Extremely Randomized CNets for Multi-label Classification

4 code implementations • XVIIth International Conference of the Italian Association for Artificial Intelligence 2018 • Teresa M.A. Basile, Nicola Di Mauro, Floriana Esposito

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.

Classification Density Estimation +2