Dear Jay,

Concerning the assessment of the number of clusters and the provision
of estimated posterior probabilities of class membership, they 
can be undertaken with a model-based approach to clustering as 
adavocated, for example, in the books by McLachlan and Basford (1988, Dekker) 
and McLachlan and Peel (2000, Wiley).

Regards,
Geoff McLachlan


Quoting Jay Liu <[log in to unmask]>:

> Dear all,
> 
>  
> 
> Apart from how to determine the number of clusters, another difficulty 
> 
> in clustering (I think) is how to predict cluster memberships of new 
> 
> data. This is very straight forward in classification but I can't think 
> 
> of a single clustering method I know can do this. I guess some 
> 
> model-based techniques maybe can do this but frankly, I have no clue at all.
> 
> 
>  
> 
>  
> 
> Jay.
> 
> 




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