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Improved Generalized Eigenvalue Proximal Support Vector Machine

delete2013-03-01
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PRE
AI
邵元海 (Yuan‐Hai Shao) *
N
Nai-Yang Deng
W
Wei-Jie Chen
王震 封面图
王震 (Zhen Wang)
DOI:10.1109/LSP.2012.2216874delete
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摘要

摘要

En 中文
In this letter, we propose an improved version of generalized eigenvalue proximal support vector machine (GEPSVM), called IGEPSVM for short. The main improvements are 1) the generalized eigenvalue decomposition is replaced by the standard eigenvalue decomposition, resulting in simpler optimization problems without the possible singularity. 2) An extra meaningful parameter is introduced, resulting in the stronger classification generalization ability. Experimental results on both the artificial datasets and several benchmark datasets show that our IGEPSVM is superior to GEPSVM in both computation time and classification accuracy.
Keyword:
Eigenvalue
pattern classification
proximal classification
support vector machine
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期刊

IEEE Signal Processing Magazine 封面图
IEEE Signal Processing Magazine
IF:
9.6
论文数:
1.1W
被引数:
1.7W

机构

Z
zhejiang university of technology
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3.3W
论文数: 2.0W
被引数: 22
C
china agricultural university
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论文数: 3.0W
被引数: 43
J
Jilin University
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8.7W
论文数: 5.6W
被引数: 8.9K
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