Aliases: xpred.rpart
Keywords: tree
### ** Examples fit <- rpart(Mileage ~ Weight, car.test.frame) xmat <- xpred.rpart(fit) xerr <- (xmat - car.test.frame$Mileage)^2 apply(xerr, 2, sum) # cross-validated error estimate
0.79767456 0.28300396 0.04154257 0.01132626 1388.8498 654.4740 477.5976 485.9340
# approx same result as rel. error from printcp(fit) apply(xerr, 2, sum)/var(car.test.frame$Mileage)
0.79767456 0.28300396 0.04154257 0.01132626 60.49250 28.50616 20.80216 21.16526
printcp(fit)
Regression tree:
rpart(formula = Mileage ~ Weight, data = car.test.frame)
Variables actually used in tree construction:
[1] Weight
Root node error: 1354.6/60 = 22.576
n= 60
CP nsplit rel error xerror xstd
1 0.595349 0 1.00000 1.05450 0.181398
2 0.134528 1 0.40465 0.57926 0.104050
3 0.012828 2 0.27012 0.42769 0.080225
4 0.010000 3 0.25729 0.41948 0.072499