An Interior Point Method for L12-SVM and Application to Feature Selection in Classification
Joint Authors
Yao, Lan
Zhang, Xiongji
Li, Dong-Hui
Chen, Haowen
Zeng, Feng
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-10
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
This paper studies feature selection for support vector machine (SVM).
By the use of the L1/2 regularization technique, we propose a new model L1/2-SVM.
To solve this nonconvex and non-Lipschitz optimization problem, we first transform it into an equivalent quadratic constrained optimization model with linear objective function and then develop an interior point algorithm.
We establish the convergence of the proposed algorithm.
Our experiments with artificial data and real data demonstrate that the L1/2-SVM model works well and the proposed algorithm is more effective than some popular methods in selecting relevant features and improving classification performance.
American Psychological Association (APA)
Yao, Lan& Zhang, Xiongji& Li, Dong-Hui& Zeng, Feng& Chen, Haowen. 2014. An Interior Point Method for L12-SVM and Application to Feature Selection in Classification. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-510126
Modern Language Association (MLA)
Yao, Lan…[et al.]. An Interior Point Method for L12-SVM and Application to Feature Selection in Classification. Journal of Applied Mathematics No. 2014 (2014), pp.1-16.
https://search.emarefa.net/detail/BIM-510126
American Medical Association (AMA)
Yao, Lan& Zhang, Xiongji& Li, Dong-Hui& Zeng, Feng& Chen, Haowen. An Interior Point Method for L12-SVM and Application to Feature Selection in Classification. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-16.
https://search.emarefa.net/detail/BIM-510126
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-510126