[R] stack overflow and predict()

Ji Zhu jizhu at umich.edu
Sat Nov 8 21:09:09 CET 2003


Hi Andy,

It works perfectly.  Thank you so much!!

Cheers,
Ji

> 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:jizhu at umich.edu]
> >
> > 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)
> > jizhu at umich.edu                 (734) 763-4676 (F)
> > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>
>

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Ji Zhu                          439 West Hall
Assistant Professor             550 East University
Department of Statistics        Ann Arbor, MI 48109
University of Michigan          (734) 936-2577 (O)
jizhu at umich.edu                 (734) 763-4676 (F)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~




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