NEW ROBUST UNSUPERVISED SUPPORT VECTOR MACHINES

NEW ROBUST UNSUPERVISED SUPPORT VECTOR MACHINES

This paper proposes robust version to unsupervised classification algorithm based on modified robust version of primal problem of standard SVMs, which directly relaxes it with label variables to a semi-definite programming. Numerical results confirm the robustness of the proposed method.

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Veröffentlicht in:Journal of systems science and complexity 2011-06, Vol.24 (3), p.466-476
Hauptverfasser: Zhao, Kun, Zhang, Mingyu, Deng, Naiyang
Format: Artikel
Sprache:eng
Schlagworte:
Complex Systems
Control
Mathematics
Mathematics and Statistics
Mathematics of Computing
Operations Research/Decision Theory
Statistics
Systems Theory
分类算法
半定规划
原始问题
支持向量机
数值结果
版本
监督
鲁棒性
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Beschreibung
Zusammenfassung:This paper proposes robust version to unsupervised classification algorithm based on modified robust version of primal problem of standard SVMs, which directly relaxes it with label variables to a semi-definite programming. Numerical results confirm the robustness of the proposed method.
ISSN:1009-6124
1559-7067
DOI:10.1007/s11424-011-8102-8