LuciferYang commented on pull request #29857:
URL: https://github.com/apache/spark/pull/29857#issuecomment-698111573
cc @srowen The remaining failed case is
```
RandomForestRegressorSuite:
- training with sample weights *** FAILED ***
0.756 was not greater than or equal to 0.78 (MLTestingUtils.scala:285)
```
https://github.com/apache/spark/blob/0bc0e91e4015eb98bd2f4bf17da2ec7135b520a9/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala#L171-L200
Input `(50, 10, 0.95, 0.78)` with
```
MLTestingUtils.testOversamplingVsWeighting[RandomForestRegressionModel,
RandomForestRegressor](df.as[LabeledPoint], estimator,
MLTestingUtils.modelPredictionEquals(df, _ ~= _ relTol 0.2, tol),
seed)
```
failed.
I found that the following `RandomForest.runBagged` behave differently for
the same input in Scala 2.12 and Scala 2.13, maybe related to the follow code
block:
https://github.com/apache/spark/blob/0bc0e91e4015eb98bd2f4bf17da2ec7135b520a9/mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala#L191-L215
but I am not familiar with this algorithm and I not find root cause, I think
we need an expert to guide how to fix it
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