Non-classical Imbalanced Classification Problems

Abstract

Most of the research in class imbalance are carried out in standard (binary or multi-class) classification problems. However, in recent years, researchers have addressed new classification frameworks beyond standard classification in different aspects. Several variations of class imbalance problem appear within these frameworks. This chapter reviews the problem of class imbalance for a spectrum of these non-classical problems. Throughout this chapter, in Sect. 12.2 some research studies related to class imbalance where only partially labeled data is available (SSL) are reviewed. Then, in Sect. 12.3 the problem of label imbalance in problems where more than a label can be associated to an instance (Multilabel Learning) is discussed. In Sect. 12.4 the problem of class imbalance when labels are associated to bags of instances, rather than individually (Multi-instance Learning), is analyzed. Next, Sect. 12.5 refers to the problem of class imbalance when there exists an ordinal relation among classes (Ordinal Classification). Finally, in Sect. 12.6 some concluding remarks are presented.