Multicategory Nonparallel Proximal Support Vector Machine
Xubing Yang1, Songcan Chen, Zhisong Pan
1Computer Science and Engineering, Nanjing University of Aeronautics & Astronautics
Available Online October 2007.
- 10.2991/iske.2007.98How to use a DOI?
- support vector machine, multicategory data classification, generalized eigenvalue
We propose a multicategory classifier, termed as Multicategory Nonparallel Proximal Support Vector Machine (MNPSVM), which is in the spirit of proximal SVMs via generalized eigenvalues (GEPSVM). Difference from GEPSVM lie in that: 1) MNPSVM keeps the genuine rather than approximate geometrical interpretation of the nonparallel proximal SVMs; 2) each nonparallel plane of MNPSVM is generated by its corresponding standard eigenvalue problems, instead of nowadays generalized eigenvalue problems. The effectiveness is demonstrated by tests on synthetic and real data sets. Furthermore, we also discuss its efficiency in experiment section and conclude that MNPSVM is far higher than that of both GEPSVM and SVM.
- © 2007, 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 - Xubing Yang AU - Songcan Chen AU - Zhisong Pan PY - 2007/10 DA - 2007/10 TI - Multicategory Nonparallel Proximal Support Vector Machine BT - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007) PB - Atlantis Press SP - 574 EP - 579 SN - 1951-6851 UR - https://doi.org/10.2991/iske.2007.98 DO - 10.2991/iske.2007.98 ID - Yang2007/10 ER -