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Autor(en): 
  • Xu Rui
  • Wunsch Don
  • Clustering 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  November 2008  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Applied mathematics / automatic classification / botryology / Cluster / cluster data / Cluster Validation / clustering / computer science
    ISBN:  9780470276808 
    EAN-Code: 
    9780470276808 
    Verlag:  Wiley 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  IEEE Press Series on Computational Intelligence  
    Dimensionen:  H 243 mm / B 165 mm / D 27 mm 
    Gewicht:  708 gr 
    Seiten:  368 
    Illustration:  Charts: 85 B&W, 0 Color; Photos: 15 B&W, 0 Color; Tables: 10 B&W, 0 Color; Graphs: 55 B&W, 0 Color 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The only thorough, comprehensive book available on clustering From two of the best-known experts in the field comes the first book to take a truly comprehensive look at clustering. The book begins with a complete introduction to cluster analysis in which readers will become familiarized with classification and clustering; definition of clusters; clustering applications; and the literature of clustering algorithms. The authors then present a detailed outline of the book's content and go on to explore: * Proximity measures * Hierarchical clustering * Partition clustering * Neural network-based clustering * Kernel-based clustering * Sequential data clustering * Large-scale data clustering * Data visualization and high-dimensional data clustering * Cluster validation The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds. The book is intended as a professional reference for computer scientists and applied mathematicians working with data-intensive applications, and for computational intelligence researchers who use clustering for feature selection or data reduction. Its selection of homework exercises also makes it appropriate as a textbook for graduate students in mathematics, science, and engineering.

      



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