Description Usage Arguments Details Value See Also Examples
Gives the predicted values for an itree
fit, under
cross validation, for a set of complexity parameter values.
Similar to xpred.rpart
but will stop and print an error message
when given a fit for which cp
is not defined. If fit
has a penalty,
then all the cross-validations use the same penalty and penalization
constant found in the fit
object.
1 | xpred.itree(fit, xval=10, cp)
|
fit |
a |
xval |
number of cross-validation groups. This may also be an explicit list of integers that define the cross-validation groups. |
cp |
the desired list of complexity values. By default it is taken from the
|
From rpart:
Complexity penalties are actually ranges, not values. If the
cp
values found in the table were .36, .28,
and .13, for instance, this means that the first row of the
table holds for all complexity penalties in the range [.36, 1],
the second row for cp
in the range [.28, .36) and
the third row for [.13,.28). By default, the geometric mean
of each interval is used for cross validation.
A matrix with one row for each observation and one column for each complexity value.
1 2 3 4 5 6 7 8 9 | #rpart's example:
fit <- itree(Mileage ~ Weight, car.test.frame)
xmat <- xpred.itree(fit)
xerr <- (xmat - car.test.frame$Mileage)^2
apply(xerr, 2, sum) # cross-validated error estimate
# approx same result as rel. error from printcp(fit)
apply(xerr, 2, sum)/var(car.test.frame$Mileage)
printcp(fit)
|
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