افزایش چندگانه در فرادسته بندی کننده جنگل تصمیم گیری کلونی مورچه

In this article we provide an overview of ensemble methods in classification tasks and concentrate on the different methodologies, such as Bagging, Boosting and Random Forest. We present all important types of ensemble methods including Boosting and Bagging in context of distributed approach, where agent-ants create better solutions employing adaptive mechanisms. Self adaptive, combining methods and modeling appropriate issues, such as ensembles presented here are discussed in context of the quality of the results. Smaller trees in decision forest without loss of accuracy are achieved during the analysis of different data sets.