[
https://issues.apache.org/jira/browse/SPARK-26458?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-26458.
-------------------------------
Resolution: Not A Problem
I don't quite get this; it already accounts for handleInvalid and dropLast, and
the fact that it can exist for multiple columns. Reopen if you can show a
specific example.
> OneHotEncoderModel verifies the number of category values incorrectly when
> tries to transform a dataframe.
> ----------------------------------------------------------------------------------------------------------
>
> Key: SPARK-26458
> URL: https://issues.apache.org/jira/browse/SPARK-26458
> Project: Spark
> Issue Type: Bug
> Components: ML
> Affects Versions: 2.3.1
> Reporter: duruihuan
> Priority: Major
>
> When the handleInvalid is set to "keep", then one should not compare the
> categorySizes of the tranformSchema and the values of the metadata of the
> dataframe to be transformed. Because there may be more than one invalid
> values in some columns in the dataframe, which causes exception as described
> in lines 302-306 in OneHotEncoderEstimator.scala. To be concluded, I think
> the verifyNumOfValues in the method transformSchema should be removed, which
> can be found in line 299 in the code.
>
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
