R caret / rfe / bayesglm feature selection

Question

I'm using bayesglm for a logistic regression problem. It's a dataset of 150 rows and 2000 variables. I'm trying to do variable selection and usually look at glmnet in caret::rfe. However there isn't a method for bayesglm.

Is there anyway to manually define a method for rfe?

Answer 1

As for the the question I can only think of rewriting lmFuncs$fit function, for example:

lmFuncs$fit<-function (x, y, first, last, ...){   
     tmp <- as.data.frame(x)   
     tmp$y <- y   
 bayesglm (y ~ ., family = gaussian, data = tmp)
}

and then do your rfe.fit with rfeControl(functions = lmFuncs)