The equivalence of support vector machine and regularization neural networks

Andras, Peter

Abstract

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.

Citation

Andras, P. (2002). The equivalence of support vector machine and regularization neural networks. Neural Processing Letters, 15, 97-104. https://doi.org/10.1023/A%3A1015292818897

• Journal Article Type: Article
• Publication Date: 2002-04
• Deposit Date: Nov 4, 2021
• Journal: Neural Processing Letters
• Print ISSN: 1370-4621
• Electronic ISSN: 1573-773X
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 15
• Pages: 97-104
• DOI: https://doi.org/10.1023/A%3A1015292818897
• Keywords: approximation, equivalent neural networks, regularization, support vector machine
• Public URL: http://researchrepository.napier.ac.uk/Output/2808978