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ESANN
1997

Kohonen maps versus vector quantization for data analysis

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Kohonen maps versus vector quantization for data analysis
Besides their topological properties, Kohonen maps are often used for vector quantization only. These auto-organised networks are often compared to other standard and/or adaptive vector quantization methods, and, according to the large literature on the subject, show either better or worst properties in terms of quantization, speed of convergence, approximation of probability densities, clustering,… The purpose of this paper is to define more precisely some commonly encountered problems, and to try to give some answers through well-known theoretical arguments or simulations on simple examples.
Eric de Bodt, Michel Verleysen, Marie Cottrell
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1997
Where ESANN
Authors Eric de Bodt, Michel Verleysen, Marie Cottrell
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