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Herausgeber: 
  • Petra Perner
  • Machine Learning and Data Mining in Pattern Recognition: 5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007, Proceedings 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2007  
    Genre:  EDV / Informatik 
     
    Artificial Intelligence / Automated Pattern Recognition / C / computer science / Computer Vision / Data Mining / Data Mining and Knowledge Discovery / Database Management
    ISBN:  9783540734987 
    EAN-Code: 
    9783540734987 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Lecture Notes in Artificial Intelligence
    #4571 - Lecture Notes in Computer Science  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  1401 gr 
    Seiten:  916 
    Illustration:  XIV, 916 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Ever wondered what the state of the art is in machine learning and data mining? Well, now you can find out. This excellent book constitutes the refereed proceedings of the 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, held in Leipzig, Germany, in July 2007. The 66 revised full papers presented together with 1 invited talk were carefully reviewed and selected from more than 250 submissions. The papers are organized in topical sections and the package features online content as well as updates. These sections cover classification; feature selection, extraction and dimensionality reduction; clustering; and support vector machines. The book also features right up-to-date information on transductive inference; association rule mining; mining spam, newsgroups and blogs; and intrusion detection and networks. Next, the papers featured cover frequent and common item set mining; mining marketing data; structural data mining; image mining; and medical, biological, and environmental data mining Lastly, the book covers the highly relevant topic of text and document mining.

      



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