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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-15767) Decision Tree Regression wrapper in SparkR
Date Wed, 15 Jun 2016 20:45:10 GMT

    [ https://issues.apache.org/jira/browse/SPARK-15767?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15332519#comment-15332519
] 

Apache Spark commented on SPARK-15767:
--------------------------------------

User 'vectorijk' has created a pull request for this issue:
https://github.com/apache/spark/pull/13690

> 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: 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.decisionTreeRegression(dataframe,
formula, ...) .  After having implemented decision tree classification, we could refactor
this two into an API more like rpart()



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