• DocumentCode
    640912
  • Title

    Extension of iVAT to asymmetric matrices

  • Author

    Havens, Timothy C. ; Bezdek, James C. ; Leckie, Christopher ; Palaniswami, Marimuthu

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Michigan Technol. Univ., Houghton, MI, USA
  • fYear
    2013
  • fDate
    7-10 July 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The iVAT algorithm reorders (symmetric) dissimilarity data so that an image of the data may reveal cluster substructure. This paper extends the method so that it can handle asymmetric dissimilarity data. The extension is based on replacing the asymmetric input data with its unique least-squared error approximation by a symmetric matrix. Examples are given to illustrate the new method, called asymmetric iVAT (asiVAT).
  • Keywords
    data handling; least squares approximations; matrix algebra; asiVAT; asymmetric dissimilarity data handling; asymmetric iVAT; asymmetric matrices; cluster substructure; iVAT algorithm; least-squared error approximation; symmetric data; symmetric matrix; Clustering algorithms; Contamination; Iris; Symmetric matrices; Tin; Vectors; Visualization; VAT; asymmetric matrices; iVAT; reordered dissimilarity images; visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2013 IEEE International Conference on
  • Conference_Location
    Hyderabad
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4799-0020-6
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2013.6622300
  • Filename
    6622300
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=640912