Try something like this (suppose x is the matrix of predictors in the training set, and xtest is the same for the test set):
my.rp <- rpart(y ~ x, ...) test.pred <- predict(my.rp, newdata=data.frame(x=I(xtest))) Make sure the name of the variable in the data frame given to newdata matches the name of the variable in the original formula, in this case `x', a matrix. HTH, Andy > From: Ji Zhu [mailto:[EMAIL PROTECTED] > > Dear R users, > > I'm trying to use rpart() to build a classification tree on a > big dataset. The number of samples is n=100 and the number of > variables is p=10000. > > At first I stored all the data in a data.frame and got a > "stack overflow" error; then I changed the data into a matrix > and the problem disappeared. Now the trouble is when I try to > use the predict() function, since each newdata is a long list > with p=10000 elements, the predict() function doesn't > recognize it and simply returns the fitted values at the > training data (rather than the newdata). > > Could anyone give me some suggestion on how to proceed? Thank you. > > Regards, > > Ji > > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > Ji Zhu 439 West Hall > Assistant Professor 550 East University > Department of Statistics Ann Arbor, MI 48109 > University of Michigan (734) 936-2577 (O) > [EMAIL PROTECTED] (734) 763-4676 (F) > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help