[R] tune an support vector machine

[Uwe Bohne]

   Hej all,

   actually i try to tune a SVM in R and use the package "e1071" wich works
   pretty well.
   I do some gridsearch in the parameters and get the best possible parameters
   for classification.
   Here is my sample code

   type<-sample(c(-1,1) , 20, replace = TRUE )
   weight<-sample(c(20:50),20, replace=TRUE)
   height<-sample(c(100:200),20, replace=TRUE)
   width<-sample(c(30:50),20,replace=TRUE)
   volume<-sample(c(1000:5000),20,replace=TRUE)

   data<-cbind(type,weight,height,width,volume)
   train<-as.data.frame(data)
   library("e1071")

   features <- c("weight","height","width","volume")
   (formula<-as.formula(paste("type ~ ", paste(features, collapse= "+"))))

   svmtune=tune.svm(formula,  data=train, kernel="radial", cost=2^(-2:5),
   gamma=2^(-2:1),cross=10)
   summary(svmtune)

   My question is if there is a way to tune the features.

   So in other words - what i wanna do is to try all possible combinations of
   features : for example use only (volume) or use (weight, height) or use
   (height,volume,width) and so on for the SVM  and to get the best combination
   back.


   Best wishes

   Uwe