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From Ted Dunning <>
Subject Re: gsoc , EM or SVM?
Date Wed, 01 Apr 2009 20:09:16 GMT

EM is a highly non-specific term and covers a huge range of very different
algorithms.  For example, pLSI, HMM's, and mixture models can all be
estimated using EM.

What exactly did you mean to address with an EM implementation?

On Wed, Apr 1, 2009 at 1:05 PM, Grant Ingersoll <> wrote:

> Hi Yifan,
> I think both are good candidates, although AIUI, SVM is a bit harder to
> parallelize, so maybe it would make sense to focus on EM.  Of course, we
> don't have to be distributed, so you could propose a non-distributed SVM
> implementation as a first cut and then work on the distributed part as the
> project develops.
> ...
>> For EM, it is a generalization of the k-means algorithm, and we already
>> have
>> k-means in the Mahout library.

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