Fuzzy-Rough Data Reduction Based on Information Entropy
2007
Presently, many researches have been carried out on rough set based data reduction. However, this method encounters a problem when dealing with real-valued data and fuzzy information. By lucubrating the theory of fuzzy rough set and utilizing the definition of information entropy presented in literature [5], the information entropy model of fuzzy rough set has been constructed. Then the conditional information entropy of attributes is adopted to measure the significance of attributes. On this condition, a heuristic fuzzy-rough data reduction method based on information entropy (E-FRDR) has been put forward. Finally, the method is validated by an example that indicates the method is feasible.
Keywords:
- Machine learning
- Joint entropy
- Information theory and measure theory
- Type-2 fuzzy sets and systems
- Artificial intelligence
- Information diagram
- Principle of maximum entropy
- Dominance-based rough set approach
- Fuzzy set operations
- Pattern recognition
- Mathematics
- Fuzzy number
- Data mining
- Entropy (information theory)
- Computer science
- Conditional entropy
- Correction
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- Cite
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