prune.rpart

prune

fitted model object of class <code>"rpart"</code>. This is assumed to be the result 
of some function that produces an object with the same named 
components as that returned by the <code>rpart</code> function.

tree

Complexity parameter to which the <code>rpart</code> object will be trimmed.

further arguments passed to or from other methods.

&#8230;

Determines a nested sequence of subtrees of the supplied <code>rpart</code> object 
by recursively <code>snipping</code> off the least important splits, based on the 
complexity parameter (<code>cp</code>).

Recursive partitioning for classification,
regression and survival trees.  An implementation of most of the
functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.

Beth Atkinson

rpart

Recursive Partitioning and Regression Trees

Terry Therneau

Brian Ripley

prune.rpart function

<dl><dt>tree</dt>
<dd>fitted model object of class <code>"rpart"</code>. This is assumed to be the result 
of some function that produces an object with the same named 
components as that returned by the <code>rpart</code> function.</dd><dt>cp</dt>
<dd>Complexity parameter to which the <code>rpart</code> object will be trimmed.</dd><dt>...</dt>
<dd>further arguments passed to or from other methods.</dd></dl>

Arguments

Cost-complexity Pruning of an Rpart Object — prune.rpart

<dl>

<dt>tree</dt>
<dd>fitted model object of class <code>"rpart"</code>. This is assumed to be the result 
of some function that produces an object with the same named 
components as that returned by the <code>rpart</code> function.</dd>

<dt>cp</dt>
<dd>Complexity parameter to which the <code>rpart</code> object will be trimmed.</dd>

<dt>...</dt>
<dd>further arguments passed to or from other methods.</dd>

</dl>

prune.rpart: Cost-complexity Pruning of an Rpart Object

Description

Usage

Value

Arguments

See Also

Examples