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

    https://github.com/apache/spark/pull/15149#discussion_r79635015
  
    --- Diff: 
mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
 ---
    @@ -200,26 +200,9 @@ abstract class ProbabilisticClassificationModel[
         if (!isDefined(thresholds)) {
           probability.argmax
         } else {
    -      val thresholds: Array[Double] = getThresholds
    -      val probabilities = probability.toArray
    -      var argMax = 0
    -      var max = Double.NegativeInfinity
    -      var i = 0
    -      val probabilitySize = probability.size
    -      while (i < probabilitySize) {
    -        if (thresholds(i) == 0.0) {
    -          max = Double.PositiveInfinity
    -          argMax = i
    -        } else {
    -          val scaled = probabilities(i) / thresholds(i)
    -          if (scaled > max) {
    -            max = scaled
    -            argMax = i
    -          }
    -        }
    -        i += 1
    -      }
    -      argMax
    +      // If set, thresholds are known to be > 0
    +      val scaledProbability = probability.toArray.zip(getThresholds).map { 
case (p, t) => p / t }
    --- End diff --
    
    This is called for every instance in the dataset when using `transform` 
method, so I think it is. I haven't done explicit testing to see the 
difference, though. 


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