Now i'm scratching my head as well, thought it might have to do with scaling at 
first, so i turned it off, and also tried scaling the data for the plot 
instead, but to no avail, it just switches the color, but doesn't show the 
correct contours.

And it is at least predicting the stuff right, so its doesn't seem to be a 
problem with the model.

On 26.07.2012, at 15:00, Meffy wrote:

> Ok, here a simple example. The file 
> http://r.789695.n4.nabble.com/file/n4637924/test.csv test.csv  has 400 lines
> containing 20 columns (1. column is class label, the other 19 are the
> features). 
> So what I'm doing is
> /
> data <- read.csv(file="test.csv", head=F, sep=",")
> 
> names(data) <- c("Class","V1", "V2", "V3", "V4", "V5", "V6", "V7", "V8",
> "V9", "V10", "V11", "V12", "V13", "V14", "V15", "V16", "V17", "V18", "V19")
> 
> model <- svm(as.factor(Class)~., data=data, kernel="linear")
> /
> 
> This gives me the result
> 
> /
> Parameters:
>   SVM-Type:  C-classification 
> SVM-Kernel:  linear 
>       cost:  1 
>      gamma:  0.05263158 
> 
> Number of Support Vectors:  5
> /
> When plotting this with
> 
> /
> plot(model, data, V2~V1)
> /
> 
> I'm getting
> http://r.789695.n4.nabble.com/file/n4637924/svm_result.png 
> Where am I wrong here??
> 
> 
> 
> 
> 
> --
> View this message in context: 
> http://r.789695.n4.nabble.com/Only-one-class-shown-in-SVM-plot-tp4637782p4637924.html
> Sent from the R help mailing list archive at Nabble.com.
> 
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