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_r331843003
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File path:
mllib/src/main/scala/org/apache/spark/ml/tree/impl/GradientBoostedTrees.scala
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@@ -106,13 +106,13 @@ private[spark] object GradientBoostedTrees extends
Logging {
* corresponding to every sample.
*/
def computeInitialPredictionAndError(
- data: RDD[LabeledPoint],
+ data: RDD[Instance],
initTreeWeight: Double,
initTree: DecisionTreeRegressionModel,
loss: OldLoss): RDD[(Double, Double)] = {
- data.map { lp =>
- val pred = updatePrediction(lp.features, 0.0, initTree, initTreeWeight)
- val error = loss.computeError(pred, lp.label)
+ data.map { case Instance(label, _, features) =>
+ val pred = updatePrediction(features, 0.0, initTree, initTreeWeight)
+ val error = loss.computeError(pred, label)
Review comment:
what would be the problem with this returning weighted error and getting rid
of the computeError function?
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