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https://issues.apache.org/jira/browse/SPARK-6227?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14428301#comment-14428301
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Xiangrui Meng commented on SPARK-6227:
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[~MeethuMathew] I agree with Joseph that we should add distributed linear
algebra data models in Python first before we wrap PCA and SVD. I will link the
JIRAs and it would be great if you can help on those JIRAs first.
> 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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