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A fast SVM-based wrapper feature selection method driven by a fuzzy complementary criterion

Content Provider	Springer Nature Link
Author	Moustakidis, S. P. Theocharis, J. B.
Copyright Year	2012
Abstract	The selection of informative and non-redundant features has become a prominent step in pattern classification. However, despite the intensive research, it is still an open issue to identify valuable feature subsets, especially in highly dimensional feature spaces. This paper proposes a wrapper feature selection method, in the context of support vector machines (SVMs), named Wr-SVM-FuzCoC. Our method combines effectively the advantages of the wrapper and filter approaches, achieving three goals simultaneously: classification performance, dimensionality reduction, and computational efficiency. In the filter part, a forward feature search methodology is developed, driven by a fuzzy complementary criterion, whereby at each iteration a feature is selected that exhibits the maximum additional contribution in regard to the previously selected subset. The quality of single features or feature subsets is assessed via a fuzzy local evaluation criterion with respect to patterns. This is achieved by the so-called fuzzy partition vector (FPV), comprising the fuzzy membership grades of every pattern in their target classes. Derivation of the feature FPVs is accomplished by incorporating a fuzzy output kernel-based support vector machine. The proposed method is favorably compared with existing SVM-based wrapper methods, in terms of performance capability and computational speed. Experimental investigation is carried out using a diverse pool of real datasets, including moderate and high-dimensional feature spaces.
Starting Page	379
Ending Page	397
Page Count	19
File Format	PDF
ISSN	14337541
Journal	Pattern Analysis & Applications
Volume Number	15
Issue Number	4
e-ISSN	1433755X
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-09-02
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Wrapper feature selection Fuzzy sets Feature redundancy Computational efficiency Fuzzy complementary criterion Fuzzy output support vector machines Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition

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