[R] learning decision trees with one's own scoring functins

[zhihua li]

Hi netters,

I want to learn a decision tree from a series of instances (learning data). 
The packages
tree or rpart can do this quite well, but the scoring functions (splitting 
criteria) are
fixed in these packages, like gini or something. However, I'm going to use 
another scoring
function. 

At first I wanna modify the R code of tree or rpart and put my own scoring 
function in. But it seems that tree and rpart perform the splitting 
procedure by calling external C functions, which I have no access to. So do 
I have to write R code from scratch to build the tree with my own scoring 
functions? It's a really tough task. Or r there other R packages that can 
do similar things with more flexible and extensible code?

Thanks a lot!