Are you sure there are 100 sites in your data? Here's an example:
R> library(randomForest)
randomForest 4.5-23
Type rfNews() to see new features/changes/bug fixes.
R> f <- factor(sample(1:4, nrow(iris), replace=TRUE))
R> rf1 <- randomForest(iris[1:4], iris[[5]], strata=f, sampsize=rep(5,
nlevels(f)))
R> rf1
Call:
randomForest(x = iris[1:4], y = iris[[5]], strata = f, sampsize rep(5,
nlevels(f)))
Type of random forest: classification
Number of trees: 500
No. of variables tried at each split: 2
OOB estimate of error rate: 4.67%
Confusion matrix:
setosa versicolor virginica class.error
setosa 50 0 0 0.00
versicolor 0 47 3 0.06
virginica 0 4 46 0.08
> -----Original Message-----
> From: r-help-bounces at r-project.org
> [mailto:r-help-bounces at r-project.org] On Behalf Of Naiara Pinto
> Sent: Sunday, March 09, 2008 5:19 PM
> To: r-help at r-project.org
> Subject: [R] sampsize in Random Forests
>
> Hi all,
>
> I have a dataset where each point is assigned to a class A, B, C, or
> D. Each point is also assigned to a study site. Each study site is
> coded with a number ranging between 1-100. This information is stored
> in the vector studySites.
>
> I want to run randomForests using stratified sampling, so I
> chose the option
> strata = factor(studySites)
>
> But I am not sure how to control the number of samples taken from each
> study site. I tried to use 10 points from each study site:
> mySampSize = rep(10, 100)
>
> So my function call looks like:
> RF = randomForest(myClass~., data=myData, mtry=5, importance=TRUE,
> strata = factor(studySites), sampsize=mySampSize)
>
> But randomForest gives me the following error:
> Error in randomForest.default(m, y, ...) :
> sampsize can not be larger than class frequency
>
> Does anybody have any idea why this happens?
>
> Thank you very much,
>
> Naiara.
>
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> PLEASE do read the posting guide
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> and provide commented, minimal, self-contained, reproducible code.
>
>
>
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