Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/8246#issuecomment-139311498
@NathanHowell I just looked this over, and it seems fine. A few questions:
Did you encounter this problem in practice? I would have thought that
choosing splits would take much less time than training itself. Was training
itself fast for you?
Note: There are currently 2 tree implementations, one in spark.mllib (which
you're modifying) and one in spark.ml. I eventually want to remove the
spark.mllib one and wrap the spark.ml one
[https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala].
We can commit this here and then copy it over to spark.ml in another PR.
Thanks!
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