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Innovations in Fuzzy Clustering [electronic resource] : Theory and Applications / by Mika Sato-Ilic, Lakhmi C. Jain.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Studies in Fuzziness and Soft Computing ; 205 | Studies in Fuzziness and Soft Computing ; 205Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006Descripción: XIII, 151 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9783540343578
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 519 23
Clasificación LoC:
  • TA329-348
  • TA640-643
Recursos en línea:
Contenidos:
Springer eBooksResumen: 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.
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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.

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.

ZDB-2-ENG

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