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A Survey on Methods for Solving Data Imbalance Problem for Classification
International Journal of Computer Applications
The term "data imbalance" in classification is a well established phenomenon in which data set contains unbalanced class distributions. Dataset is called unbalanced if it contains at least one class which is presented by very few examples. A range of solutions have been proposed for the problem of data imbalance including data sampling, cost evaluation of model, bagging, boosting, Genetic Programming (GP) based methods etc. This paper presents a survey of various methods introduced bydoi:10.5120/ijca2015906677 fatcat:nslebujkgfhylks57jbmexvxoy