Titlebook: Rough Sets and Current Trends in Computing; Third International James J. Alpigini,James F. Peters,Ning Zhong Conference proceedings 2002 S

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Database Mining on Derived Attributes Granular and Rough Computing Approachof all possible derived attributes can be generated. Then, for any data mining task, the relation can select desirable attributes by interpreting them from the universal model. The development of the universal model is based on the relation lattice, which was initiated by T. T. Lee around 1983. Howe

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Generalized Decision Algorithms, Rough Inference Rules, and Flow Graphsssociated: the ., the . and the . factors of the rule. It has been shown previously that the certainty and the coverage factors are linked by Bayes’ theorem. Bayes’ theorem has also been presented in a simple form employing the strength of decision rules. In this paper, we relax some conditions on t

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On the Structure of Rough Approximations a lattice-theoretical setting two maps which mimic the rough approximation operators and note that this setting is suitable also for other operators based on binary relations. Properties of the ordered sets of the upper and the lower approximations of the elements of an atomic Boolean lattice are s