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Posted to issues@spark.apache.org by "Bago Amirbekian (JIRA)" <ji...@apache.org> on 2018/03/02 01:29:00 UTC

[jira] [Created] (SPARK-23562) RFormula handleInvalid should handle invalid values in non-string columns.

Bago Amirbekian created SPARK-23562:
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             Summary: 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


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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