  Boosting methods have been introduced in the late 1980's. They were born
following the theoritical aspect of PAC learning. The main idea of boosting
methods is to combine weak learners to obtain a strong learner. The weak
learners are obtained iteratively by an heuristic which tries to correct the
mistakes of the previous weak learner. In 1995, Freund and Schapire [18]
introduced AdaBoost, a boosting algorithm that is still widely used today.
Since then, many views of the algorithm have been proposed to properly tame its
dynamics. In this paper, we will try to cover all the views that one can have
on AdaBoost. We will start with the original view of Freund and Schapire before
covering the different views and unify them with the same formalism. We hope
this paper will help the non-expert reader to better understand the dynamics of
AdaBoost and how the different views are equivalent and related to each other.
