xpred.rpart
Return Cross-Validated Predictions
Description
Gives the predicted values for an rpart
fit, under cross validation, for a set of complexity parameter values.
Usage
xpred.rpart(fit, xval = 10, cp, return.all = FALSE)
Arguments
fit | a object of class |
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 |
return.all | if FALSE return only the first element of the prediction |
Details
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.
Value
A matrix with one row for each observation and one column for each complexity value. If return.all
is TRUE and the prediction for each node is a vector, then the result will be an array containing all of the predictions. When the response is categorical, for instance, the result contains the predicted class followed by the class probabilities of the selected terminal node; result[1,,]
will be the matrix of predicted classes, result[2,,]
the matrix of class 1 probabilities, etc.
See Also
Examples
fit <- rpart(Mileage ~ Weight, car.test.frame) xmat <- xpred.rpart(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)
Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.