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R-clustDDist - Clustering Discrete Distributions

Description:

Clustering of units described with discrete distributions is considered.
Frequent approach for clustering such data combines non-hierarchical
method (to allow clustering of large amount of units) with hierarchical
clustering method (to build dendrogram from the obtained nonhierarchical
clusters and determine the most 'natural' final clustering(s) from it).
The use of the squared Euclidean distance as an error function favors
steep unimodal patterns of distributions. Here several alternative error
functions are implemented. They characterize errors between clustered
units and a cluster representative - leader (which needs not be defined in
the same space). For these error functions the adapted leaders methods and
compatible agglomerative hierarchical clustering methods are
implemented.

Packages

- initial package for Fedora

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