SOM-based data visualization methods

Article type: Research Article

Authors: Vesanto, Juha^{; 1}

Affiliations: Laboratory of Computer and Information Science, Helsinki University of Technology, P. O. Box 5400, FIN-02015 HUT, Finland

Note: [1] E-mail: [email protected].

Abstract: The self-organizing map (SOM) is an efficient tool for visualization of multidimensional numerical data. In this paper, an overview and categorization of both old and new methods for the visualization of SOM is presented. The purpose is to give an idea of what kind of information can be acquired from different presentations and how the SOM can best be utilized in exploratory data visualization. Most of the presented methods can also be applied in the more general case of first making a vector quantization (e.g. k-means) and then a vector projection (e.g. Sammon's mapping).

Keywords: Self-organizing map, Data mining, Visualization, Vector quantization, Projection

DOI: 10.3233/IDA-1999-3203

Journal: Intelligent Data Analysis, vol. 3, no. 2, pp. 111-126, 1999