Skip Navigation

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 2006 E89-A(10):2795-2802; doi:10.1093/ietfec/e89-a.10.2795
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by GUO, J.
Right arrow Articles by NISHI, T.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Copyright © 2006 The Institute of Electronics, Information and Communication Engineers

Special Section on Nonlinear Theory and its Applications -- Papers -- Control, Neural Networks and Learning

An Efficient Method for Simplifying Decision Functions of Support Vector Machines

Jun GUO1, Norikazu TAKAHASHI1 and Tetsuo NISHI2

1 The authors are with the Department of Computer Science and Communication Engineering, Kyushu Univ., Fukuoka-shi, 812-8581 Japan. E-Mail: guojun{at}kairo.csce.kyushu-u.ac.jp, 2 The author is with the Faculty of Science and Engineering, Waseda Univ., Tokyo, 162-0072 Japan.

A novel method to simplify decision functions of support vector machines (SVMs) is proposed in this paper. In our method, a decision function is determined first in a usual way by using all training samples. Next those support vectors which contribute less to the decision function are excluded from the training samples. Finally a new decision function is obtained by using the remaining samples. Experimental results show that the proposed method can effectively simplify decision functions of SVMs without reducing the generalization capability.

Key Words: support vector machines, decision function, complexity, span

Manuscript received January 16, 2006. Manuscript revised May 17, 2006. Final manuscript received June 8, 2006.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.