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Herausgeber: 
  • Masoud Nikravesh
  • Lofti A. Zadeh
  • Steve Gunn
  • Isabelle Guyon
  • Feature Extraction: Foundations and Applications 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  April 2017  
    Genre:  EDV / Informatik 
     
    Applications of Mathematics / Applied mathematics / Artificial Intelligence / B / Computer Imaging, Vision, Pattern Recognition and Graphics / Computer Vision / Computer-Aided Design (CAD) / Computer-aided engineering / Computer-Aided Engineering (CAD, CAE) and Design / engineering / Engineering mathematics / Image Processing and Computer Vision / Mathematical and Computational Engineering / Mathematical and Computational Engineering Applications / Maths for engineers / Optical data processing
    ISBN:  9783662517710 
    EAN-Code: 
    9783662517710 
    Verlag:  Springer Berlin Heidelberg 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  #207 - Studies in Fuzziness and Soft Computing  
    Dimensionen:  H 235 mm / B 155 mm / D 43 mm 
    Gewicht:  1194 gr 
    Seiten:  804 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction.
    "This book compiles some very promising techniques, coming from an extremely smart collection of researchers, delivering their best ideas in a competitive environment."
    Trevor Hastie, Stanford University
    "Feature selection is a key technology for making sense of the high dimensional data. Isabelle Guyon et al. have done a splendid job in designing a challenging competition, and collecting the lessons learned."
    Bernhard Schoelkopf, Max Planck Institute
    "There has been until now insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons. This volume is noteworthy for the breadth of methods covered, the clarity of presentations, the unity in notation and the helpful statistical appendices."
    David G. Stork, Ricoh Innovations
    "Feature extraction finds application in biotechnology, industrial inspection, the Internet, radar, sonar, and speech recognition. This book will make a difference to the literature on machine learning."
    Simon Haykin, Mc Master University
    "This book sets a high standard as the public record of an interesting and effective competition."
    Peter Norvig, Google Inc.

      
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