You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2016/08/22 23:33:20 UTC

[jira] [Updated] (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 ]

Joseph K. Bradley updated SPARK-15767:
--------------------------------------
    Shepherd:   (was: Joseph K. Bradley)

> 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-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org