You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Kai Jiang (JIRA)" <ji...@apache.org> on 2016/06/22 19:20:16 UTC
[jira] [Issue Comment Deleted] (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 ]
Kai Jiang updated SPARK-15767:
------------------------------
Comment: was deleted
(was: cc [~shivaram] What about your idea?)
> 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.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