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A Review on Rapidly Convergence Approach for Handling Class Imbalance Data Set?

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.3, No. 12)

Publication Date:

Authors : ; ;

Page : 181-188

Keywords : Imbalanced Classification; Resampling; Over-Sampling; Under-Sampling; Oversampling; SMOTE; Gibbs Sampling;

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In recently class imbalance problem have drawn growing because of their classification difficulties. Class imbalance problem become greatest issue in data mining. Imbalance problem occur where one of the two classes having more sample than other classes. For creating good prediction model, a well balance dataset is very important. As the application area of technology increases the size of data also increases. To handle this major issue of the imbalance class the most existing classification methods and many ensemble methods have been proposed to deal with such imbalance problems. In this paper we examine the different methods of over-sampling and under-sampling techniques to balance data.

Last modified: 2014-12-15 22:43:32