Hi,
sorry, I do not have any references, it was only an intuitive idea (but
there might be references somewhere out in space).
The idea is that you can indeed weight the points. For this you have to
multiply the contribution of each point to the target function by the
weight, and you have to compu
Hi,
I have read some of the papers on weighted clustering but those weigths
are with respect to variables (say we are clustering height measured in
cms and weights in tons etc) rather than each point itself and hence they
just multiply the distances with the weights. In my case, it is something
li
Hi,
the target functions of k-means clusterung and of normal mixture model
clustering (in library mclust) should work with weighted data points as
well. This is, however, only a theoretical suggestion, because as far as I
know, it is not implemented in R, and the R-functions for kmeans and
model
Hi,
I have a data set(say 2-d demands of a product (say flow-rate vs
concentration)) and with each demand is the weightage (like a probability)
of that demand occuring. Is there a way to cluster this demand-data
(deterministic or probabilistic(if possible)) which also incorporates the
weights (jus
