Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4906#discussion_r26056478
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala ---
@@ -69,6 +74,42 @@ class GradientBoostedTrees(private val boostingStrategy:
BoostingStrategy)
case _ =>
throw new IllegalArgumentException(s"$algo is not supported by the
gradient boosting.")
}
+ baseLearners = fitGradientBoostingModel.trees
+ baseLearnerWeights = fitGradientBoostingModel.treeWeights
+ fitGradientBoostingModel
+ }
+
+ /**
+ * Method to compute error or loss for every iteration of gradient
boosting.
+ * @param data: RDD of [[org.apache.spark.mllib.regression.LabeledPoint]]
+ * @param loss: evaluation metric that defaults to boostingStrategy.loss
+ * @return an array with index i having the losses or errors for the
ensemble
+ * containing trees 1 to i + 1
+ */
+ def evaluateEachIteration(
--- End diff --
This method should be implemented in the model, not in the estimator.
There's no need to make a duplicate of the model in the estimator class. (We
try to keep estimator classes stateless except for parameter values so that
they remain lightweight types.)
This change will require a bit of refactoring, so I'll hold off on more
comments until then.
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