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.

additional plotting parameters

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.

Value

None.

Side Effects

A plot is produced on the current graphical device.

See Also

rpart, printcp, rpart.object

Aliases
  • plotcp
Documentation reproduced from package rpart, version 4.1-15, License: GPL-2 | GPL-3

Community examples

ats0stv@gmail.com at Dec 31, 2018 rpart v4.1-13

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) ```