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Knowledge-based clustering : from data to information granules

Author: Witold Pedrycz
Publisher: Hoboken, N.J. : Wiley, ©2005.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
"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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Pedrycz, Witold, 1953-
Knowledge-based clustering.
Hoboken, N.J. : Wiley, ©2005
(DLC) 2004054805
(OCoLC)55877252
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Witold Pedrycz
ISBN: 0471708593 9780471708599 0471708607 9780471708605
OCLC Number: 609260264
Reproduction Notes: Electronic reproduction. [S.l.] : HathiTrust Digital Library, 2010. MiAaHDL
Description: 1 online resource (xvii, 316 pages) : illustrations
Details: Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002.
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.
Responsibility: Witold Pedrycz.
More information:

Abstract:

"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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