SC 99-38 Tobias Galliat, Wilhelm Huisinga, Peter Deuflhard: Self-Organizing Maps Combined with Eigenmode Analysis for
Automated Cluster Identification
Abstract: One of the important tasks in Data Mining is automated
cluster
analysis. Self-Organizing Maps (SOMs) introduced by KOHONEN
are, in principle, a powerful tool for this task. Up to
now,
however, its cluster identification part is still open to
personal
bias. The present paper suggests a new approach towards
automated
cluster identification based on a combination of SOMs
with an
eigenmode analysis that has recently been developed by
DEUFLHARD ET AL. in the context of molecular
conformational
dynamics. Details of the algorithm are worked out.
Numerical
examples from Data Mining and Molecular Dynamics are
included.
Keywords: Self-Organizing Maps,
cluster analysis
MSC: 62H30, 15A18, 65U05, 68T05