Axiomatic Systems of Generalized Rough Sets

Rough set theory was proposed by Pawlak to deal with the vagueness and granularity in information systems that are characterized by insufficient, inconsistent, and incomplete data. Its successful applications draw attentions from researchers in areas such as artificial intelligence, computational intelligence, data mining and machine learning. The classical rough set model is based on an equivalence relation on a set, but it is extended to generalized model based on binary relations and coverings. This paper reviews and summarizes the axiomatic systems for classical rough sets, generalized rough sets based on binary relations, and generalized rough sets based on coverings

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