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Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.
This is a digital product.
Additional ISBNs
9783662003763
Rough Set Methods and Applications: New Developments in Knowledge Discovery in Information Systems 1st Edition is written by Shusaku Tsumoto; Lech T. Polkowski; Tsau Young Lin and published by Physica. The Digital and eTextbook ISBNs for Rough Set Methods and Applications are 9783790818406, 3790818402 and the print ISBNs are 9783790813289, 3790813281. Additional ISBNs for this eTextbook include 9783662003763.

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