DocumentCode
1935053
Title
The Model of Fuzzy Variable Precision Rough Sets
Author
Zhao, Su-yun ; Tsang, Eric C C ; Chen, De-gang
Author_Institution
Hong Kong Polytech. Univ., Hong Kong
Volume
6
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
3057
Lastpage
3062
Abstract
One limitation of the fuzzy rough sets is its sensitivity to the perturbation of original numerical data. In this paper we construct a model of fuzzy variable precision rough sets (FVPRS) by combining the fuzzy rough sets and variable precision rough sets, which is non-sensitive to the perturbation of the original numerical data. First, the fuzzy lower and upper approximations of FVPRS model are defined, and their properties are described. Second, the concepts of attributes reduction of FVPRS model, such as attributes reduct, core and positive region, etc, are defined. Third, a discernibility matrix is adopted to develop an algorithm to obtain all the attributes reduction of FVPRS. By the strict mathematical reasoning, we prove that the results obtained by the algorithm based on the discernibility matrix are the exact attributes reducts of FVPRS. Finally, the experimental results demonstrate that the model of FVPRS is feasible and effective in the real problems.
Keywords
fuzzy set theory; matrix algebra; rough set theory; discernibility matrix; fuzzy lower approximations; fuzzy upper approximations; fuzzy variable precision rough sets; mathematical reasoning; Computer science; Cybernetics; Electronic mail; Fuzzy sets; Machine learning; Mathematical model; Mathematics; Physics computing; Rough sets; Set theory; Attributes reduction; Discernibility matrix; Fuzzy rough sets; Triangular norm; Variable precision rough sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370673
Filename
4370673
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