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Knowledge-based clustering [electronic resource] : from data to information granules / Witold Pedrycz.

By: Pedrycz, Witold, 1953-.
Material type: TextTextPublisher: Hoboken, N.J. : Wiley, c2005Description: 1 online resource (xvii, 316 p.) : ill.ISBN: 0471708593 (electronic bk.); 9780471708599 (electronic bk.); 0471708607 (electronic bk.); 9780471708605 (electronic bk.).Subject(s): Soft computing | Granular computing | Fuzzy systems | Informatique douce | Calcul granulaire | Syst�emes flous | COMPUTERS -- Enterprise Applications -- Business Intelligence Tools | COMPUTERS -- Intelligence (AI) & Semantics | Electrical and Electronics Engineering | FACsci | ER Internet Book Full textGenre/Form: Electronic books.Additional physical formats: Print version:: Knowledge-based clustering.DDC classification: 006.3 Online resources: EBSCOhost
Contents:
1. Clustering and fuzzy clustering -- 2. Computing with granular information : fuzzy sets and fuzzy relations -- 3. Logic-oriented neurocomputing -- 4. Conditional fuzzy clustering -- 5. Clustering with partial supervision -- 6. Principles of knowledge-based guidance in fuzzy clustering -- 7. Collaborative clustering -- 8. Directional clustering -- 9. Fuzzy relational clustering -- 10. Fuzzy clustering of heterogeneous patterns -- 11. Hyperbox models of granular data : the Tchebyschev FCM -- 12. Genetic tolerance fuzzy neural networks -- 13. Granular prototyping -- 14. Granular mappings -- 15. Linguistic modeling.
Review: "This is must reading for researchers, professionals, and students interested in clustering, fuzzy clustering, unsupervised learning, neural networks, fuzzy sets, pattern recognition, and system modeling. With the author's emphasis on mastering the prerequisites, coupled with carefully constructed practical examples and experiments, readers will be well on their way to becoming knowledge-based clustering experts themselves."--Jacket.
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"A Wiley-Interscience publication."

Includes bibliographical references (p. 297-313) and index.

1. Clustering and fuzzy clustering -- 2. Computing with granular information : fuzzy sets and fuzzy relations -- 3. Logic-oriented neurocomputing -- 4. Conditional fuzzy clustering -- 5. Clustering with partial supervision -- 6. Principles of knowledge-based guidance in fuzzy clustering -- 7. Collaborative clustering -- 8. Directional clustering -- 9. Fuzzy relational clustering -- 10. Fuzzy clustering of heterogeneous patterns -- 11. Hyperbox models of granular data : the Tchebyschev FCM -- 12. Genetic tolerance fuzzy neural networks -- 13. Granular prototyping -- 14. Granular mappings -- 15. Linguistic modeling.

"This is must reading for researchers, professionals, and students interested in clustering, fuzzy clustering, unsupervised learning, neural networks, fuzzy sets, pattern recognition, and system modeling. With the author's emphasis on mastering the prerequisites, coupled with carefully constructed practical examples and experiments, readers will be well on their way to becoming knowledge-based clustering experts themselves."--Jacket.

Description based on print version record.

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Knowledge-based clustering by Pedrycz, Witold, ©2005
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