A Survey of Different Techniques to Handle An Unbalanced Dataset - Yerawar, Pooja; Pakle, Ganesh (International Journal of Computer Sciences and Engineering, 2018)
Researchers has a big challenge to handle the unbalanced data, which is an issue found in many real-world applications in engineering. Dataset is unbalanced means at least one class has very fewer examples than another class. In such dataset, examples are taken as majority class (i.e. negative) and minority class (i.e. positive). This paper contains a survey of what is mean by imbalance data, an issue with it, its challenges, examples of applications, different approaches to rebalance the data like ensemble techniques( like boosting, bagging), sampling, feature selection, algorithmic to increase the performance of classification have been proposed.