Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science

Improved Weighted Support Vector Machine

Authors
WanLing Li, Peng Chen, Xiangjun Song
Corresponding Author
WanLing Li
Available Online June 2016.
DOI
10.2991/icamcs-16.2016.4How to use a DOI?
Keywords
SVM, Weighted SVM, sample, isolated points, C-SVM
Abstract

In this paper, weighted Support Vector Machine was introduced. And the weighted Support Vector Machine was improved. Some methods of determining weight were introduced, and the comprehensive method of determining weight was adopted. Simulation results indicated that the total accuracy rating by improved weighted Support Vector Machine is higher than C-SVM. It’s able to improve the distribution accuracy rating with improved Supported Vector Machine effectively.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-189-6
ISSN
2352-5401
DOI
10.2991/icamcs-16.2016.4How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - WanLing Li
AU  - Peng Chen
AU  - Xiangjun Song
PY  - 2016/06
DA  - 2016/06
TI  - Improved Weighted Support Vector Machine
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 14
EP  - 17
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.4
DO  - 10.2991/icamcs-16.2016.4
ID  - Li2016/06
ER  -