The advancement in multi-label and label distribution learning

Multi label learning and label distribution learning as emerging machine learning paradigms have developed rapidly in recent years. This article aims to review the research progress in this field, focusing on the algorithms and applications of multi label learning and label distribution learning. Firstly, the basic concepts and related backgrounds of multi label learning and label distribution learning were introduced, and their differences and connections with traditional single label learning were explained. Secondly, the research progress on multi label learning, multi label classification, multi label feature selection, and label distribution learning were introduced separately. Finally, this article summarizes and looks forward to the future development directions of multi label learning and label distribution learning.