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.
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Gözde Ulutagay, PhD: Department of Industrial Engineering, Izmir University, Izmir, TURKEY. Efendi Nasibov, PhD, DrSc: Department of Computer Science, Dokuz Eylul University, Izmir, TURKEY.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 144 pp. Englisch. Bestandsnummer des Verkäufers 9783846540251
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ulutagay GozdeGoezde Ulutagay, PhD: Department of Industrial Engineering, Izmir University, Izmir, TURKEY. Efendi Nasibov, PhD, DrSc: Department of Computer Science, Dokuz Eylul University, Izmir, TURKEY.When Prof. Zadeh introduce. Bestandsnummer des Verkäufers 5497728
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9783846540251
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 144 pp. Englisch. Bestandsnummer des Verkäufers 9783846540251
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