prune_se

Prune an <code>rpart</code> object using the standard error (SE) of the 
cross-validation results.

Miscellaneous data sets and functions to accompany Greenwell (2022)
"Tree-Based Methods for Statistical Learning in R" <doi:10.1201/9781003089032>.

Brandon Greenwell

treemisc

Data Sets and Functions to Accompany "Tree-Based Methods for
Statistical Learning in R"

prune_se function

<dl><dt>object</dt>
<dd>An object that inherits from class <code>"rpart"</code>.</dd>
<dt>prune</dt>
<dd>Logical indicating whether or not to return the pruned decision
tree. Default is <code>TRUE</code>. If <code>FALSE</code>, the optimal value of the 
cost-complexity parameter is returned instead.</dd>
<dt>se</dt>
<dd>Numeric specifying the number of standard errors to use when 
pruning the tree. Default is <code>1</code>, which corresponds to the 1-SE rule
described in Breiman et al. (1984).</dd></dl>

Arguments

Prune an rpart object — prune_se

<dl>

<dt>object</dt>
<dd>An object that inherits from class <code>"rpart"</code>.</dd>


<dt>prune</dt>
<dd>Logical indicating whether or not to return the pruned decision
tree. Default is <code>TRUE</code>. If <code>FALSE</code>, the optimal value of the 
cost-complexity parameter is returned instead.</dd>


<dt>se</dt>
<dd>Numeric specifying the number of standard errors to use when 
pruning the tree. Default is <code>1</code>, which corresponds to the 1-SE rule
described in Breiman et al. (1984).</dd>

</dl>

prune_se: Prune an `rpart` object

Description

Usage

Value

Arguments

References

See Also