Oscar Gabriel Reyes Pupo

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Multi-label learning has become an important area of research due to the increasing number of modern applications that contain multi-label data. The multi-label data are structured in a more complex way than single-label data. Consequently the development of techniques that allow the improvement in the performance of machine learning algorithms over(More)
In the last decade several modern applications where the examples belong to more than one label at a time have attracted the attention of research into machine learning. Several derivatives of the k-nearest neighbours classifier to deal with multi-label data have been proposed. A k-nearest neighbours classifier has a high dependency with respect to the(More)
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