Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/14834#discussion_r76463590
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/ProbabilisticClassifier.scala
---
@@ -201,11 +201,24 @@ abstract class ProbabilisticClassificationModel[
probability.argmax
} else {
val thresholds: Array[Double] = getThresholds
- val scaledProbability: Array[Double] =
- probability.toArray.zip(thresholds).map { case (p, t) =>
- if (t == 0.0) Double.PositiveInfinity else p / t
+ val probabilities = probability.toArray
--- End diff --
This code was implemented in the PR for MLOR. I included it here since it
is more generic. It requires only a single pass through the probabilities array
using a while loop, so it should be slightly faster.
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