Rough sets approximations in data tables containing missing values

Rough sets are applied to data tables containing missing values. A new method, called a method of possible equivalence classes, is proposed. Discernibility as well as indiscernibility of missing values is considered in order to improve previous results. A family of possible equivalence classes is obtained, in which each possible equivalence class has the possibility that it is an actual one. By using the family of possible equivalence classes, we derive lower and upper approximations. The lower and the upper approximations coincide with ones obtained from methods of possible worlds.