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Inhibitory Rules in Data Analysis - A Rough Set Approach (Hardcover, 2009 ed.) Loot Price: R2,789
Discovery Miles 27 890
Inhibitory Rules in Data Analysis - A Rough Set Approach (Hardcover, 2009 ed.): Pawel Delimata, Mikhail Ju Moshkov, Zbigniew...

Inhibitory Rules in Data Analysis - A Rough Set Approach (Hardcover, 2009 ed.)

Pawel Delimata, Mikhail Ju Moshkov, Zbigniew Suraj

Series: Studies in Computational Intelligence, 163

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Loot Price R2,789 Discovery Miles 27 890 | Repayment Terms: R261 pm x 12*

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This monograph is devoted to theoretical and experimental study of inhibitory decision and association rules. Inhibitory rules contain on the right-hand side a relation of the kind "attribut = value." The use of inhibitory rules instead of deterministic (standard) ones allows us to describe more completely infor- tion encoded in decision or information systems and to design classi?ers of high quality. The mostimportantfeatureofthis monographis thatit includesanadvanced mathematical analysis of problems on inhibitory rules. We consider algorithms for construction of inhibitory rules, bounds on minimal complexity of inhibitory rules, and algorithms for construction of the set of all minimal inhibitory rules. We also discuss results of experiments with standard and lazy classi?ers based on inhibitory rules. These results show that inhibitory decision and association rules can be used in data mining and knowledge discovery both for knowledge representation and for prediction. Inhibitory rules can be also used under the analysis and design of concurrent systems. The results obtained in the monograph can be useful for researchers in such areas as machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory, and logical analysis of data (LAD). The monograph can be used under the creation of courses for graduate students and for Ph.D. studies. TheauthorsofthisbookextendanexpressionofgratitudetoProfessorJanusz Kacprzyk, to Dr. Thomas Ditzinger and to the Studies in Computational Int- ligence sta? at Springer for their support in making this book possible.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Studies in Computational Intelligence, 163
Release date: October 2008
First published: 2009
Authors: Pawel Delimata • Mikhail Ju Moshkov • Zbigniew Suraj
Dimensions: 235 x 155 x 9mm (L x W x T)
Format: Hardcover
Pages: 116
Edition: 2009 ed.
ISBN-13: 978-3-540-85637-5
Categories: Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers
Books > Professional & Technical > Technology: general issues > Technical design > Computer aided design (CAD)
Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN: 3-540-85637-4
Barcode: 9783540856375

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