Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search
Simon Fong1; Yan Zhuang1; Rui Tang1; Xin-She Yang2; Suash Deb3
2013-12-01
Source PublicationJournal of Applied Mathematics
ISSN1110-757X
Volume2013
Other Abstract

Selecting the right set of features from data of high dimensionality for inducing an accurate classification model is a tough computational challenge. It is almost a NP-hard problem as the combinations of features escalate exponentially as the number of features increases. Unfortunately in data mining, as well as other engineering applications and bioinformatics, some data are described by a long array of features. Many feature subset selection algorithms have been proposed in the past, but not all of them are effective. Since it takes seemingly forever to use brute force in exhaustively trying every possible combination of features, stochastic optimization may be a solution. In this paper, we propose a new feature selection scheme called Swarm Search to find an optimal feature set by using metaheuristics. The advantage of Swarm Search is its flexibility in integrating any classifier into its fitness function and plugging in any metaheuristic algorithm to facilitate heuristic search. Simulation experiments are carried out by testing the Swarm Search over some high-dimensional datasets, with different classification algorithms and various metaheuristic algorithms. The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum. 

DOIhttp://dx.doi.org/10.1155/2013/590614
URLView the original
Indexed BySCI
Language英语
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000328060700001
PublisherHINDAWI LTD, ADAM HOUSE, 3RD FLR, 1 FITZROY SQ, LONDON, WIT 5HE, ENGLAND
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Citation statistics
Cited Times [WOS]:9   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorSimon Fong
Affiliation1.Department of Computer and Information Science, University of Macau, Macau
2.Faculty of Science and Technology, Middlesex University, UK
3.Department of Computer Science and Engineering, Cambridge Institute of Technology, Ranchi, India
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Simon Fong,Yan Zhuang,Rui Tang,et al. Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search[J]. Journal of Applied Mathematics,2013,2013.
APA Simon Fong,Yan Zhuang,Rui Tang,Xin-She Yang,&Suash Deb.(2013).Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search.Journal of Applied Mathematics,2013.
MLA Simon Fong,et al."Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search".Journal of Applied Mathematics 2013(2013).
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