Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/21097#discussion_r184763088
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/regression/GBTRegressor.scala ---
@@ -269,6 +269,21 @@ class GBTRegressionModel private[ml](
new OldGBTModel(OldAlgo.Regression, _trees.map(_.toOld), _treeWeights)
}
+ /**
+ * Method to compute error or loss for every iteration of gradient
boosting.
+ *
+ * @param dataset Dataset for validation.
+ */
+ @Since("2.4.0")
+ def evaluateEachIteration(dataset: Dataset[_]): Array[Double] = {
--- End diff --
Do we want to support evaluation on other losses, as in the old API? It
might be nice to be able to without having to modify the Model's loss Param
value.
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