Decision Making in Incomplete Information System Based on Decision-Theoretic Rough Sets

In complete information system, the universe is partitioned with equivalence relation. Given a concept we get a pair of approximations of the concept using rough set theory. An incomplete information table can be expressed as a family of complete information tables. The universe is partitioned by equivalence relation for each of complete information table. The probability of each object in universe belonging to the concept can be calculated. A decision rule is derived using the probability instead of conditional probability in decision-theoretic rough sets. At last, the unverse is divided into three regions according to the probability.

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