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

object.

```
plotcp(x, minline = TRUE, lty = 3, col = 1,
upper = c("size", "splits", "none"), …)
```

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

None.

A plot is produced on the current graphical device.

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.