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Posted to issues@spark.apache.org by "Huaxin Gao (Jira)" <ji...@apache.org> on 2020/02/26 00:26:00 UTC
[jira] [Commented] (SPARK-29333) Sample weight in
RandomForestRegressor
[ https://issues.apache.org/jira/browse/SPARK-29333?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17045038#comment-17045038 ]
Huaxin Gao commented on SPARK-29333:
------------------------------------
This is resolved in https://issues.apache.org/jira/browse/SPARK-9478 recently.
> 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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