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July 2005


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Jason Niles <[log in to unmask]>
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Classification, clustering, and phylogeny estimation
Wed, 27 Jul 2005 09:04:56 -0400
text/plain (49 lines)

Model based approaches (see such as that used in the
Latent GOLD program provide parameter estimates that can be applied to new
cases.  As the formula for computing the posteriors may be complicated in
some cases, a trick that you can use with the Latent GOLD program to have
the program output posterior probabilities for (new) cases not used in the
model estimation is to 1) append the new cases to the bottom of your data
file and 2) create a 'case weight' variable
that equals 1 for your original cases, and a small constant such as
0.0000000001 (say 1E-100) for each new case.  Then estimate the same model
again, using this case weight as a weight and requesting
classification output to a file.  You will get the classification
information for the new records in addition
to the observed records.


----- Original Message ----- 
From: "Jay Liu" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Tuesday, July 26, 2005 1:37 PM
Subject: Prediction in clustering

> 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
> Jay.