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https://issues.apache.org/jira/browse/SPARK-5016?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14321099#comment-14321099
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Travis Galoppo commented on SPARK-5016:
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Hmm. I'm having trouble conceptualizing how to use aggregateByKey here; the
breezeData RDD is not keyed. We could have a keyed RDD of expectation sums
(with a little rework), but each entry in the breezeData RDD would need to be
operated on by each reducer (which seems awkward?)... or I'm way off?
> GaussianMixtureEM should distribute matrix inverse for large numFeatures, k
> ---------------------------------------------------------------------------
>
> Key: SPARK-5016
> URL: https://issues.apache.org/jira/browse/SPARK-5016
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.2.0
> Reporter: Joseph K. Bradley
>
> If numFeatures or k are large, GMM EM should distribute the matrix inverse
> computation for Gaussian initialization.
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