can anyone direct me to a package/commands in R for performing step-wise feature selection, preferably using the
I have already used linear discriminant analysis (LDA), Random forest, PCA and a wrapper using a support vector machine. I was thinking of including a partial least sqaures or a gradient boosting method, but while trying to use them on multi-class data, they cause R to crash. People have reported similar experiences on multi-class data using
caret when attempting to use
I realize that I haven't used a step-wise approach and I was searching for one that can be implemented on highly correlated, dependent variables for selecting the best performing 20 variables (for example) to create a parsimonious model.
Any suggestions would be welcomed