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.
| ISBN: | 9783662003763 |
| Publication date: | 8th October 2012 |
| Author: | Lech Polkowski, Shusaku Tsumoto, Tsau Y Lin |
| Publisher: | Physica an imprint of Physica-Verlag HD |
| Format: | Paperback |
| Pagination: | 683 pages |
| Series: | Studies in Fuzziness and Soft Computing |
| Genres: |
Artificial intelligence Mathematical theory of computation Business mathematics and systems Business applications |
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.
Rough Set Methods and Applications features in the following genres: Artificial intelligence, Mathematical theory of computation, Business mathematics and systems, Business applications
Paperback. Not Available.
Rough Set Methods and Applications was written by Lech Polkowski, Shusaku Tsumoto, Tsau Y Lin and published by Physica an imprint of Physica-Verlag HD
Rough Set Methods and Applications has 683 pages
Yes it is part of Studies in Fuzziness and Soft Computing series