![](/images/graphics-bg.png)
Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization
Joint Authors
Pedrycz, Witold
Ahmad, S. Sakinah S.
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-04-09
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Information Technology and Computer Science
Abstract EN
The study is concerned with data and feature reduction in fuzzy modeling.
As these reduction activities are advantageous to fuzzy models in terms of both the effectiveness of their construction and the interpretation of the resulting models, their realization deserves particular attention.
The formation of a subset of meaningful features and a subset of essential instances is discussed in the context of fuzzy-rule-based models.
In contrast to the existing studies, which are focused predominantly on feature selection (namely, a reduction of the input space), a position advocated here is that a reduction has to involve both data and features to become efficient to the design of fuzzy model.
The reduction problem is combinatorial in its nature and, as such, calls for the use of advanced optimization techniques.
In this study, we use a technique of particle swarm optimization (PSO) as an optimization vehicle of forming a subset of features and data (instances) to design a fuzzy model.
Given the dimensionality of the problem (as the search space involves both features and instances), we discuss a cooperative version of the PSO along with a clustering mechanism of forming a partition of the overall search space.
Finally, a series of numeric experiments using several machine learning data sets is presented.
American Psychological Association (APA)
Ahmad, S. Sakinah S.& Pedrycz, Witold. 2012. Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization. Applied Computational Intelligence and Soft Computing،Vol. 2012, no. 2012, pp.1-21.
https://search.emarefa.net/detail/BIM-464620
Modern Language Association (MLA)
Ahmad, S. Sakinah S.& Pedrycz, Witold. Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization. Applied Computational Intelligence and Soft Computing No. 2012 (2012), pp.1-21.
https://search.emarefa.net/detail/BIM-464620
American Medical Association (AMA)
Ahmad, S. Sakinah S.& Pedrycz, Witold. Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization. Applied Computational Intelligence and Soft Computing. 2012. Vol. 2012, no. 2012, pp.1-21.
https://search.emarefa.net/detail/BIM-464620
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-464620