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Posted to issues@spark.apache.org by "Felix Cheung (JIRA)" <ji...@apache.org> on 2017/05/22 17:42:05 UTC

[jira] [Assigned] (SPARK-15767) Decision Tree Regression wrapper in SparkR

     [ https://issues.apache.org/jira/browse/SPARK-15767?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Felix Cheung reassigned SPARK-15767:
------------------------------------

    Assignee: zhengruifeng  (was: Kai Jiang)

> Decision Tree Regression wrapper in SparkR
> ------------------------------------------
>
>                 Key: SPARK-15767
>                 URL: https://issues.apache.org/jira/browse/SPARK-15767
>             Project: Spark
>          Issue Type: New Feature
>          Components: ML, SparkR
>            Reporter: Kai Jiang
>            Assignee: zhengruifeng
>             Fix For: 2.3.0
>
>
> Implement a wrapper in SparkR to support decision tree regression. R's naive Decision Tree Regression implementation is from package rpart with signature rpart(formula, dataframe, method="anova"). I propose we could implement API like spark.rpart(dataframe, formula, ...) .  After having implemented decision tree classification, we could refactor this two into an API more like rpart()



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