Ensemble Learning Method for Class Overlapping Problem

Class overlapping and ensemble learning method have long been regarded as one of the toughest yet pervasive problems in data mining. The effect of ensemble learning method and class overlapping are with few researches. To meet this critical challenge, in this paper, we pay a systematic study on the different classifier performance in class overlapping problem and propose a new Ensemble Learning Method based on Naive Bayes for class overlapping problem (ELM-NB). ELM-NB uses NB to find class overlapping region and use this region and non-overlapping region in ensemble learning model. Experimental results on selected data sets prove that ELM-NB can have good classification performance for class overlapping problem.