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.
$\begingroup$
$\endgroup$
Add a comment
|