A SOM Based Cluster Visualization and Its Application for False Coloring

The self-organizing map SOM is widely used as a data visualization method in various engineering applications. It performs a non-linear 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 get di erent color codings 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 meant for making an easily implementable, explorative cluster visualization tool.

• Type: Conference
• Year: 2000
• Where: IJCNN
• Authors: Johan Himberg
• Keywords: Cluster Structure, Data Visualization Method, IJCNN 2000, Neural Networks, SOM Model Vectors