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

Xiangrui Meng updated SPARK-15767:
----------------------------------
    Issue Type: Sub-task  (was: New Feature)
        Parent: SPARK-16442

> Decision Tree Regression wrapper in SparkR
> ------------------------------------------
>
>                 Key: SPARK-15767
>                 URL: https://issues.apache.org/jira/browse/SPARK-15767
>             Project: Spark
>          Issue Type: Sub-task
>          Components: ML, SparkR
>            Reporter: Kai Jiang
>            Assignee: Kai Jiang
>
> 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()



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to