Jiaqi Guo created SPARK-29333:
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Summary: Sample weight in RandomForestRegressor
Key: SPARK-29333
URL: https://issues.apache.org/jira/browse/SPARK-29333
Project: Spark
Issue Type: New Feature
Components: ML
Affects Versions: 2.4.4
Reporter: Jiaqi Guo
I think there have been some tickets that are related to this feature request.
Even though the tickets earlier have been designated with resolved status, it
still seems impossible to add sample weight to random forest
classifier/regressor.
The possibility of having sample weight is definitely useful for many use
cases, for example class imbalance and weighted bias correction for the
samples. I think the sample weight should be considered in the splitting
criterion.
Please correct me if I am missing the new feature. Otherwise, it would be great
to have an update on whether we have a path forward supporting this in the near
future.
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