• DocumentCode
    905926
  • Title

    A note on learning for Gaussian properties

  • Author

    Keehn, Daniel G.

  • Volume
    11
  • Issue
    1
  • fYear
    1965
  • fDate
    1/1/1965 12:00:00 AM
  • Firstpage
    126
  • Lastpage
    132
  • Abstract
    By employing a Bayesian approach to the analysis of learning the probability distribution of property vectors, an estimation likelihood computation scheme for the general Gaussian distribution (quadratic adaptive decision surface) is shown optimum. Some results relating the number of learning samples to Type I misclassification errors are included.
  • Keywords
    Bayes procedures; Gaussian processes; Learning procedures; Pattern classification; Bayesian methods; Distributed computing; Gaussian distribution; Nominations and elections; Pattern recognition; Probability distribution; Q measurement; Space technology; Statistical analysis; Surface treatment;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.1965.1053726
  • Filename
    1053726
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=905926