[GitHub] spark pull request #17556: [SPARK-16957][MLlib] Use midpoints for split valu...

[srowen <gi...@git.apache.org>]

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

    https://github.com/apache/spark/pull/17556#discussion_r114112732
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala ---
    @@ -1009,10 +1009,24 @@ private[spark] object RandomForest extends Logging {
           // sort distinct values
           val valueCounts = valueCountMap.toSeq.sortBy(_._1).toArray
     
    -      // if possible splits is not enough or just enough, just return all possible splits
    +      // perhaps weighted mean is better in the future, see SPARK-16957 and Github PR 17556.
    +      def mean(pre: (Double, Int), cur: (Double, Int)): Double = {
    +        val (preValue, preCount) = pre
    --- End diff --
    
    Is it worth factoring a method for this? you could just write `(preValue, _) =` here, but, just dereferncing `._1` isn't so bad, and then, wondering if it saves much to make a method.


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