• DocumentCode
    3539481
  • Title

    Bayesian network structure learning for discrete and continuous variables

  • Author

    Suzuki, Joe

  • Author_Institution
    Dept. of Math., Osaka Univ., Suita, Japan
  • fYear
    2012
  • fDate
    14-15 Aug. 2012
  • Firstpage
    141
  • Lastpage
    144
  • Abstract
    We consider estimation of Bayesian network structures given a finite number of examples when both discrete and continuous random variables are present in a Bayesian network.
  • Keywords
    Bayes methods; belief networks; learning (artificial intelligence); random processes; Bayesian network structure estimation; Bayesian network structure learning; continuous random variable; discrete variable; Artificial neural networks; Bayesian methods; Cognition; Density functional theory; Estimation; Mathematical model; Random variables; Bayesian networks; discrete/continuous variables; model selection; structure estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Uncertainty Reasoning and Knowledge Engineering (URKE), 2012 2nd International Conference on
  • Conference_Location
    Jalarta
  • Print_ISBN
    978-1-4673-1459-6
  • Type

    conf

  • DOI
    10.1109/URKE.2012.6319529
  • Filename
    6319529
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3539481