Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/16922
Title: Rule induction based on fuzzy rough sets
Authors: Tsang, ECC
Zhao, SY
Lee, JWT
Keywords: Discernibility array
Fuzzy rough set
Rule induction
Triangular norm
Issue Date: 2007
Publisher: IEEE
Source: 2007 International Conference on Machine Learning and Cybernetics, 19-22 August 2007, Hong Kong, p. 3028-3033 How to cite?
Abstract: In this paper, we propose one method of rule induction based on fuzzy rough set. First, the consistence degree is proposed as the basic concept to induce rules based on fuzzy rough sets. The concepts of rule induction, such as value reduct, reduct rule and so on, are then proposed based on the definition of consistence degree. Second, a discernibility array is constructed, and then an algorithm to find the reduct rule using the discernibility array is designed. Finally, the numerical experimental results demonstrate that the method of rule induction proposed in this paper is feasible. The key idea of this paper is that the value reduct (i.e. reduct rule) keeps the consistence degree invariant. The main contribution of this paper is introduction of rule induction based on fuzzy rough sets using the concept of fuzzy lower and upper approximation.
URI: http://hdl.handle.net/10397/16922
ISBN: 978-1-4244-0973-0
978-1-4244-0973-0 (E-ISBN)
DOI: 10.1109/ICMLC.2007.4370667
Appears in Collections:Conference Paper

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