[R] fuzzy classification and dissimilarity matrix

2006-04-07 Thread Jeanne Vallet
Hello,
 
I want to make a fuzzy classification from a dissimilarity matrix
(calculated with daisy from package 'cluster'). I have tried to use
fanny (package cluster) but I have the same problems than described in a
previous message
(http://tolstoy.newcastle.edu.au/R/help/05/05/4546.html) i.e. it always
gives me two clusters in the results (even if k is different from 2)
with the same memberships for all cluster. One solution suggested to the
previous message was to use cmeans from package e1071. The problem is
that it seems that cmeans doesn't work with dissimilarity matrix and I
have to use daisy because I have mixed data. 
What can I do ? 
 
Jeanne Vallet

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Re: [R] fuzzy classification and dissimilarity matrix

2006-04-07 Thread Martin Maechler
 Jeanne == Jeanne Vallet [EMAIL PROTECTED]
 on Fri, 7 Apr 2006 12:43:59 +0200 writes:

Jeanne Hello, I want to make a fuzzy classification from a
Jeanne dissimilarity matrix (calculated with daisy from
Jeanne package 'cluster'). I have tried to use fanny
Jeanne (package cluster) but I have the same problems than
Jeanne described in a previous message
Jeanne (http://tolstoy.newcastle.edu.au/R/help/05/05/4546.html)
Jeanne i.e. it always gives me two clusters in the results
Jeanne (even if k is different from 2) with the same
Jeanne memberships for all cluster. One solution suggested
Jeanne to the previous message was to use cmeans from
Jeanne package e1071. The problem is that it seems that
Jeanne cmeans doesn't work with dissimilarity matrix and I
Jeanne have to use daisy because I have mixed data.  What
Jeanne can I do ?

This looks like a bug in  fanny(), actually somewhere in its
Fortran code.
Following the above URL leads to a reproducible example --
eventually! -- from Matthias Temple, though a relatively large
example.

I'd like to look at the bug and fix it as soon as possible.
If you want you can also send me (privately, not via R-help!)
your dissmilarity object {resulting from daisy()}, or preferably
your data set and the exact calls you used {daisy(), then
fanny()}, to produce the outcome you mention above.

Regards,
Martin Maechler, ETH Zurich
 
Jeanne Jeanne Vallet
Jeanne [[alternative HTML version deleted]]

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