Multicategory Nonparallel Proximal Support Vector Machine

DOI

10.2991/iske.2007.98How to use a DOI?

Keywords

support vector machine, multicategory data classification, generalized eigenvalue

Abstract

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.

Copyright

© 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/).

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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  -