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Optimization of data resampling through GA for the classification of imbalanced datasets
2019
IJAIN (International Journal of Advances in Intelligent Informatics)
Classification of imbalanced datasets is a critical problem in numerous contexts. In these applications, standard methods are not able to satisfactorily detect rare patterns due to multiple factors that bias the classifiers toward the frequent class. This paper overview a novel family of methods for the resampling of an imbalanced dataset in order to maximize the performance of arbitrary data-driven classifiers. The presented approaches exploit genetic algorithms (GA) for the optimization of
doi:10.26555/ijain.v5i3.409
fatcat:bmdt43ln4jdyrg32ksgk6dnwqu