Fuzzy Neighborhood-Based Clustering | with Recent Theory and Applications. Este artículo no está disponible.
Idioma: inglés
Editorial: LAP LAMBERT Academic Publishing, 2011
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Fuzzy Neighborhood-Based Clustering | with Recent Theory and Applications | Gozde Ulutagay (u. a.) | Taschenbuch | 144 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846540251 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.
N° de ref. del artículo 106736387
- Título
- Fuzzy Neighborhood-Based Clustering | with Recent Theory and Applications
- Autor
- Gozde Ulutagay (u. a.)
- Editorial
- LAP LAMBERT Academic Publishing
- Año de publicación
- 2011
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 3846540250
- ISBN 13
- 9783846540251
- Peso del artículo
- 233 gramos
- Dimensiones
- 220 x 150 x 9 mm
- Catálogos de vendedores
- Bücher
When Prof. Zadeh introduced the concept of fuzzy sets that produced the idea of allowing to have membership functions to all clusters in 1965, his main objective was to set up a formal framework for the representation and management of vague and uncertain data. Today, besides the possibility to handle uncertainties within data, fuzzy data analysis allows us to learn knowledge-based representation of the information subsistent in the data. When writing this monograph, our intention was not only to give a self-contained and methodological introduction to fuzzy neighborhood-based cluster analysis with its areas of applications, but also to provide a systematic description of novel clustering methods. We think that the book will be useful for engineers, statisticians, and computer scientists in both teaching and research, who deal with data analysis, pattern recognition, bioinformatics, or who take into consideration the application of fuzzy neighborhood-based clustering methods in their area of work.
“Sinopsis” puede pertenecer a otra edición de este título.
Reseña del editor
When Prof. Zadeh introduced the concept of fuzzy sets that produced the idea of allowing to have membership functions to all clusters in 1965, his main objective was to set up a formal framework for the representation and management of vague and uncertain data. Today, besides the possibility to handle uncertainties within data, fuzzy data analysis allows us to learn knowledge-based representation of the information subsistent in the data. When writing this monograph, our intention was not only to give a self-contained and methodological introduction to fuzzy neighborhood-based cluster analysis with its areas of applications, but also to provide a systematic description of novel clustering methods. We think that the book will be useful for engineers, statisticians, and computer scientists in both teaching and research, who deal with data analysis, pattern recognition, bioinformatics, or who take into consideration the application of fuzzy neighborhood-based clustering methods in their area of work.
“Acerca de” puede pertenecer a otra edición de este título.