1 code implementation • 2 Dec 2021 • Kecia G. Moura, Ricardo B. C. Prudêncio, George D. C. Cavalcanti
This work investigates the performance of ensemble noise detection under two different noise models: the Noisy at Random (NAR), in which the probability of label noise depends on the instance class, in comparison to the Noisy Completely at Random model, in which the probability of label noise is entirely independent.
