Handling Missing Values in terms of Rough Sets

Rough sets are applied to data tables containing missing values. Discernibility and indiscernibility of missing values are considered simultaneously. A family of possible equivalence classes is obtained, in which each equivalence class has the possibility that it is an actual one. By using the family of possible equivalence classes, we can derive lower and upper approximations, even if the approximations are not obtained by previous methods. Furthermore, the lower and upper approximations coincide with ones obtained from methods of possible worlds.

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