On performance of boosting in classification problem

The work provide some new explanation of effectiveness of the boosting methods. The main reason why boosting makes good decision functions on real world tasks is that the boosting utilizes some pattern of feature independence. We also discuss margin based risk estimations with relation to boosting and show that margin depends on complexity of composition.