Document (#20911)

Author

Lingras, P.J.
Yao, Y.Y.

Title

Data mining using extensions of the rough set model

Source

Journal of the American Society for Information Science. 49(1998) no.5, S.415-422

Year

1998

Abstract

Examines basic issues of data mining using the theory of rough sets, which is a recent proposal for generalizing classical set theory. The Pawlak rough set model is based on the concept of an equivalence relation. A generalized rough set model need not be based on equivalence relation axioms. The Pawlak rough set model has been used for deriving deterministic as well as probabilistic rules froma complete database. Demonstrates that a generalised rough set model can be used for generating rules from incomplete databases. These rules are based on plausability functions proposed by Shafer. Discusses the importance of rule extraction from incomplete databases in data mining

Footnote

Contribution to a special issue devoted to knowledge discovery and data mining

Theme

Data Mining

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