On the Covering Probabilistic Rough Set Models and Its Bayes Desicions

The classical probabilistic rough sets are defined based on the equivalent relations of the universe. However, the equivalent relation of the universe is often difficult to obtain, furthermore, it has some restrictions in the real applications. This paper devote to the study of the covering probabilistic rough set models in order to solve the problems proposed above: the covering probabilistic rough set models are presented, and as an application, a Bayes decision procedure in medical diagnosis is discussed.