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

[Philippe Grosjean]

Hello,

You have access to the C code of the function in the *source* of the
package. You can modify it and recompile the package and function (its
better then to give a different name!).
Best,

Philippe Grosjean

..............................................<¡ã}))><........
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( ( ( ( (    Prof. Philippe Grosjean
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( ( ( ( (    Numerical Ecology of Aquatic Systems
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zhihua li wrote:
> 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!
> 
> 
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