Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/16441#discussion_r94874968
--- 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 --
sorry I'm a bit confused, this classifier also only deals with two classes,
it does not support multiclass data. Instead of overriding, what is the
alternative? There is no default predictRaw or raw2probability implemented in
probabilistic classifier, and it seems that this is the minimum required for
GBTClassifier to use ProbabilisticClassifier. Can you please give more
information on this point?
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