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Int J Neural Syst. 2002 Apr;12(2):117-35.

Kernel-Kohonen networks.

Author information

1
Department of Psychology, University of Newcastle upon Tyne, Newcastle upon Tyne, NE1 7RU, UK. peter.andras@ncl.ac.uk

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.

PMID:
12035126
DOI:
10.1142/S0129065702001084
[Indexed for MEDLINE]

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