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OverviewRough 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. Full Product DetailsAuthor: Lech Polkowski , Shusaku Tsumoto , Tsau Y. LinPublisher: Physica Verlag,Wien Imprint: Physica Verlag,Wien Edition: Softcover reprint of the original 1st ed. 2000 Volume: 56 Dimensions: Width: 15.50cm , Height: 3.50cm , Length: 23.50cm Weight: 1.050kg ISBN: 9783662003763ISBN 10: 3662003767 Pages: 683 Publication Date: 16 November 2000 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |