不平衡数据分类的研究现状

Current state of research on imbalanced data sets classification learning

不平衡数据在实际应用中广泛存在,它们已对机器学习领域构成了一个挑战,如何有效处理不平衡数据也成为目前的一个新的研究热点。综述了这一新领域的研究现状,包括该领域最新研究内容、方法及成果。

IDS（ imbalanced data sets） , arising pervasively in practical applications, have caused a huge challenge to the machine learning community and consequently attracted more and more attentions. The paper summarized the state of this relatively new research field, including its issues, methods and results.