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https://issues.apache.org/jira/browse/SPARK-3726?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14280651#comment-14280651
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Joseph K. Bradley commented on SPARK-3726:
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Sorry! I had forgotten that this was really solved by
[https://github.com/apache/spark/commit/8602195510f5821b37746bb7fa24902f43a1bd93]!
That commit added subsamplingRate. Thinking more about this, I'm not sure if
sampling without replacement is needed (or useful, since it is more expensive
and makes for less randomness in the bootstrapped samples).
Users can currently set subsamplingRate via Strategy, and I don't think it
needs to be added to the train* methods.
Let me know if you have a good use case for subsampling without replacement.
Thanks!
> RandomForest: Support for bootstrap options
> -------------------------------------------
>
> Key: SPARK-3726
> URL: https://issues.apache.org/jira/browse/SPARK-3726
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Joseph K. Bradley
> Assignee: Manoj Kumar
> Priority: Minor
>
> RandomForest uses BaggedPoint to simulate bootstrapped samples of the data.
> The expected size of each sample is the same as the original data (sampling
> rate = 1.0), and sampling is done with replacement. Adding support for other
> sampling rates and for sampling without replacement would be useful.
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