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https://issues.apache.org/jira/browse/SPARK-5400?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14290971#comment-14290971
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Travis Galoppo commented on SPARK-5400:
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Hmm. This has me thinking in a different direction. We could generalize the
expectation-maximization algorithm to work with any mixture model supporting a
set of necessary likelihood compute/update methods... then we could ask for,
e.g., "new ExpectationMaximization[GaussianMixtureModel]". This would
de-couple the model and the algorithm, and could open the door for the
implementation to be applied to (for instance) tomographic image reconstruction
(which seems like a great fit for Spark given the volume of data involved).
> Rename GaussianMixtureEM to GaussianMixture
> -------------------------------------------
>
> Key: SPARK-5400
> URL: https://issues.apache.org/jira/browse/SPARK-5400
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
> Priority: Minor
>
> GaussianMixtureEM is following the old naming convention of including the
> optimization algorithm name in the class title. We should probably rename it
> to GaussianMixture so that it can use other optimization algorithms in the
> future.
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