Approximation of Classification and Measures of Uncertainty in Rough Set on Two Universal Sets
Bala Krushna Tripathy, D. P. Acharjya
Abstract
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Bala Krushna Tripathy, D. P. Acharjya
Abstract
Open-access reader
The notion of rough set captures indiscernibility of elements in a set. But, in many real life situations, an information system establishes the relation between different universes. This gave the extension of rough set on single universal set to rough set on two universal sets. In this paper, we introduce approximation of classifications and measures of uncertainty basing upon rough set on two universal sets employing the knowledge due to binary relations.
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The notion of rough set captures indiscernibility of elements in a set. But, in many real life situations, an information system establishes the relation between different universes. This gave the extension of rough set on single universal set to rough set on two universal sets. In this paper, we introduce approximation of classifications and measures of uncertainty basing upon rough set on two universal sets employing the knowledge due to binary relations.
Key concepts: Rough set, Binary relation, Extension (predicate logic), Universal set, Dominance-based rough set approach, Set (abstract data type), Relation (database), Mathematics