# Support vector regression in R

I am searching tutorial for support vector regression in R. I found this and manual for e1071 package. But there is few explanation how to set parameters, like choose kernels, choose regression, not classification. Any material is appreciated.

$p = \frac{1}{1+e^{(-g(f))}}$
where $g(f)$ is some function of the SVM predictions $f$. I've found that a simple linear function $g(f) = a + bf$ usually does the job.
Try using the kernlab package, you can use ksvm(...,type='eps-svr') to get regression. It's smart enough to automatically select regression if given a continuous variable.