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In dominance based rough set theory, calculation of approximations is a core step, but their computations prove expensive, particularly when we are dealing with larger databases. In the 1st step, a complete dataset needs to be traversed to compute upward and downward union of classes for each decision class. In the second step, a conventional algorithm must compare every single object and its characteristics with the whole dataset for multiple times belonging to the upward or downward union of classes. One object can belong to more than one equivalence class, so computation of the dominance relation is also repeated against each respected class. After computation of dominance relations, subset or intersection property need to be checked for computation of lower or upper approximation. We repeat the whole lengthy process for updating approximations in case of some variation in dataset.
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IEEE/ICACT20220156 Slide.09
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