cv.tree in a function

[Odile <mullodi@yahoo.fr>]

Hello,

My s-plus programm does not work and I do not know why! The problem may come from the function cv.tree.

 

Here is my function :

 

"bagging"<-

function(learning,test)

{

n <- nrow(learning)

m <- nrow(test)

K <- 25

predi <- matrix(nrow = m, ncol = K)

arbre <- tree(learning)

cval <- cv.tree(arbre FUN = prune.tree)  # It stops here!

print("here") # That is not printed...

for (i in 1:K){

XXX <- learning[sample(n,n,T),]

arb <- tree(XXX,control=tree.control(nrow(learning),mindev=0.005))

cval <- cv.tree(arb, FUN = prune.tree)

mi <- min(cval$dev)

p <- min(cval$size[cval$dev==mi]) # (number of nodes when the deviance is min)

elag <- prune.tree(arb, best=p)

predi[,i] <- predict.tree(elag,newdata=test)

}

pred <- rowMeans(predi)

errors(pred,test[,1])

}

bagging(app1,test1)

S-plus reply is :

"Error: Object "learning" not found"

or if I just run what is inside for {}, I get "missing values are not allowed"

app1 and test1 are dataframes I get with the funtion read.table and they do not contain any missing values. Actually, if I type :

arbre <- tree(app1)

cval <- cv.tree(arbre, FUN = prune.tree) 

in the command window, it works (cval is calculated).

Thanks for your help,

odile.

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