A Survey and Current Research Challenges in Multi-Label Classification Methods

Abstract

Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also done comparative analysis of multi label classification methods on the basis of theoretical study and than on the basis of simulation done on various data sets.