I am relatively new to machine learning generally and R specifically.
Is the (caret) package a stronger tool for using random forest rather than the (randomForest) package?
From my understanding, caret helps optimize the hyperparameters of a random forest model, is the (randomForest) package capable of finding the optimum hyperparameters as well? or they can be found after multiple iterations in the generated code from that package? e.g.
randomForest(formula, data=NULL, ..., subset, na.action=na.fail)
If (caret) is a versatile tool for Random forests, can we say the same for other models?
I used caret to generate an mlp model for the same data frame, but the accuracy was poor.