A popular boosting algorithm is gradient boosting. Rather than selecting combinations of binary questions at random (like random forests), gradient boosting selects binary questions that improve prediction accuracy for each new tree. Decision trees are therefore grown sequentially, as each tree is created using information derived from the previous decision tree.
