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Is rpart automatic pruning?
The decision tree produced by rpart is much more levels than that produced by Oracle Data Mining which has the automatic pruning.
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No, but the defaults for the fitting function may stop splitting "early" (for some definition of "early").
Syntax : printcp ( x ) where x is the rpart object. This function provides the optimal prunings based on the cp value. We prune the tree to avoid any overfitting of the data.
The rpart algorithm works by splitting the dataset recursively, which means that the subsets that arise from a split are further split until a predetermined termination criterion is reached.
Rpart is a powerful machine learning library in R that is used for building classification and regression trees. This library implements recursive partitioning and is very easy to use.
No, but the defaults for the fitting function may stop splitting "early" (for some definition of "early").
See ?rpart.control for the parameters you can tweak. In particular, see the argument minsplit and minbucket in that help file. These are stopping rules that will prevent any node being split if those conditions are not met.
You will most likely need to prune the tree back using prune() to some optimal value of the cost-complexity parameter.
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