Multi-label classification: An overview
G Tsoumakas, I Katakis - Data Warehousing and Mining: Concepts …, 2008 - igi-global.com
Data Warehousing and Mining: Concepts, Methodologies, Tools, and …, 2008•igi-global.com
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
multilabel classification methods. It also contributes the definition of concepts for the
quantification of the multi-label nature of a data set.
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
multilabel classification methods. It also contributes the definition of concepts for the
quantification of the multi-label nature of a data set.
Abstract
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 multilabel 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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