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Construction of Bayesian Models

Construction of Bayesian Models

Ben Kei Daniel
Copyright: © 2009 |Pages: 12
ISBN13: 9781605666631|ISBN10: 1605666637|ISBN13 Softcover: 9781616924799|EISBN13: 9781605666648
DOI: 10.4018/978-1-60566-663-1.ch011
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MLA

Ben Daniel. "Construction of Bayesian Models." Social Capital Modeling in Virtual Communities: Bayesian Belief Network Approaches, IGI Global, 2009, pp.195-206. https://doi.org/10.4018/978-1-60566-663-1.ch011

APA

B. Daniel (2009). Construction of Bayesian Models. IGI Global. https://doi.org/10.4018/978-1-60566-663-1.ch011

Chicago

Ben Daniel. "Construction of Bayesian Models." In Social Capital Modeling in Virtual Communities: Bayesian Belief Network Approaches. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-663-1.ch011

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Abstract

Bayesian Belief Networks (BBNs) are increasingly used for understanding different problems in many domains. Though BBN techniques are elegant ways of capturing uncertainties, knowledge engineering effort required to create and initialize a network has prevented many researchers from using them. Even though the structure of the network and its conditional and initial probabilities could be learned from data, data is not always available and/or too costly to obtain. Furthermore, current algorithms used to learn relationships among variables, initial and conditional probabilities from data are often complex and cumbersome to employ. A qualitative Bayesian network approach was introduced to address some of the difficulties in building models that mainly depend on quantitative data. Building BBN models from quantitative data presupposes that relationships among variables or concepts of interests are known and can be correlated, causally related or they can relate to each other independently. The interdependency or relationships among the variables enable more reliable inferences which in turn help in making informed decisions about results of the model.This Chapter presents qualitative techniques and algorithms for creating Bayesian belief network models. It simplifies the construction of Bayesian models in few steps. The goal of the Chapter is to introduce the reader to the basic principles underlying the constructions of Bayesian Belief Network.

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