![](/images/graphics-bg.png)
Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search
Joint Authors
Yang, Xin-She
Tang, Rui
Deb, Suash
Zhuang, Yan
Fong, Simon
Source
Journal of Applied Mathematics
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-28
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Fong, Simon& Zhuang, Yan& Tang, Rui& Yang, Xin-She& Deb, Suash. 2013. Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search. Journal of Applied Mathematics،Vol. 2013, no. 2013, pp.1-18.
https://search.emarefa.net/detail/BIM-483256
Modern Language Association (MLA)
Fong, Simon…[et al.]. Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search. Journal of Applied Mathematics No. 2013 (2013), pp.1-18.
https://search.emarefa.net/detail/BIM-483256
American Medical Association (AMA)
Fong, Simon& Zhuang, Yan& Tang, Rui& Yang, Xin-She& Deb, Suash. Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search. Journal of Applied Mathematics. 2013. Vol. 2013, no. 2013, pp.1-18.
https://search.emarefa.net/detail/BIM-483256
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-483256