Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/4677#discussion_r25139249
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/GradientBoostedTrees.scala ---
@@ -76,8 +77,44 @@ class GradientBoostedTrees(private val boostingStrategy:
BoostingStrategy)
def run(input: JavaRDD[LabeledPoint]): GradientBoostedTreesModel = {
run(input.rdd)
}
-}
+ /**
+ * Method to validate a gradient boosting model
+ * @param trainInput Training dataset: RDD of
[[org.apache.spark.mllib.regression.LabeledPoint]].
+ * @param validateInput Validation dataset:
+ RDD of
[[org.apache.spark.mllib.regression.LabeledPoint]].
+ Should follow same distribution as trainInput.
--- End diff --
Oh, and we should also explicitly say that validateInput should be a
*different* dataset than trainInput. (We don't need to check for this, though.
If it is the same, then validationTol acts like convergenceTol.)
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