[
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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
