Multi-Label Classification: An Overview

Multi-Label Classification: An Overview

Grigorios Tsoumakas (Aristotle University of Thessaloniki, Greece) and Ioannis Katakis (Aristotle University of Thessaloniki, Greece)
DOI: 10.4018/978-1-60566-058-5.ch021
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Multi-label classification methods are increasingly required by modern applications, such as protein function classification, music categorization, and semantic scene classification. This article introduces the task of multi-label classification, organizes the sparse related literature into a structured presentation and performs comparative experimental results of certain multi-label classification methods. It also contributes the definition of concepts for the quantification of the multi-label nature of a data set.

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