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  • × author_ss:"Lingras, P.J."
  • × theme_ss:"Data Mining"
  • × year_i:[1990 TO 2000}
  1. Lingras, P.J.; Yao, Y.Y.: Data mining using extensions of the rough set model (1998) 0.00
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    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
    Type
    a