# plotcp

0th

Percentile

##### Plot a Complexity Parameter Table for an Rpart Fit

Gives a visual representation of the cross-validation results in an rpart object.

Keywords
tree
##### Usage
plotcp(x, minline = TRUE, lty = 3, col = 1,
upper = c("size", "splits", "none"), …)
##### Arguments
x

an object of class "rpart"

minline

whether a horizontal line is drawn 1SE above the minimum of the curve.

lty

line type for this line

col

colour for this line

upper

what is plotted on the top axis: the size of the tree (the number of leaves), the number of splits or nothing.

##### Details

The set of possible cost-complexity prunings of a tree from a nested set. For the geometric means of the intervals of values of cp for which a pruning is optimal, a cross-validation has (usually) been done in the initial construction by rpart. The cptable in the fit contains the mean and standard deviation of the errors in the cross-validated prediction against each of the geometric means, and these are plotted by this function. A good choice of cp for pruning is often the leftmost value for which the mean lies below the horizontal line.

None.

##### Side Effects

A plot is produced on the current graphical device.

rpart, printcp, rpart.object
Load the required libraries r library(rpart) library(rpart.plot)  Load a sample dataset r data(Titanic)  Create a decision Tree r decisionTree <- rpart(Survived~., data = Titanic)  The raw data in the CP table of the decision tree can be printed using r decisionTree\$cptable  Plot the CP table using the plotcp function r plotcp(decisionTree)