期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：1
出版社：S.S. Mishra
摘要：Data classification plays important role in the field of data mining. The increasing rate of data diversity and size decrease the performance and efficiency of classifier. The decreasing performance o f classifier compromised with unvoted data of classifier. Now the merging of two or more classifier for better prediction and voting of data are used, such techniques are called Ensemble classifier. Initially the resembling of classifier used bogging and boosting technique and later on used random Forest technique. The process of classifier improved the performance and efficiency of data classification. But feature selection process of ensemble technique has important part of classifier. In this paper we present various technique of ensemble classifier for binary classification as well as multi-class classification.
关键词：ensemble classifier; Bogging; boosting; Random forest; majority Voting
