[GitHub] spark pull request: [SPARK-10524][ML] Use the soft prediction to o...

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

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

    https://github.com/apache/spark/pull/8734#discussion_r48616278
  
    --- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala ---
    @@ -776,7 +776,7 @@ private[ml] object RandomForest extends Logging {
                   val categoryStats =
                     binAggregates.getImpurityCalculator(nodeFeatureOffset, featureValue)
                   val centroid = if (categoryStats.count != 0) {
    -                categoryStats.predict
    +                categoryStats.calculate()
    --- End diff --
    
    This should use the soft prediction, not simply the impurity.  For regression, that means using predict(), but for binary classification, that will require using categoryStats.stats(1).


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