I am using few regression based ML models in r language for hyperparameter tuning and evaluate its performance. I need to evaluate also its counterparts in weka tool. I am using neural network (nnet), cart (rpart), svm, random forest (rf) and gradient boosting method using r language. My question is which are the the alternatives of these algorithms in weka in terms of the similar parameters? I am asking this because the names of parameters in weka are different than r language, even if they are similar.