• DocumentCode
    1943606
  • Title

    Connection between Self-Organizing Maps and Metric Multidimensional Scaling

  • Author

    Yin, Hujun

  • Author_Institution
    Univ. of Manchester, Manchester
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    1025
  • Lastpage
    1030
  • Abstract
    The self-organizing map (SOM) and some of its variants such as visualization induced SOM (ViSOM) have been seen to yield similar results to multidimensional scaling (MDS). However the exact connection has yet been established, though similar topographic mapping results have been shown in several studies. In this paper we provide a review on the SOM and its cost function and topological measures. Then we examine its relationship with MDS from their cost functions in the aspect of data visualization. The SOM is shown to produce a quantized, qualitative scaling and while the ViSOM a quantitative or metric scaling. The SOM can also be regarded as a generalized MDS to relate two metric spaces by forming a topological mapping between them. The connection between MDS and principal manifolds is also discussed.
  • Keywords
    pattern recognition; self-organising feature maps; metric multidimensional scaling; principal manifolds; self-organizing maps; topographic mapping; Brain modeling; Cerebral cortex; Cost function; Data visualization; Multidimensional systems; Nerve fibers; Neural networks; Pattern recognition; Self organizing feature maps; Surface topography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4371099
  • Filename
    4371099