R: Return Cross-Validated Predictions

xpred.rpart {rpart} | R Documentation

## 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)

### Arguments

`fit` | a `rpart` object.
`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 `cptable` component of the fit.

### 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.

### See Also

`rpart`

### 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)

[Package rpart version 3.1-42 Index]