A New Hierarchical Clustering Method using Topological Map
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We present a new hierarchical clustering criteria which can be applied
to data set. This is done after generating an initial partition byusing
a Topological Self Organizing Map. This criteria contains two terms
which take into account two di
erent errors simultaneously: the square
error of the entire clustering (as the Ward criteria) and the
topological structure given by the Self Organizing Map. A parameter T
allows to control the corresponding in uence of these two terms. Results
on simulated data are presented which show the e
ect of this criteria
for different values of T.
[1] Fouad Badran,et al. Hierarchical clustering of self-organizing maps for cloud classification , 2000, Neurocomputing.