[jira] [Resolved] (SPARK-30543) RandomForest add Param bootstrap to control sampling method

["zhengruifeng (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-30543?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

zhengruifeng resolved SPARK-30543.
----------------------------------
    Resolution: Resolved

> 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
>            Assignee: 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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