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https://issues.apache.org/jira/browse/SPARK-29333?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Huaxin Gao resolved SPARK-29333.
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Resolution: Fixed
> 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: 3.0.0
> Reporter: Jiaqi Guo
> Priority: Major
>
> 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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