Learning from class-imbalanced data: overlap-driven resampling for imbalanced data classification.
(2020)
Thesis
VUTTIPITTAYAMONGKOL, P. 2020. Learning from class-imbalanced data: overlap-driven resampling for imbalanced data classification. Robert Gordon University, PhD thesis. Hosted on OpenAIR [online]. Available from: https://openair.rgu.ac.uk
Classification of imbalanced datasets has attracted substantial research interest over the past years. This is because imbalanced datasets are common in several domains such as health, finance and security, but learning algorithms are generally not d... Read More about Learning from class-imbalanced data: overlap-driven resampling for imbalanced data classification..