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Posted to issues@spark.apache.org by "Manoj Kumar (JIRA)" <ji...@apache.org> on 2015/08/01 15:31:04 UTC

[jira] [Commented] (SPARK-6227) PCA and SVD for PySpark

    [ https://issues.apache.org/jira/browse/SPARK-6227?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14650314#comment-14650314 ] 

Manoj Kumar commented on SPARK-6227:
------------------------------------

[~mengxr] Can this be assigned to me? Since the blockmatrix PR is already worked on.

> PCA and SVD for PySpark
> -----------------------
>
>                 Key: SPARK-6227
>                 URL: https://issues.apache.org/jira/browse/SPARK-6227
>             Project: Spark
>          Issue Type: Sub-task
>          Components: MLlib, PySpark
>    Affects Versions: 1.2.1
>            Reporter: Julien Amelot
>
> The Dimensionality Reduction techniques are not available via Python (Scala + Java only).
> * Principal component analysis (PCA)
> * Singular value decomposition (SVD)
> Doc:
> http://spark.apache.org/docs/1.2.1/mllib-dimensionality-reduction.html



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