TR: Limitations of SOM

[Arthur Flexer]

Dear colleagues,

the following report is available via my personal WWW-page:

	http://www.ai.univie.ac.at/~arthur/
as
	ftp://ftp.ai.univie.ac.at/papers/oefai-tr-96-23.ps.Z

Sorry, there are no hardcopies available, comments are welcome!

	Sincerely, Arthur Flexer

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Arthur Flexer					       arthur at ai.univie.ac.at
Austrian Research Inst. for Artificial Intelligence    +43-1-5336112(Tel)
Schottengasse 3, A-1010 Vienna, Austria		       +43-1-5320652(Fax) 
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Flexer A.: Limitations of self-organizing maps for vector quantization and
   multidimensional scaling, to appear in: Advances in Neural Information
   Processing Systems 9, edited by M.C. Mozer, M.I. Jordan, and T. Petsche,
   available in 1997.

Abstract:

  The limitations of using self-organizing maps (SOM) for either
  clustering/vector quantization (VQ) or multidimensional scaling
  (MDS) are being discussed by reviewing recent empirical findings and
  the relevant theory. SOM's remaining ability of doing both VQ {\em
  and} MDS at the same time is challenged by a new combined
  technique of adaptive {\em K}-means clustering plus Sammon mapping
  of the cluster centroids. SOM are shown to perform significantly
  worse in terms of quantization error, in recovering the structure of
  the clusters and in preserving the topology in a comprehensive
  empirical study using a series of multivariate normal clustering
  problems.