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The Kohonen self-organizing map method: An assessment

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Abstract

The “self-organizing map” method, due to Kohonen, is a well-known neural network method. It is closely related to cluster analysis (partitioning) and other methods of data analysis. In this article, we explore some of these close relationships. A number of properties of the technique are discussed. Comparisons with various methods of data analysis (principal components analysis, k-means clustering, and others) are presented.

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Author notes

  1. F. Murtagh

    Present address: Space Telescope-European Coordinating Facility, European Southern Observatory, Karl-Schwarzschild-Str. 2, D-85748, Garching, Germany

  2. M. Hernández-Pajares

    Present address: Department de Matemàtica Aplicada i Telemàtica, Universitat Politècnica de Catalunya, Apartat 300002, E-08080, Barcelona, Spain

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    1. F. Murtagh
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    2. M. Hernández-Pajares
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    Additional information

    This work has been partially supported for M. Hernández-Pajares by the DGCICIT of Spain under grant No. PB90-0478 and by a CESCA-1993 computer-time grant. Fionn Murtagh is affiliated to the Astrophysics Division, Space Science Department, European Space Agency.

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    Murtagh, F., Hernández-Pajares, M. The Kohonen self-organizing map method: An assessment. Journal of Classification 12, 165–190 (1995). https://doi.org/10.1007/BF03040854

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