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Posted to issues@spark.apache.org by "zhengruifeng (Jira)" <ji...@apache.org> on 2020/01/17 08:10:00 UTC

[jira] [Assigned] (SPARK-30545) Impl Extremely Randomized Trees

     [ https://issues.apache.org/jira/browse/SPARK-30545?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

zhengruifeng reassigned SPARK-30545:
------------------------------------

    Assignee: zhengruifeng

> Impl Extremely Randomized Trees
> -------------------------------
>
>                 Key: SPARK-30545
>                 URL: https://issues.apache.org/jira/browse/SPARK-30545
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML, PySpark
>    Affects Versions: 3.0.0
>            Reporter: zhengruifeng
>            Assignee: zhengruifeng
>            Priority: Major
>
> 1, Extremely Randomized Trees or ExtraTrees is widely used and impled in Scikit-Learn and OpenCV;
> 2, ExtraTrees is quite similar to RandomForest, and the main difference lie in that,on each leaf, candidate splits (only one split in Scikit-Learn's impl) are drawn at random for each feature and the best of these randomly-chosen splits is selected.
> Based on current impl of ensenble trees, it can be impled.



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