Most classification problems associate a single class to each example or instance. However, there are many classification tasks where each instance can be associated with one or more classes. This group of problems represents an area known as multi-label classification. One typical example of multi-label classification problems is the classification of documents, where each document can be assigned to more than one class. This tutorial presents the most frequently used techniques to deal with these problems in a pedagogical manner, with examples illustrating the main techniques and proposing a taxonomy of multi-label techniques that highlights the similarities and differences between these techniques. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
de Carvalho, A. C. P. L. F., & Freitas, A. A. (2009). A tutorial on multi-label classification techniques. Studies in Computational Intelligence, 205, 177–195. https://doi.org/10.1007/978-3-642-01536-6_8
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