[SciPy-user] PyEM: custom (non-Euclidean) distance function?

David Cournapeau cournape@gmail....
Mon Mar 16 11:53:54 CDT 2009

On Tue, Mar 17, 2009 at 1:46 AM, Emanuele Olivetti
<emanuele@relativita.com> wrote:
> You are right. I'm coming from K-means (MacKay's book) and
> moving to GMM, that's why I had in mind custom distances.

Note that GMM is what is called soft kmean in MacKay's book. You can
use other distances for kmeans, and other kind of soft-kmeans - but as
said by Josef, I am more puzzled by the idea of non euclidean distance
in the EM context, because of the inherent probabilistic view. Because
of the probabilities, there is no obvious interpretation in distance
anymore (it is not an argmin_c ||x-c|| for each point x).

There are soft kmeans algorithms with non euclidean distances, but not
in a probabilistic framework - at least I am not aware of any.



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