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Self-organizing Maps

  • Marc M. Van Hulle
Reference work entry

Abstract

A topographic map is a two-dimensional, nonlinear approximation of a potentially high-dimensional data manifold, which makes it an appealing instrument for visualizing and exploring high-dimensional data. The self-organizing map (SOM) is the most widely used algorithm, and it has led to thousands of applications in very diverse areas. In this chapter we introduce the SOM algorithm, discuss its properties and applications, and also discuss some of its extensions and new types of topographic map formation, such as those that can be used for processing categorical data, time series, and tree-structured data.

Keywords

Input Space Travel Salesman Problem Neighborhood Function Voronoi Region Neighborhood Range 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

The author is supported by the Excellence Financing program (EF 2005) and the CREA Financing program (CREA/07/027) of K.U.Leuven, the Belgian Fund for Scientific Research – Flanders (G.0234.04 and G.0588.09), the Flemish Regional Ministry of Education (Belgium) (GOA 2000/11), the Belgian Science Policy (IUAP P6/29), and the European Commission (NEST-2003-012963, STREP-2002-016276, IST-2004-027017, and ICT-2007-217077).

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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marc M. Van Hulle
    • 1
  1. 1.Laboratorium voor NeurofysiologieK.U. LeuvenLeuvenBelgium

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