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From "Manoj Kumar (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-5021) GaussianMixtureEM should be faster for SparseVector input
Date Thu, 05 Feb 2015 03:00:41 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5021?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14306549#comment-14306549
] 

Manoj Kumar commented on SPARK-5021:
------------------------------------

Ah, I see what you mean (Google helped me), I never knew that was called soft assignment.
But I still think there would be benefits if we do not convert the input vectors to dense
and keep everything else dense.

> 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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