An example of choosing the svm function in R

Question

I am trying to apply function selection (for example, recursive function selection) in SVM using package R. I installed Weka, which supports function selection in LibSVM, but I did not find any example for SVM syntax or anything like that. A short example might help.

Answer 1

The rfe function in caret performs a recursive selection of functions for various algorithms. Here is an example from the caret documentation :

 library(caret) data(BloodBrain, package="caret") x <- scale(bbbDescr[,-nearZeroVar(bbbDescr)]) x <- x[, -findCorrelation(cor(x), .8)] x <- as.data.frame(x) svmProfile <- rfe(x, logBBB, sizes = c(2, 5, 10, 20), rfeControl = rfeControl(functions = caretFuncs, number = 200), ## pass options to train() method = "svmRadial") # Here what your results look like (this can take some time) > svmProfile Recursive feature selection Outer resampling method: Bootstrap (200 reps) Resampling performance over subset size: Variables RMSE Rsquared RMSESD RsquaredSD Selected 2 0.6106 0.4013 0.05581 0.08162 5 0.5689 0.4777 0.05305 0.07665 10 0.5510 0.5086 0.05253 0.07222 20 0.5203 0.5628 0.04892 0.06721 71 0.5202 0.5630 0.04911 0.06703 * The top 5 variables (out of 71): fpsa3, tcsa, prx, tcpa, most_positive_charge