You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Xusen Yin (JIRA)" <ji...@apache.org> on 2016/06/06 23:46:20 UTC

[jira] [Commented] (SPARK-15574) Python meta-algorithms in Scala

    [ https://issues.apache.org/jira/browse/SPARK-15574?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15317503#comment-15317503 ] 

Xusen Yin commented on SPARK-15574:
-----------------------------------

[~josephkb] Can I work on this one? 

> Python meta-algorithms in Scala
> -------------------------------
>
>                 Key: SPARK-15574
>                 URL: https://issues.apache.org/jira/browse/SPARK-15574
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, PySpark
>            Reporter: Joseph K. Bradley
>
> This is an experimental idea for implementing Python ML meta-algorithms (CrossValidator, TrainValidationSplit, Pipeline, OneVsRest, etc.) in Scala.  This would require a Scala wrapper for algorithms implemented in Python, somewhat analogous to Python UDFs.
> The benefit of this change would be that we could avoid currently awkward conversions between Scala/Python meta-algorithms required for persistence.  It would let us have full support for Python persistence and would generally simplify the implementation within MLlib.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org