imatiach-msft commented on a change in pull request #25926: [SPARK-9612][ML]
Add instance weight support for GBTs
URL: https://github.com/apache/spark/pull/25926#discussion_r331842874
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File path:
mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala
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@@ -129,20 +129,17 @@ private[spark] object GradientBoostedTrees extends
Logging {
* corresponding to each sample.
*/
def updatePredictionError(
- data: RDD[LabeledPoint],
+ data: RDD[Instance],
predictionAndError: RDD[(Double, Double)],
treeWeight: Double,
tree: DecisionTreeRegressionModel,
loss: OldLoss): RDD[(Double, Double)] = {
-
- val newPredError = data.zip(predictionAndError).mapPartitions { iter =>
- iter.map { case (lp, (pred, error)) =>
- val newPred = updatePrediction(lp.features, pred, tree, treeWeight)
- val newError = loss.computeError(newPred, lp.label)
+ data.zip(predictionAndError).map {
+ case (Instance(label, _, features), (pred, _)) =>
Review comment:
oh, reading some of the other code this looks like unweighted error. That
seems very confusing. I think we could improve this code structure a bit more.
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