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- T. Graepel and
K. Obermayer. Fuzzy Topographic Kernel Clustering.
.
In W. Brauer, editor, Proceedings of the 5th GI Workshop Fuzzy Neuro
Systems, pages 90-97, 1998.
(FTP Gzipped PostScript, 8 pages, 69 kb)
A new topographic clustering algorithm is proposed, which -- by the
use of integral operator kernel functions -- efficiently estimates the
centers of clusters in a high-dimensional feature space, which is related to
data space by some non linear map. Like in the Self-Organizing Map topography
is imposed by assuming finite transition probabilities between cluster
indices. The optimization of the associated cost function is achieved by
estimating the parameters via an EM-scheme and determini stic annealing. The
effect of different radial basis function kernels on topographic maps of
handwritten digit data is examined in computer simulations.
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