Innovations in fuzzy clustering : theory and applications /

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Bibliographic Details
Author / Creator:	Sato-Ilic, Mika.
Imprint:	Berlin ; New York : Springer, 2006.
Description:	1 online resource (xiii, 152 pages) : figure, table.
Language:	English
Series:	Studies in fuzziness and soft computing ; v. 205 Studies in fuzziness and soft computing ; v. 205.
Subject:	Fuzzy sets. Fuzzy logic. Fuzzy mathematics. Data mining. Soft computing. Data mining. Fuzzy logic. Fuzzy mathematics. Fuzzy sets. Soft computing.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11069012

Hidden Bibliographic Details
ISBN:	9783540343578 3540343571 3540343563 9783540343561 1280657200 9781280657207
Notes:	Includes bibliographical references and index. Print version record.
Summary:	There is a great interest in clustering techniques due to the vast amount of data generated in every field including business, health, science, engineering, aerospace, management and so on. It is essential to extract useful information from the data. Clustering techniques are widely used in pattern recognition and related applications. The research monograph presents the most recent advances in fuzzy clustering techniques and their applications. The following contents are included: Introduction to Fuzzy Clustering Fuzzy Clustering based Principal Component Analysis Fuzzy Clustering based Regression Analysis Kernel based Fuzzy Clustering Evaluation of Fuzzy Clustering Self-Organized Fuzzy Clustering This book is directed to the computer scientists, engineers, scientists, professors and students of engineering, science, computer science, business, management, avionics and related disciplines.
Other form:	Print version: Sato-Ilic, Mika. Innovations in fuzzy clustering. Berlin ; New York : Springer, 2006 3540343563 9783540343561

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