Github user BryanCutler commented on a diff in the pull request:

    https://github.com/apache/spark/pull/17849#discussion_r132522347
  
    --- Diff: python/pyspark/ml/wrapper.py ---
    @@ -263,7 +284,8 @@ def _fit_java(self, dataset):
     
         def _fit(self, dataset):
             java_model = self._fit_java(dataset)
    -        return self._create_model(java_model)
    +        model = self._create_model(java_model)
    +        return self._copyValues(model)
    --- End diff --
    
    Yes, that is the assumption and it's the same on the Scala side too.  The 
estimators and models should both have a shared mixin that defines the common 
params used.  That's how it's done on the Scala side and Python should follow 
(once that's done, the temporary fix from here can be removed).


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