[R] "FANNY" function in R package "cluster"

[Aamir M]

Dear All,

I am attempting to use the FANNY fuzzy clustering function in R
(Kaufman & Rousseeuw, 1990), found in the "cluster" package. I have
run into a variety of difficulties; the two most crucial difficulties
are enumerated below.

1. Where is the 'm' parameter in FANNY? 
In _Finding Groups in Data: An Introduction to Cluster Analysis_
(1990) by Kaufman & Rousseeuw, the authors discuss the FANNY
algorithm. On pages 189-190, they attempt to demonstrate an
equivalence between Fuzzy c-Means (FCM) and FANNY. In doing so they,
appear to be assuming that the value of the 'm' parameter in FCM (a
measure of the fuzziness) is fixed at m=2. Although this is how FCM
was originally formulated, it eventually became apparent that m should
be a user-specified parameter and not a fixed value of m=2.  My
question, then, is twofold. Firstly, am I correct in saying that
Kaufman & Rousseeuw have assumed m=2 in their formulation of Fuzzy
c-Means and FANNY? Secondly, is it possible to modify the FANNY
algorithm to allow user-specification of the m (fuzziness) parameter?

2. What do I do with training data?
Is there any way to use FANNY for assigning clustering membership
values to new, test data? In Fuzzy c-Means, new data is compared to
the cluster centers in order to assign clustering membership values to
the test data. However, in FANNY these centers do not exist. Is there,
then, any way to compute the FANNY clustering membership values of a
test data point without affecting the clustering membership values of
the training data? Perhaps there are enough conditions to use the
objective function as a way of computing the membership values of the
test data?

Aamir M
University of Toronto