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Autor(en): 
  • S. Sumathi
  • S.N. Sivanandam
  • Introduction to Data Mining and its Applications 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  August 2016  
    Genre:  EDV / Informatik 
     
    Applied mathematics / Artificial Intelligence / B / Data Mining / Data Mining and Knowledge Discovery / engineering / Engineering mathematics / Expert systems / knowledge-based systems
    ISBN:  9783662500804 
    EAN-Code: 
    9783662500804 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #29 - Studies in Computational Intelligence  
    Dimensionen:  H 297 mm / B 210 mm / D  
    Gewicht:  2194 gr 
    Seiten:  828 
    Illustration:  XXII, 828 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, AI, machine learning, NN, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. This book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. Since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. It is also written for technical managers and executives as well as for technologists interested in learning about data mining.

      



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