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

From: zhihua li <lzhtom_at_hotmail.com>
Date: Fri 26 Aug 2005 - 17:56:28 EST

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

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!

R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Aug 26 18:00:41 2005

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