A SOM based cluster visualization and its application for false coloring

Abstract

The self-organizing map (SOM) is widely used as a data visualization method in various engineering applications. It performs a nonlinear mapping from a high-dimensional data space to a lower dimensional visualization space. In this paper, a simple method for visualizing the cluster structure of SOM model vectors is presented. The method may be used to produce tree-like visualizations, but the main application here is to derive different color coding that express the approximate cluster structure of the SOM model vectors. This coloring may be exploited in making false color (pseudo color) presentations of the original data. The method is especially designed as an easily implementable, explorative cluster visualization tool.