Enhancement Encoding: A New Imbalanced Classification Approach via Encoding the Labels. (arXiv:2208.11056v1 [cs.LG])

Class imbalance, which is also called long-tailed distribution, is a common
problem in classification tasks based on machine learning. If it happens, the
minority data will be overwhelmed by the majority, which presents quite a
challenge for data science. To address the class imbalance problem, researchers
have proposed lots of methods: some people make the data set balanced (SMOTE),
some others refine the loss function (Focal Loss), and even someone has noticed
the value of labels influences class-imbalanced learning (Yang …

arxiv classification encoding labels lg