rsq.itree {itree} | R Documentation |
Produces 2 plots. The first plots the r-square (apparent and
apparent - from cross-validation) versus the number of splits.
The second plots the Relative Error(cross-validation) +/- 1-SE from
cross-validation versus the number of splits. Same as rsq.rpart
but does some checking to make sure warnings/error is printed
when the user attempts to call the function in cases where either
cptable=NULL
or does not have the correct meaning to make the plots
useful. Identical to the rpart
function.
rsq.itree(x)
x |
fitted model object of class |
Two plots are produced.
The labels are only appropriate for the "anova"
method. Further
the cptable from which the r-squared values are taken are not appropriate
if a penalty has been used. If this is the case, the method stops.
#rpart's example: z.auto <- itree(Mileage ~ Weight, car.test.frame) rsq.itree(z.auto)