Github user yanboliang commented on a diff in the pull request:
https://github.com/apache/spark/pull/8866#discussion_r41984815
--- Diff: mllib/src/main/scala/org/apache/spark/ml/tree/treeParams.scala ---
@@ -214,7 +216,7 @@ private[ml] object TreeClassifierParams {
/**
* Parameters for Decision Tree-based regression algorithms.
*/
-private[ml] trait TreeRegressorParams extends Params {
+private[ml] trait TreeRegressorParams extends DecisionTreeParams with
HasVarianceCol {
--- End diff --
But if we only add ```HasVarianceCol``` to ```DecisionTreeRegressor```, we
will need to implement ```validateAndTransformSchema``` for both
```DecisionTreeRegressor``` and ```DecisionTreeRegressionModel```. And further
more, if we want to add ```HasVarianceCol``` to other Regressors, we need to
implement ```validateAndTransformSchema``` for each *Regressor and
*RegressionModel which is redundancy. I referred AFTSurvivalRegression which
provide a similar prediction function ```predictQuantiles```. Looking forward
to your comments.
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