A discussion of attribute reduction in fuzzy rough sets using support vector machine

摘要

This paper mainly focuses on the attribute reduction in fuzzy rough sets. An algorithm using discernibility matrix to compute all the attribute reductions is developed. After reducing the attributes, we introduce Support Vector Machine (SVM) as a classification technique to test the knowledge representation ability of attribute reduction. The numerical results show that the attribute reduction with fuzzy rough sets contains the same information as the original one.