Advanced Methodologies Employed in Ensemble of Classifiers: A Survey

If we look a few years back, we will find that ensemble classification model has outbreak many research and publication in the data mining community discussing how to combine models or model prediction with reduction in the error that results. When we ensemble the prediction of more than one classifier, more accurate and robust models are generated. We have convention that bagging, boosting with neural network etc. are the most popular method of combining different models and are realized in many data mining software but there are variation and alternative to bagging and boosting. This survey paper will give insight into various newly proposed ensemble classification models based on different methodologies.