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Rough set-based rule generation in tables with uncertainties, especially non-deterministic information and missing values, is investigated. The possible world semantics is employed, and both certain rules and possible rules are defined. Even though these definitions cause the computational problem, it is solved by using rough set-based concepts, and(More)
This paper reports the definability of a set of objects and rough set-based rule generation. In a standard table, we at first obtain equivalence classes with respect to an attribute set, and we solve the definability of a set X of objects. As the side effect, we obtain conditions for specifying the set X. We have extended this algorithm to tables with(More)
We have been proposing a framework Rough Non-deterministic Information Analysis (RNIA), which applies granular computing concepts to tables with incomplete information. We have recently defined an expression named division chart over an equivalence class with respect to descriptors. A division chart takes the similar role of the contingency table. In this(More)