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https://issues.apache.org/jira/browse/SPARK-30543?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zhengruifeng updated SPARK-30543:
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Issue Type: Improvement (was: Bug)
> RandomForest add Param bootstrap to control sampling method
> -----------------------------------------------------------
>
> Key: SPARK-30543
> URL: https://issues.apache.org/jira/browse/SPARK-30543
> Project: Spark
> Issue Type: Improvement
> Components: ML, PySpark
> Affects Versions: 3.0.0
> Reporter: zhengruifeng
> Priority: Minor
>
> Current RF with numTrees=1 will directly build a tree using the orignial
> dataset,
> while with numTrees>1 it will use bootstrap samples to build trees.
> This design is to train a DecisionTreeModel by the impl of RandomForest,
> however, it is somewhat strange.
> In Scikit-Learn, there is a param bootstrap to control bootstrap samples are
> used.
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