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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-23562) RFormula handleInvalid should handle invalid values in non-string columns.
Date Tue, 03 Apr 2018 18:21:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-23562?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16424394#comment-16424394
] 

Apache Spark commented on SPARK-23562:
--------------------------------------

User 'yogeshg' has created a pull request for this issue:
https://github.com/apache/spark/pull/20970

> RFormula handleInvalid should handle invalid values in non-string columns.
> --------------------------------------------------------------------------
>
>                 Key: SPARK-23562
>                 URL: https://issues.apache.org/jira/browse/SPARK-23562
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 2.3.0
>            Reporter: Bago Amirbekian
>            Priority: Major
>
> Currently when handleInvalid is set to 'keep' or 'skip' this only applies to String
fields. Numeric fields that are null will either cause the transformer to fail or might be
null in the resulting label column.
> I'm not sure what the semantics of keep might be for numeric columns with null values,
but we should be able to at least support skip for these types.



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