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From "Felix Cheung (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-15767) Decision Tree Regression wrapper in SparkR
Date Mon, 22 May 2017 17:42:05 GMT

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

Felix Cheung resolved SPARK-15767.
----------------------------------
       Resolution: Fixed
    Fix Version/s: 2.3.0

> 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
>             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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