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Autor(en): 
  • Kaufman
  • Rousseeuw
  • Finding Groups In Data P 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  März 2005  
    Genre:  Schulbücher 
     
    Mathematics / MATHEMATICS / Probability & Statistics / General
    ISBN:  9780471735786 
    EAN-Code: 
    9780471735786 
    Verlag:  John Wiley & Sons 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Wiley Series in Probability and Statistics  
    Dimensionen:  H 234 mm / B 156 mm / D 20 mm 
    Gewicht:  559 gr 
    Seiten:  368 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

    "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well."
    -Mathematical Reviews

    "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature."
    -Journal of Classification

    "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study."
    -Technometrics

    An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book discusses various types of data, including interval-scaled and binary variables as well as similarity data, and explains how these can be transformed prior to clustering.

      



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