First of all, kmeans doesn't work on distance matrices.

On Mon, 7 Aug 2006, Ffenics wrote:

> Hi there
> I have been using R to perform kmeans on a dataset. The data is fed in using 
> read.table and then a matrix (x) is created
>
> i.e:
>
> [
> mat <- matrix(0, nlevels(DF$V1), nlevels(DF$V2),
> dimnames = list(levels(DF$V1), levels(DF$V2)))
> mat[cbind(DF$V1, DF$V2)] <- DF$V3
> This matrix is then taken and a distance matrix (y) created using dist() 
> before performing the kmeans clustering.
>
> My query is this: not all the data for the initial matrix (x) exists and 
> therefore the matrix is not fully populated - empty cells are populated with 
> '0's.
>
> Could someone please tell me how this may affect the result from the dist() 
> command - because a '0' in a distance matrix means that the two variables are 
> identical doesnt it(?) - but I dont want tthings clustered together simply 
> because there was no information.
>
> Is this a problem and are there ways to circumnavigate them? Thanks
>
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>
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>

*** --- ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone +44 207 679 1698
[EMAIL PROTECTED], www.homepages.ucl.ac.uk/~ucakche

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