train for random forests

 rf2 <- train(variable ~.,
      method = "rf", 
      trControl = 
      importance = TRUE)

What is the purpose of the "importance = TRUE" argument. Is it necessary, or optional?

In train an argument comes either from caret::train or from the model used in method and for which argument are passed through ...

In you can't find it as a argument of train, (in help page or the book), you can assume it is from the model.

Here method = 'rf' means randomForest from the :package: randomForest and importance is an argument from randomForest::randomForest. See the help page.

importance Should importance of predictors be assessed?

It is FALSE by default.


You might already have gotten your answer from @cderv, but if you're looking for the meaning of (variable/feature) importance, check out this awesome book.


thank you!

Do we use importance = TRUE in order to use varImp(randomforest)? It looks like we can still use varImp() even if importance = FALSE.

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