Hi,
I'm clustering objects defined by categorical variables with a hierarchical
algorithm - average linkage.
My distance matrix (general dissimilarity coefficient) includes several
distances with exactly the same values.
As I see, a standard agglomerative procedure ignores this problems, simply
selecting, above equal distances, the one that comes first.
For this reason the analysis in output depends strongly on the orderings of
the objects within the raw data matrix.
Is there a standard procedure to deal with this?
Thanks
Bruno
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