Description
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()
Attachments
Issue Links
- Is contained by
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SPARK-15069 GSoC 2016: Exposing more R and Python APIs for MLlib
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- Closed
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- relates to
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SPARK-16137 Random Forest wrapper in SparkR
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- Resolved
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- links to
