Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/17556#discussion_r110391698
--- 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
+ def weightedMean(pre: (Double, Int), cru: (Double, Int)): Double = {
+ val (preValue, preCount) = pre
+ val (curValue, curCount) = cru
+ (preValue * preCount + curValue * curCount) / (preCount + curCount)
+ }
+
// if possible splits is not enough or just enough, just return all
possible splits
val possibleSplits = valueCounts.length - 1
- if (possibleSplits <= numSplits) {
- valueCounts.map(_._1).init
+ if (possibleSplits == 0) {
+ // constant feature
+ Array.empty[Double]
+
+ } else if (possibleSplits <= numSplits) {
+ valueCounts
+ .sliding(2)
+ .map{x => weightedMean(x(0), x(1))}
--- End diff --
No not scanLeft, just manually building the result array and iterating
because it's already known ahead of time how big it is.
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