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Erschienen in:
2000 | OriginalPaper | Buchkapitel
Data Mining in Incomplete Information Systems from Rough Set Perspective
verfasst von : Marzena Kryszkiewicz, Henryk Rybiński
Erschienen in: Rough Set Methods and Applications
Verlag: Physica-Verlag HD
Enthalten in: Professional Book Archive
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Mining rules is of a particular interest in Rough Sets applications. Inconsistency and incompleteness issues in the information system are considered. Algorithms, which mine in very large incomplete information systems for certain, possible and generalized decision rules are presented. The algorithms are based on efficient data mining techniques devised for association rules generation from large data bases. The algorithms are capable to generate rules both supported by the system directly and hypothetical. The rules generated from incomplete system are not contradictory with any plausible extension of the system.