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Titlebook: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis; Uffe B. Kjærulff,Anders L. Madsen Book 20081st edition Spr

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Uffe B. Kjærulff,Anders L. MadsenComprehensive introduction to probabilistic networks.Written specifically for practitioners of applied artificial intelligence.Complete guide to understand, construct, and analyze probabilistic networ
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Michael St.Pierre,Gesine HofingerIn this chapter we introduce probabilistic networks for reasoning and decision making under uncertainty.
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Johannes Bauer Ph.D.,Christian Harteis Ph.D.A probabilistic network can be constructed manually, (semi-)automatically from data, or through a combination of a manual and a data driven process. In this chapter we will focus exclusively on the manual approach. See Chapter 8 for approaches involving data.
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Probabilistic NetworksIn this chapter we introduce probabilistic networks for reasoning and decision making under uncertainty.
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Eliciting the ModelA probabilistic network can be constructed manually, (semi-)automatically from data, or through a combination of a manual and a data driven process. In this chapter we will focus exclusively on the manual approach. See Chapter 8 for approaches involving data.
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Modeling TechniquesIn this chapter we introduce a set of modeling methods and techniques for simplifying the specification of a probabilistic network.
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Data-Driven ModelingIn this chapter we introduce data-driven modeling as the task of inducing a Bayesian network by fusion of (observed) data and domain expert knowledge.
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