Rough Set Methods and Applications New Developments in Knowledge Discovery in Information Systems /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Polkowski, Lech (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Tsumoto, Shusaku (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Lin, Tsau Y. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2000.
• Έκδοση: 1st ed. 2000.
• Σειρά: Studies in Fuzziness and Soft Computing, 56
• Θέματα: Artificial intelligence.; Mathematical logic.; Information technology.; Business-Data processing.; Artificial Intelligence.; Mathematical Logic and Formal Languages.; IT in Business.
• Φυσική περιγραφή: X, 683 p. online resource.
• ISBN: 9783790818406
• ISSN: 1434-9922 ;
• DOI: 10.1007/978-3-7908-1840-6

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.