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Exploring Bayesian Belief Networks Using Netica®

  • Zhifang Ni
  • Lawrence D. Phillips
  • George B. Hanna
Chapter

Abstract

Bayesian belief networks (BBNs) are graphical tools for reasoning with uncertainties (see Chap. 7). They can be used to combine expert knowledge with hard data and making sense of uncertain evidence. The computation of Bayesian inference is complex. In this chapter, we provide a step-to-step guide of how to construct and use Bayesian networks by using Netica software.

Keywords

Mutual Information Bayesian Network Target Node Uncertain Variable Bayesian Belief Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Hanna GB, Phillips LD, Priest OH, Ni Z. Developing guidelines for the safe verification of feeding tube position - a decision analysis approach. A report for the National Health Service (NHS) Patient Safety Research Portfolio; 2010.Google Scholar
  2. 2.
    Norsys_Software_Corp. Norsys Tutorial. Norsys Software Corporation 1995-2010:2010.Google Scholar

Copyright information

© Springer London 2011

Authors and Affiliations

  • Zhifang Ni
    • 1
  • Lawrence D. Phillips
  • George B. Hanna
  1. 1.Department of Surgery and CancerImperial College LondonLondonUK

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