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From "Derrick Burns (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-2308) Add KMeans MiniBatch clustering algorithm to MLlib
Date Tue, 07 Oct 2014 02:40:33 GMT

    [ https://issues.apache.org/jira/browse/SPARK-2308?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14161390#comment-14161390
] 

Derrick Burns commented on SPARK-2308:
--------------------------------------

I submitted PR #2634 to address the issues that I mentioned.  I did NOT include mini-batch
sampling in this PR.  Once this PR is approved, I will add (back) the modification to support
mini-batch sampling.  Then we can test how it works. :)

> Add KMeans MiniBatch clustering algorithm to MLlib
> --------------------------------------------------
>
>                 Key: SPARK-2308
>                 URL: https://issues.apache.org/jira/browse/SPARK-2308
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: RJ Nowling
>            Assignee: RJ Nowling
>            Priority: Minor
>         Attachments: many_small_centers.pdf, uneven_centers.pdf
>
>
> Mini-batch is a version of KMeans that uses a randomly-sampled subset of the data points
in each iteration instead of the full set of data points, improving performance (and in some
cases, accuracy).  The mini-batch version is compatible with the KMeans|| initialization algorithm
currently implemented in MLlib.
> I suggest adding KMeans Mini-batch as an alternative.
> I'd like this to be assigned to me.



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