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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/07/25 13:37:20 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 ]
Apache Spark reassigned SPARK-16710:
------------------------------------
Assignee: Apache Spark
> 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: Apache Spark
>
> 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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