Kernel-kohonen networks

Andras, Peter

Abstract

We investigate the combination of the Kohonen networks with the kernel methods in the context of classification. We use the idea of kernel functions to handle products of vectors of arbitrary dimension. We indicate how to build Kohonen networks with robust classification performance by transformation of the original data vectors into a possibly infinite dimensional space. The resulting Kohonen networks preserve a non-Euclidean neighborhood structure of the input space that fits the properties of the data. We show how to optimize the transformation of the data vectors in order to obtain higher classification performance. We compare the kernel-Kohonen networks with the regular Kohonen networks in the context of a classification task.

Citation

Andras, P. (2002). Kernel-kohonen networks. International Journal of Neural Systems, 12(2), 117-135. https://doi.org/10.1142/S0129065702001084

• Journal Article Type: Article
• Acceptance Date: Apr 15, 2002
• Publication Date: 2002-04
• Deposit Date: Nov 4, 2021
• Journal: International Journal of Neural Systems
• Print ISSN: 0129-0657
• Electronic ISSN: 1793-6462
• Publisher: World Scientific Publishing
• Peer Reviewed: Peer Reviewed
• Volume: 12
• Issue: 2
• Pages: 117-135
• DOI: https://doi.org/10.1142/S0129065702001084
• Keywords: Adaptive kernels, classification, financial data analysis, kernel methods, Kohonen networks
• Public URL: http://researchrepository.napier.ac.uk/Output/2808703