Andrew -
I think
answer = replicate(50,{fit1 <- rpart(CHAB~.,data=chabun, method="anova",
control=rpart.control(minsplit=10,
cp=0.01, xval=10));
x = printcp(fit1);
x[which.min(x[,'xerror']),'nsplit']})
will put the numbers you want into answer, but there was no reproducible
example to test it on. Unfortunately, I don't know of any way to
surpress the printing from printcp().
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Wed, 13 Oct 2010, Andrew Halford wrote:
Hi All,
I have to say upfront that I am a complete neophyte when it comes to
programming. Nevertheless I enjoy the challenge of using R because of its
incredible statistical resources.
My problem is this .........I am running a regression tree analysis using
"rpart" and I need to run the calculation repeatedly (say n=50 times) to
obtain a distribution of results from which I will pick the median one to
represent the most parsimonious tree size. Unfortunately rpart does not
contain this ability so it will have to be coded for.
Could anyone help me with this? I have provided the code (and relevant
output) for the analysis I am running. I need to run it n=50 times and from
each output pick the appropriate tree size and post it to a datafile where I
can then look at the frequency distribution of tree sizes.
Here is the code and output from a single run
fit1 <- rpart(CHAB~.,data=chabun, method="anova",
control=rpart.control(minsplit=10, cp=0.01, xval=10))
printcp(fit1)
Regression tree:
rpart(formula = CHAB ~ ., data = chabun, method = "anova", control =
rpart.control(minsplit = 10,
cp = 0.01, xval = 10))
Variables actually used in tree construction:
[1] EXP LAT POC RUG
Root node error: 35904/33 = 1088
n= 33
CP nsplit rel error xerror xstd
1 0.539806 0 1.00000 1.0337 0.41238
2 0.050516 1 0.46019 1.2149 0.38787
3 0.016788 2 0.40968 1.2719 0.41280
4 0.010221 3 0.39289 1.1852 0.38300
5 0.010000 4 0.38267 1.1740 0.38333
Each time I re-run the model I will get a slightly different output. I want
to extract the nsplit number corresponding to the lowest xerror for each run
of the model (in this case it is for nsplit = 0) over 50 runs and then look
at the distribution of nsplits after 50 runs.
Any help appreciated.
Andy
--
Andrew Halford
Associate Researcher
Marine Laboratory
University of Guam
Ph: +1 671 734 2948
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