The equivalence of support vector machine and regularization neural networks

被引：35
|
作者：
András, P [1 ]
机构：
[1] Newcastle Univ, Dept Psychol, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
来源：
NEURAL PROCESSING LETTERS | 2002年 / 15卷 / 02期
关键词：
approximation; equivalent neural networks; regularization; support vector machine;
D O I：
10.1023/A:1015292818897
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We show in this brief paper the equivalence of the support vector machine and regularization neural networks. We prove both implication sides of the equivalence in a generally applicable way. The novelty lies in the effective construction of the regularization operator corresponding to a given support vector machine formulation. We give also a short introductory description of both neural network approximation frameworks.
引用
收藏
页码：97 / 104
页数：8
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