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https://issues.apache.org/jira/browse/SPARK-21812?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16387068#comment-16387068
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Bryan Cutler commented on SPARK-21812:
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Adding SPARK-15009 as an example of how to restructure the model class
hierarchy, using CountVectorizer, to own params instead of depending on
transfer from Scala.
> PySpark ML Models should not depend transfering params from Java
> ----------------------------------------------------------------
>
> Key: SPARK-21812
> URL: https://issues.apache.org/jira/browse/SPARK-21812
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Affects Versions: 2.3.0
> Reporter: holdenk
> Priority: Major
>
> After SPARK-10931 we should fix this so that the Python parameters are
> explicitly defined instead of relying on copying them from Java. This can be
> done in batches of models as sub issues since the number of params to be
> update could be quite large.
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