feature selection with randomForest package
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I'm using randomForest in order to find out the most significant variables. I was expecting some output that defines the accuracy of the model and also ranks the variables based on their importance. But i am a bit confused now. I tried randomForest and then runned importance to extract the importance of variables. But then I saw another command rfcv (Random Forest Cross-Valdidation for feature selection), which should be the most appropriate for this purpose i suppose, but the question i have regarding this is: how to get the list of the most important variables? How to see the output after running it? Which command to use?

Another thing: What is the difference between randomForest and predict.randomForest?

I am not very familiar with randomforest and R therefore any help would be appreciated. 

Thank you in advance!