How does Adaboost select best features from the sample data (or a unit feature vector)?

It would be nice if someone can explain if the above statement is true or not.

I've seen the term features and classifiers being used in place of each other in documentation that's available of Adaboost (that's what I thought).

• @raul_w Check out R package ada's varplot and gbm's summary method of gbm objects. They have nice citations in the manuals. – user88 Apr 10 '12 at 11:16