Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/16441#discussion_r94902030
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/GBTClassifier.scala ---
@@ -248,12 +269,38 @@ class GBTClassificationModel private[ml](
if (prediction > 0.0) 1.0 else 0.0
}
+ override protected def predictRaw(features: Vector): Vector = {
--- End diff --
I can see how my comment was confusing now :) Since GBT only supports two
classes right now, we could override methods like `probability2prediction`
which are by default calling what is implemented in `ProbabilisticClassifier`.
That method loops through all the classes in a while loop, divides by the
threshold and takes the largest one. Since we know we only have two classes
here, we could instead do something faster, like
````scala
if (probability(1) > getThreshold) 1 else 0
````
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