Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/3951#issuecomment-69998021
@kazk1018 Thanks for the PR! A few high-level items:
* Will it reduce duplicate code to abstract the "TreeEnsembleModel"
concept, as in Scala? Forests and boosting produce models which are very
similar. GradientBoostedTreesModel and RandomForestModel could wrap the
abstract class.
* Default parameter values: You state default parameter values in the docs
for trainClassifier/Regressor, but they are not actually set in the method
declarations. Could you please fix that?
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