Innovations in Fuzzy Clustering Theory and Applications /

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...

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Bibliographic Details
Main Authors: Sato-Ilic, Mika (Author), Jain, Lakhmi C. (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
Series:Studies in Fuzziness and Soft Computing, 205
Subjects:
Online Access:Full Text via HEAL-Link
Description
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.
Physical Description:XIII, 151 p. online resource.
ISBN:9783540343578
ISSN:1434-9922 ;