[R] Jackknife and rpart

[Frank E Harrell Jr]

On Wed, 16 Apr 2003 10:28:08 -0700
chumpmonkey at hushmail.com wrote:

> 
> Hi,
> 
> First, thanks to those who helped me see my gross misunderstanding of
> randomForest. I worked through a baging tutorial and now understand the
> "many tree" approach. However, it is not what I want to do! My bagged
> errors are accpetable but I need to use the actual tree and need a single
> tree application. 
> 
> I am using rpart for a classification tree but am interested in a more
> unbaised estimator of error in my tree. I lack sufficent data to train
> and test the tree and I'm hoping to bootstrap, or rather jacknife, an
> error estimate.
> 
> I do not think the rpart.object can be applied to the jackknife function
> in bootstrap but can I do something as simple as:
> 
> for(i in 1:number of samples){
>   remove i from the data
>   run the tree
>   compare sample[i] to the tree using predict
>   create an error matrix}
> 
> This would give me a confussion matrix of data not included in the tree's
> constuction.
> 
> Am I being obtuse again?
> 
> Thanks, CM
> 
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You might look at the validate.tree function in the Design library (http://hesweb1.med.virginia.edu/biostat/s/Design.html) but better validated predictive accuracy would be obtained by approximating the predictions from the randomForest by a single (moderately large) tree.  You can use rpart to develop such a tree, stopping when, for example, the R-square is 0.9 or 0.95.
---
Frank E Harrell Jr              Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine  http://hesweb1.med.virginia.edu/biostat