crucial data mining technique that simplifies datasets and enhances decision system efficiency. Our code implementation includes core algorithms such as rough set theory-based reduction methods, dependency degree calculations, and attribute significance evaluation. The solution features MATLAB functions for handling decision tables, computing equivalence classes, and implementing heuristic reduction algorithms like the Johnson reducer or genetic algorithm approaches. The documentation not only contains detailed code comments explaining each computational step but also provides relevant background knowledge and reference materials for comprehensive topic understanding. Whether you're a beginner learning attribute reduction concepts or a professional implementing optimization techniques, our documentation offers valuable assistance with practical MATLAB implementations, including data preprocessing functions and performance evaluation metrics.