Abstract
Bayesian networks (BN) are models that enable reasoning under uncertainty, thus making them very strong contenders for use by organisations in domains that are complex and where decision making takes place under uncertainty. Such models can be built from existing datasets, from expert knowledge or from a combination of both. Within the context of this book we assume that expert knowledge is the source employed to build effort estimation models. This chapter provides suggestions on how such models can be employed, where these suggestions are based on post-mortem interviews with the project managers with whom we collaborated building several effort estimation Bayesian network models.
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© 2014 Springer-Verlag Berlin Heidelberg
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Mendes, E. (2014). Ways in Which to Use Bayesian Network Models Within a Company. In: Practitioner's Knowledge Representation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54157-5_13
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DOI: https://doi.org/10.1007/978-3-642-54157-5_13
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54156-8
Online ISBN: 978-3-642-54157-5
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