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G. Pölzlbauer, A. Rauber, M. Dittenbach:
"A Vector Field Visualization Technique for Self-organizing Maps";
Vortrag: 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2005, Hanoi, Vietnam; 18.05.2005 - 20.05.2005; in: "Advances in Knowledge Discovery and Data Mining", Springer, Lecture Notes in Artificial Intelligence 3518 (2005), ISBN: 3-540-26076-5; S. 399 - 409.

The Self-Organizing Map is one of most prominent tools for the analysis
and visualization of high-dimensional data.
We propose a novel visualization technique for
Self-Organizing Maps which can be displayed either as a vector
field where arrows point to cluster centers, or as
a plot that stresses cluster borders. A parameter is
provided that allows for visualization of the cluster structure at different levels of detail.
Furthermore, we present a number of experimental results using
standard data mining benchmark data.

http://aleph.ub.tuwien.ac.at/F?base=tuw01&func=find-c&ccl_term=AC05936229

Projektleitung A Min Tjoa:
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