[R] predicting fuzzy cluster membership
Prof Brian Ripley
ripley at stats.ox.ac.uk
Sat May 24 18:08:14 CEST 2003
That's not how conventional clustering works: you need to understand the
underlying principles (and for fanny, the main reference). The goal is to
place a given set of objects into clusters (overlapping clusters for
fanny). It is not to assign a future object to a cluster: that's a
completely different, supervised, pattern recognition problem, and you
should be using very different methods (given in different books, even).
Only for a few methods are there closely related prediction methods (e.g.
1nn on cluster centres for k-means, mda for emclust).
On Sat, 24 May 2003, Luis Torgo wrote:
> I'm trying to obtain a fuzzy clustering with fanny from the cluster package,
> using a given set of data. That worked just fine.
> I have another separate sample of data from the same problem. For each case in
> this new sample I would like to know their membership coefficients with
> respect to the clustering obtained with the first dataset. In effect I want
> to have a kind of prediction of the probability that each case in the new set
> belongs to each of the clusters formed with the first set of data. I do not
> want to add the second ssample to the first and build a new clustering
> because that would change the initial clustering.
> I've looked in the help pages of the cluster package for some similar example
> with no success. I've also searched the R mailing list but didn't find any
> related question.
But it's a question on (lack of) understanding of statistics, and your
best avenue is to seek expert local statistical help.
Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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