Neighbourhood-based undersampling approach for handling imbalanced and overlapped data.
(2019)
Journal Article
VUTTIPITTAYAMONGKOL, P. and ELYAN, E. 2020. Neighbourhood-based undersampling approach for handling imbalanced and overlapped data. Information sciences [online], 509, pages 47-70. Available from: https://doi.org/10.1016/j.ins.2019.08.062
Class imbalanced datasets are common across different domains including health, security, banking and others. A typical supervised learning algorithm tends to be biased towards the majority class when dealing with imbalanced datasets. The learning ta... Read More about Neighbourhood-based undersampling approach for handling imbalanced and overlapped data..