Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19458
Title: A discussion of attribute reduction in fuzzy rough sets using support vector machine
Authors: Tsang, ECC
Chen, D
Zhao, S
He, Q
Keywords: Data analysis
Data reduction
Fuzzy set theory
Knowledge representation
Matrix algebra
Pattern classification
Rough set theory
Support vector machines
Issue Date: 2006
Publisher: IEEE
Source: IEEE International Conference on Systems, Man and Cybernetics, 2006 : SMC '06, 8-11 October 2006, Taipei, p. 3436-3440 How to cite?
Abstract: 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.
URI: http://hdl.handle.net/10397/19458
ISBN: 1-4244-0099-6
1-4244-0100-3 (E-ISBN)
DOI: 10.1109/ICSMC.2006.384650
Appears in Collections:Conference Paper

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