An Overview of Class Imbalance Problem in Supervised Learning

Vol.1 No.3

Year: 2012

Issue: May-Jul

Title: An Overview of Class Imbalance Problem in Supervised Learning   

Author Name: Satuluri Naganjaneyulu, Mrithyumjaya Rao Kuppa   

Synopsis: 

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.