Plot a Complexity Parameter Table for an Rpart Fit

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

Usage

plotcp(x, xvse = 1, minline = TRUE, lty = 3, col = 1,
  upper = c("size","splits", "none"), tab, resub.err = TRUE,
  adj.df = FALSE, ...)

Arguments

x: an object of class rpart
xvse: multiplier for xvse * SE above the minimum of the curve.
minline: whether a horizontal line is drawn 1SE above the minimum of the curve.
lty: type of lines used in plot, default = 3.
col: color of lines, default =1.
upper: what is plotted on the top axis: the size of the tree (the number of leaves), the number of splits or nothing.
tab: used for multiple cross-validation.
resub.err: use resubstitution error for calculations of SEs.
adj.df: adjust df of resubstitution error estimate for calculations of SEs.
...: additional plotting parameters

Value

None.

Side Effects

A plot is produced on the current graphical device.

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.