• DocumentCode
    918200
  • Title

    Error probability in dependent pattern classification (Corresp.)

  • Author

    Forsyth, John J.

  • Volume
    18
  • Issue
    5
  • fYear
    1972
  • fDate
    9/1/1972 12:00:00 AM
  • Firstpage
    678
  • Lastpage
    680
  • Abstract
    This correspondence derives an upper bound on the probability of error of the m -class Bayes decision process when the patterns observed have first-order stochastic dependence. The bound is derived by applying an information-theoretic approach in which both the equivocation and the Bhattacharyya coefficient play a role.
  • Keywords
    Bayes procedures; Pattern classification; Computer science; Entropy; Error probability; Machine learning; Mutual information; Pattern classification; Pattern recognition; Random variables; Stochastic processes; Upper bound;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.1972.1054883
  • Filename
    1054883
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=918200