Analyzing classification methods in multi-label tasks

Abstract

Multi-label classification methods have been increasingly used in modern application, such as music categorization, functional genomics and semantic annotation of images. This paper presents a comparative analysis of some existing multi-label classification methods applied to different domains. The main aim of this analysis is to evaluate the performance of such methods in different tasks and using different evaluation metrics. © 2010 Springer-Verlag Berlin Heidelberg.