Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/5585#issuecomment-94509488
It's mainly to reduce clutter in the spark.ml namespace. We'll get more
and more items shared between classification and regression:
* public interfaces
* Predictor (private now, but should be public later)
* tree abstractions: Node, Split, models
* ensembles: boosting & bagging
* impl
* tree params
* ensemble params
Once the prediction Dev APIs are made public (Predictor, etc.), then we'll
have a spark.ml.prediction subpackage anyways. At that point, tree and
ensemble abstractions seem like they would belong in that subpackage, rather
than in the spark.ml namespace.
I'm OK if you prefer to keep these items in the .ml namespace, but if
you're ambivalent, then I'd prefer fewer subpackages under spark.ml
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