Extremely Randomized CNets for Multi-label Classification

XVIIth International Conference of the Italian Association for Artificial Intelligence 2018 Teresa M.A. BasileNicola Di MauroFloriana Esposito

Multi-label classification (MLC) is a challenging task in ma-chine learning consisting in the prediction of multiple labels associated with a single instance. Promising approaches for MLC are those able to capture label dependencies by learning a single probabilistic model—differently from other competitive approaches requiring to learn many models... (read more)

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