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https://issues.apache.org/jira/browse/SPARK-5021?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14306538#comment-14306538
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Manoj Kumar commented on SPARK-5021:
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Can you please explain, what do you mean by "soft assignments"?
Anyhow, maybe it might not be beneficial to keep the means sparse as you said,
however we might benefit in not converting the original sample points to dense
while making the calculations (of updating the means, cov matrix etc). What do
you say?
> GaussianMixtureEM should be faster for SparseVector input
> ---------------------------------------------------------
>
> Key: SPARK-5021
> URL: https://issues.apache.org/jira/browse/SPARK-5021
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
> Assignee: Manoj Kumar
>
> GaussianMixtureEM currently converts everything to dense vectors. It would
> be nice if it were faster for SparseVectors (running in time linear in the
> number of non-zero values).
> However, this may not be too important since clustering should rarely be done
> in high dimensions.
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