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Posted to issues@spark.apache.org by "Yanbo Liang (JIRA)" <ji...@apache.org> on 2016/08/11 05:01:20 UTC

[jira] [Assigned] (SPARK-16710) SparkR spark.glm should support weightCol

     [ https://issues.apache.org/jira/browse/SPARK-16710?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Yanbo Liang reassigned SPARK-16710:
-----------------------------------

    Assignee: Yanbo Liang

> SparkR spark.glm should support weightCol
> -----------------------------------------
>
>                 Key: SPARK-16710
>                 URL: https://issues.apache.org/jira/browse/SPARK-16710
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML, SparkR
>            Reporter: Yanbo Liang
>            Assignee: Yanbo Liang
>             Fix For: 2.1.0
>
>
> Training GLMs on weighted dataset is very important use cases. Users can pass argument {{weights}} to specify the weights vector in native R. For {{spark.glm}}, we can pass in the {{weightCol}} which is consistent with MLlib.



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