Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Wang, Biqinga; b; * | Liang, Changyongb
Affiliations: [a] School of Mathematics and Computer, Tongling University, Tongling 244000, Anhui, China | [b] School of Management, Hefei University of Technology, Hefei 230009, Anhui, China
Correspondence: [*] Corresponding author: Biqing Wang, School of Mathematics and Computer, Tongling University, Tongling 244000, Anhui, China. E-mail: wbq@tlu.edu.cn.
Abstract: Attribute reduction means that redundant attributes are excluded from decision table and it is an important topic in rough set theory research. Firstly, this paper proposes a new algorithm for computing equivalence classes based on subsection quick sort and obtains a higher efficiency compared with traditional algorithms. On this basis, the algorithm for computing refined decision table is given, which makes it possible to discover attribute reduction by using part objects. Finally, a fast attribute reduction algorithm which uses quantity of information as heuristic information is presented. Time complexity of the algorithm is O(|C|2|U/C|). Theoretical analysis and experimental results show that the algorithm proposed in this paper is efficient and provides a good job for follow-up work.
Keywords: Rough set, attribute reduction, positive region, sorting, quantity of information
DOI: 10.3233/JCM-180859
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 19, no. 1, pp. 97-107, 2019
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl