R help - Dec 2009 - svm regression/classification

Hi everyone,
 
Can anyone please tell whether there is a difference between the code for using
svm in regression and code for using svm in classification?
 
This is my code for regression, should I change it to do classification?:
 
train <- read.table("trainingset.txt",sep=";")
test <- read.table("testset.txt",sep=";")
 
 
svmmodelfitness <- function(myformula,mydata,mytestdata) 
{
                   
     mymodel <- svm(myformula,data=mydata) 
 
      mytest <- predict(mymodel, mytestdata)
      error <- mytest - mytestdata[,1]
      -sqrt(mean(error**2))
}
 
Many thanks,
Nancy 		 	   		  
_________________________________________________________________


	[[alternative HTML version deleted]]

Hi Nancy,

Comments in line:

On Sun, Dec 27, 2009 at 3:34 AM, Nancy Adam <nancyadam84 at hotmail.com>
wrote:
> Hi everyone,
>
> Can anyone please tell whether there is a difference between the code for
using svm in regression and code for using svm in classification?
>
> This is my code for regression, should I change it to do classification?:
I'm not sure how to answer your question ... are you asking how you
can explicitly tell the `svm` function to do classification vs.
regression? Or are you asking if classification is better suited for
your problem than regression?

Are you trying to predict a label or some range of "real valued"
numbers? Can you show us your `y` vector?

-steve

-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact