Piecewise-Smooth Support Vector Machine for Classification
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-11
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Support vector machine (SVM) has been applied very successfully in a variety of classification systems.
We attempt to solve the primal programming problems of SVM by converting them into smooth unconstrained minimization problems.
In this paper, a new twice continuously differentiable piecewise-smooth function is proposed to approximate the plus function, and it issues a piecewise-smooth support vector machine (PWSSVM).
The novel method can efficiently handle large-scale and high dimensional problems.
The theoretical analysis demonstrates its advantages in efficiency and precision over other smooth functions.
PWSSVM is solved using the fast Newton-Armijo algorithm.
Experimental results are given to show the training speed and classification performance of our approach.
American Psychological Association (APA)
Wu, Qing& Wang, Wenqing. 2013. Piecewise-Smooth Support Vector Machine for Classification. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1008503
Modern Language Association (MLA)
Wu, Qing& Wang, Wenqing. Piecewise-Smooth Support Vector Machine for Classification. Mathematical Problems in Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1008503
American Medical Association (AMA)
Wu, Qing& Wang, Wenqing. Piecewise-Smooth Support Vector Machine for Classification. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1008503
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1008503