Message-ID: <1115817144.428204b857f42@homae.univ-ubs.fr>
Date: 2005-05-11T13:12:24Z
From: emmanuelle.anthoine1@etud.univ-ubs.fr
Subject: generalisation in the use of cclust (library cclust)
hello,
I would like to compare indexes in order to see which clustering algorithm (k-
means, k-medoid, hierarchical clustering with euclidean and pearson distance)
is more efficient. So I want to calculate the c-index and the db in all those
cases(library cclust).
To do that I use the cclust function. How can I run this function with pearson
distance for k-means? How can I generalize cclust for hierarchical clustering
and k-medoid?
The class cclust object has a list of 13 components. Can anybody tell me how
these components are calculated?
thanks for everything.
Emmanuelle Anthoine.
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