• DocumentCode
    3455822
  • Title

    Multivariate Data Classification Using the Distribution Mapping Exponent

  • Author

    Jirina, Marcel ; Jirina, Marcel

  • Author_Institution
    Inst. of Comput. Sci., Czech Acad. of Sci., Prague
  • fYear
    2006
  • fDate
    20-22 Aug. 2006
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    An exponent similar to the correlation dimension is introduced. This exponent is used for probability density estimation in high-dimensional spaces and for classification of multivariate data. It is also shown that this classifier exhibits significantly better behavior (classification accuracy) than other kinds of classifiers.
  • Keywords
    data handling; pattern classification; probability; correlation dimension; distribution mapping exponent; high-dimensional spaces; multivariate data classification; probability density estimation; Bayesian methods; Biomedical engineering; Computer science; Content addressable storage; Decision trees; Euclidean distance; Extraterrestrial measurements; Nearest neighbor searches; Neural networks; Probability distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Cybernetics, 2006. ICCC 2006. IEEE International Conference on
  • Conference_Location
    Budapest
  • Print_ISBN
    1-4244-0071-6
  • Electronic_ISBN
    1-4244-0072-4
  • Type

    conf

  • DOI
    10.1109/ICCCYB.2006.305707
  • Filename
    4097668
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3455822