Pruning for Bagging

Prune each of the trees returned by bagging.

Usage

# S3 method for class 'classbagg'
prune(tree, cp=0.01,...)

Arguments

tree

an object returned by bagging (calling this tree is needed by the generic function prune in package rpart).

cp

complexity parameter, see prune.rpart.

...

additional arguments to prune.rpart.

Details

By default, bagging grows classification trees of maximal size. One may want to prune each tree, however, it is not clear whether or not this may decrease prediction error.

Value

An object of the same class as tree with the trees pruned.

Examples

data("Glass", package = "mlbench")
library("rpart")

mod <- bagging(Type ~ ., data=Glass, nbagg=10, coob=TRUE)
pmod <- prune(mod)
print(pmod)
#> 
#> Bagging classification trees with 10 bootstrap replications 
#> 
#> Call: bagging.data.frame(formula = Type ~ ., data = Glass, nbagg = 10, 
#>     coob = TRUE)
#> 
#> Out-of-bag estimate of misclassification error:  0.2944 
#>