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: Moaref, Afsoon | Naeini, Vahid Sattari
Affiliations: Department of Computer Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
Note: [] Corresponding author. Afsoon Moaref, Department of Computer Engineering, Shahid Bahonar University of Kerman, Afzalipoor Square, 7616914111 Kerman, Iran. E-mails: [email protected]; [email protected] (V.S. Naeini).
Abstract: Finding out information about features is one of the main goals of feature selection. In that case there is not particularly care about the resulting classification accuracy, but we are interested in maximizing dependency degree. A data set can have several minimal data reductions; however, most of the methods are able to find only one minimal data reduction which is not beneficial. In this paper, we propose a feature selection method based on modified Ant Colony Optimization algorithm (ACO). The main contribution of this paper includes using fuzzy-rough gain ratio as heuristic information and new rules for pheromone updating in ACO. Unlike most of the methods which find only one minimal reduction, this method is able to find various minimal data reductions. The proposed method is compared with three other meta-heuristic methods. The results show that our approach is very successful in finding various minimal data reductions.
Keywords: Feature selection, fuzzy rough set, ant colony optimization, gain ratio, minimal reduct
DOI: 10.3233/IFS-130921
Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 5, pp. 2505-2513, 2014
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
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
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]