Visualization of single clusters

Authors:
Frank Rehm;Frank Klawonn;Rudolf Kruse
Affiliations:
German Aerospace Center, Braunschweig, Germany;University of Applied Sciences Braunschweig/Wolfenbüttel, Germany;Otto-von-Guericke-University of Magdeburg, Germany
Venue:
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Year:
2006

Citing 7
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Abstract

Evaluation of clustering partitions is a crucial step in data processing. A multitude of measures exists, which – unfortunately – give for one data set various results. In this paper we present a visualization technique to visualize single clusters of high-dimensional data. Our method maps single clusters to the plane trying to preserve membership degrees that describe a data point's gradual membership to a certain cluster. The resulting scatter plot illustrates separation of the respecting cluster and the need of additional prototypes as well. Since clusters will be visualized individually, additional prototypes can be added locally where they are needed.