zhengruifeng commented on a change in pull request #21632:
[SPARK-19591][ML][MLlib] Add sample weights to decision trees
URL: https://github.com/apache/spark/pull/21632#discussion_r320549522
##########
File path: mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala
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@@ -37,7 +37,7 @@ import org.apache.spark.sql.types.{DataType, DoubleType,
StructType}
* Note: Marked as private and DeveloperApi since this may be made public in
the future.
*/
private[ml] trait DecisionTreeParams extends PredictorParams
- with HasCheckpointInterval with HasSeed {
+ with HasCheckpointInterval with HasSeed with HasWeightCol {
Review comment:
@imatiach-msft Params `weightCol` and `minWeightFractionPerNode` are
introduced `DecisionTreeParams` and also exposed to RF and GBT.
But RF and GBT do not support sample weighting for now. Is there any plan to
support it? or we should put these params into `DecisionTreeRegressorParams`
and `DecisionTreeClassifierParams`?
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