On the use of self-organizing maps for clustering and visualization

Article type: Research Article

Authors: Flexer, Arthur

Affiliations: The Austrian Research Institute for Artificial Intelligence, Schottengasse 3, A-1010 Vienna, Austria. E-mail: [email protected]

Abstract: We show that the number of output units used in a self-organizing map (SOM) influences its applicability for either clustering or visualization. By reviewing the appropriate literature and theory and own empirical results, we demonstrate that SOMs can be used for clustering or visualization separately, for simultaneous clustering and visualization, and even for clustering via visualization. For all these different kinds of application, SOM is compared to other statistical approaches. This will show SOM to be a flexible tool which can be used for various forms of explorative data analysis but it will also be made obvious that this flexibility comes with a price in terms of impaired performance.

Keywords: self-organizing map, clustering, visualization, multidimensional scaling

DOI: 10.3233/IDA-2001-5502

Journal: Intelligent Data Analysis, vol. 5, no. 5, pp. 373-384, 2001