A Survey on Unbalanced Classification: How Can Evolutionary Computation Help?
这篇综述梳理了进化计算在不平衡分类中的应用，总结其贡献、最新进展和局限，并列举实际应用和未来研究方向，适合关注不平衡分类或进化计算的学者快速了解领域全貌。
Unbalanced classification is an essential machine learning task, which has attracted widespread attention from both the academic and industrial communities due mainly to its broad applications. Evolutionary computation (EC) has contributed greatly to unbalanced classification. However, to the best of our knowledge, there have not been any comprehensive investigations on the strengths and weaknesses of alternative EC methods in addressing various challenging problems in unbalanced classification. This article reviews the literature which utilize EC techniques for unbalanced classification, with the aim of revealing the contributions of EC to unbalanced classification, providing an overview of recent advances, and identifying limitations of existing works. In addition, we present a series of real-world applications, and identify open challenges as well as possible research directions for the future.