[jira] [Commented] (SPARK-16592) Improving ml.Logistic Regression on speed and scalability

["yuhao yang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-16592?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15381222#comment-15381222 ] 

yuhao yang commented on SPARK-16592:
------------------------------------

Placeholder for list of primary ongoing efforts:



> Improving ml.Logistic Regression on speed and scalability
> ---------------------------------------------------------
>
>                 Key: SPARK-16592
>                 URL: https://issues.apache.org/jira/browse/SPARK-16592
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: yuhao yang
>
> With the spreading application of Apache Spark* logistic regression, we've seen more and more requirements come up about improving the speed and scalability. Many suggestions and discussions have been evolving in the developer and user communities.  While it may be difficult to find an optimization for all the cases, understanding the various scenarios and approaches will be important. 
> As discussed with [~josephkb], this JIRA is created for discussion and collecting efforts on the optimization work of LR (logistic regression). All the ongoing related JIRA will be linked here, as well as new ideas and possibilities. 
> Users are encouraged to share their experiences/expectations on LR and track the development status from the community. Developers can leverage the JIRA to browse existing efforts, make communication and introduce research/development resources.



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