[R] modifying predict.nnet() to function with errorest()

[Armitage, Dave]

Greetings,

I am having trouble calculating artificial neural network 
misclassification errors using errorest() from the ipred package. 
I have had no problems estimating the values with randomForest() 
or svm(), but can't seem to get it to work with nnet(). I believe 
this is due to the output of the predict.nnet() function within 
cv.factor(). Below is a quick example of the problem I'm 
experiencing. Any ideas on how to get around it or will it simply 
not work with nnet()?

> library(MASS)
> library(nnet)
> library(ipred)
> data(iris3)
> set.seed(191)
> 
> samp <- c(sample(1:50,25), sample(51:100,25), sample(101:150,25))
> ird <- data.frame(rbind(iris3[,,1], iris3[,,2], iris3[,,3]),
+         species = factor(c(rep("s",50), rep("c", 50), rep("v", 
50))))
> errorest(species ~., data = ird, subset = samp, model = nnet, 
> size = 2, rang =0.1, decay = 5e-4, maxit = 200)
# weights:  19
initial  value 73.864441
.
.
.
final  value 0.339114
converged
Error in cv.factor(y, formula, data, model = model, predict = 
predict,  :
  predict does not return factor values



Thanks,
Dave
______________________________________

Dave Armitage
Wildlife Ecology and Conservation
University of Florida