MATLAB Code for Attribute Reduction with Information Entropy and Fuzzy Information Entropy Algorithms
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Resource Overview
MATLAB implementation for attribute reduction featuring information entropy and fuzzy information entropy approaches; these algorithms handle both discrete and numerical variables simultaneously without requiring discretization preprocessing.
Detailed Documentation
In this paper, we present MATLAB code for attribute reduction, implementing algorithms based on information entropy and fuzzy information entropy. These algorithms can process both discrete and numerical variables concurrently while eliminating the need for data discretization. The implementation includes core functions for calculating entropy measures and determining attribute significance, with optimization techniques applied to enhance computational efficiency. Additionally, we have incorporated algorithmic improvements to boost accuracy and performance. We believe this code will help researchers better understand and apply attribute reduction algorithms, thereby contributing to advancements in related fields.
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