Gabriel
Thanks for your feedback. Indeed, I was not particularly clear here. The
empty model is just a very special case in a more general setting. I'd
have to work around this deficiency in my code -- sure I can do that,
but I thought a generic solution should be possible. In particular, I'm
Kirill,
Perhaps I'm just being obtuse, but what are you proposing rpart do in the
case of an empty model? Return a "tree" that always guesses the most
common label, or doesn't guess at all (NA)? It doesn't seem like you'd need
rpart for either of those.
~G
On Wed, Aug 13, 2014 at 3:51 AM, Kiri
Dear list
For my work, it would be helpful if rpart worked seamlessly with an
empty model:
library(rpart); rpart(formula=y~0, data=data.frame(y=factor(1:10)))
Currently, an unrelated error (originating from na.rpart) is thrown.
At some point in the near future, I'd like to release a package
