JCS_V1_N3_A1 Satuluri Naganjaneyulu Mrithyumjaya Rao Kuppa Journal on Communication Engineering and Systems 2277-5242 1 3 1 10 Classification, Class Imbalance, Under-sampling, Over-sampling In Data mining and Knowledge Discovery hidden and valuable knowledge from the data sources is discovered. The traditional algorithms used for knowledge discovery are bottle necked due to wide range of data sources availability. Class imbalance is a one of the problem arises due to data source which provide unequal class i.e. examples of one class in a training data set vastly outnumber examples of the other class(es). This paper presents an updated literature survey of current class imbalance learning methods for inducing models which handle imbalanced datasets efficiently. May - July 2012 Copyright © 2012 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=1886