I have trained a Random Forest model in R with the
caret package but the results are not very promising. I have decided to try with SVM models but I have a great dilemma:
Would it be acceptable to use the "ranking" of important variables given by the Random Forest model (
varImp function) to train SVM models with different number of predictors (based on this ranking)?
I supose that this Variable Importance is specific to the Random Forest model but I would like to know if it would make sense to apply this ranking to other models like SVM.