On selecting the optimal Bayesian Network model construction approach

Ifeyinwa E. Achumba, Djamel Azzi, Sebastian Bersch, Ifeanyi Ezebili

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review


    The construction of a Bayesian Network (BN) model entails two major tasks: realization of the model structure, and the calibration (parameterization) of the model. BN model constructors, ab initio, relied only on domain experts to define both the structure and parameters of a model. Currently, algorithms exist to construct BN models from data. Consequently, there are three BN model construction techniques: total expert-centred, total data-centred, and semi data-centred. We empirically investigated which of these approaches is the optimal approach for the construction of a BN model for our intended application. The investigation yielded some interesting themes.
    Original languageEnglish
    Title of host publicationProceedings of the World Congress on Engineering 2012. Vol 2
    Place of PublicationHong Kong
    PublisherNewswood Limited
    Number of pages2065
    ISBN (Print)9789881925213
    Publication statusPublished - 4 Jul 2012
    EventWorld Congress on Engineering - London
    Duration: 4 Jul 20126 Jul 2012

    Publication series

    NameLecture notes in engineering and computer science
    PublisherNewswood Limited


    ConferenceWorld Congress on Engineering


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