RISK ASSESSMENT AND DECISION ANALYSIS WITH BAYESIAN NETWORKS
NORMAN FENTON，MARTIN NEIL
The book has two parts. The first ten chapters of the book teach all the basics of probability and risk, and about building and using BN models, whereas the last three chapters go into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand these to build and use BN models. Although purists have argued that only by understanding the algorithms can you understand the limitations and hence build efficient BN models, we overcome this by providing pragmatic advice about model building to ensure models are built efficiently. Our approach means that the main body of the text is free of the intimidating mathematics that has been a major impediment to the more widespread use of BNs.