I have implemented logistic regression using glmnet library. For hyper parameter tuning internal cross-validation is performed. I can fix the internal folds using set.seed so that foldid parameters can be given. I want to compare the predictive performance in SVM and Random Forest classifier. I want to know If there is a similar parameter in Random Forest and SVM so that I can fix internal folds for hyper parameter tuning in these functions.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.