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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 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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Tsoumakas et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69d8fde77e3358c846d17d44 — DOI: https://doi.org/10.4018/jdwm.2007070101
Grigorios Tsoumakas
Ioannis Katakis
International Journal of Data Warehousing and Mining
Aristotle University of Thessaloniki
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