Review of Ensemble Classification

Abstract— Data mining techniques like classification is effectively for used for prediction. Due to technological up gradation, the datasets which are large are distributed over different locations and classification has become a difficult task. The single classifier models are not sufficient for these types of datasets. So the recent research concentrates on combination of various classifiers and creates models. Ensemble methods combine multiple models and are useful in both supervised and unsupervised learning. This paper discusses the framework of ensemble and two types of ensemble models. A review of various algorithms of these two models is given. Combination methods which are used for combining outputs and few applications where it can be used effectively are also discussed.