You didn't provide the results of sessionInfo().
Upgrade to the version just released on cran and see if you still have the
issue.
Max
On Thu, Nov 29, 2012 at 6:55 PM, Brian Feeny <bfe...@mac.com> wrote:
> I have never been able to get class probabilities to work and I am
> relatively new to using these tools, and I am looking for some insight as
> to what may be wrong.
>
> I am using caret with kernlab/ksvm. I will simplify my problem to a basic
> data set which produces the same problem. I have read the caret vignettes
> as well as documentation for ?train. I appreciate any direction you can
> give. I realize this is a very small dataset, the actual data is much
> larger, I am just using 10 rows as an example:
>
> trainset <- data.frame(
> outcome=factor(c("0","1","0","1","0","1","1","1","1","0")),
> age=c(10, 23, 5, 28, 81, 48, 82, 23, 11, 9),
> amount=c(10.11, 22.23, 494.2, 2.0, 29.2, 39.2, 39.2, 39.0, 11.1, 12.2)
> )
>
> > str(trainset)
> 'data.frame': 7 obs. of 3 variables:
> $ outcome: Factor w/ 2 levels "0","1": 2 1 2 2 2 2 1
> $ age : num 23 5 28 48 82 11 9
> $ amount : num 22.2 494.2 2 39.2 39.2 ...
>
> > colSums(is.na(trainset))
> outcome age amount
> 0 0 0
>
>
> ## SAMPLING AND FORMULA
> dataset <- trainset
> index <- 1:nrow(dataset)
> testindex <- sample(index, trunc(length(index)*30/100))
> trainset <- dataset[-testindex,]
> testset <- dataset[testindex,-1]
>
>
> ## TUNE caret / kernlab
> set.seed(1)
> MyTrainControl=trainControl(
> method = "repeatedcv",
> number=10,
> repeats=5,
> returnResamp = "all",
> classProbs = TRUE
> )
>
>
> ## MODEL
> rbfSVM <- train(outcome~., data = trainset,
> method="svmRadial",
> preProc = c("scale"),
> tuneLength = 10,
> trControl=MyTrainControl,
> fit = FALSE
> )
>
> There were 50 or more warnings (use warnings() to see the first 50)
> > warnings()
> Warning messages:
> 1: In train.default(x, y, weights = w, ...) :
> At least one of the class levels are not valid R variables names; This
> may cause errors if class probabilities are generated because the variables
> names will be converted to: X0, X1
> 2: In caret:::predictionFunction(method = method, modelFit = mod$fit,
> ... :
> kernlab class prediction calculations failed; returning NAs
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Max
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