Rough ?? Granular Computing in Knowledge Discovery
Stepaniuk, J.
Sold by Basi6 International, Irving, TX, U.S.A.
AbeBooks Seller since June 24, 2016
New - Soft cover
Condition: New
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Add to basketSold by Basi6 International, Irving, TX, U.S.A.
AbeBooks Seller since June 24, 2016
Condition: New
Quantity: 10 available
Add to basketNew. US edition. Print on demand title. Delivery takes 20-25 days. Excellent Customer Service.
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This book covers methods based on a combination of granular computing, rough sets, and knowledge discovery in data mining (KDD). The discussion of KDD foundations based on the rough set approach and granular computing feature illustrative applications.
The book "Rough-Granular Computing in Knowledge Discovery and Data Mining" written by Professor Jaroslaw Stepaniuk is dedicated to methods based on a combination of the following three closely related and rapidly growing areas: granular computing, rough sets, and knowledge discovery and data mining (KDD). In the book, the KDD foundations based on the rough set approach and granular computing are discussed together with illustrative applications. In searching for relevant patterns or in inducing (constructing) classifiers in KDD, different kinds of granules are modeled. In this modeling process, granules called approximation spaces play a special rule. Approximation spaces are defined by neighborhoods of objects and measures between sets of objects. In the book, the author underlines the importance of approximation spaces in searching for relevant patterns and other granules on dfferent levels of modeling for compound concept approximations. Calculi on such granules are used for modeling computations on granules in searching for target (sub) optimal granules and their interactions on different levels of hierarchical modeling. The methods based on the combination of granular computing, the rough and fuzzy set approaches allow for an effcient construction of the high quality approximation of compound concepts.
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