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Sensitivity analysis in Bayesian networks
1995For systems based on Bayesian networks, evidence is used to compute posterior probabilities for some hypotheses. Sensitivity analysis is concerned with questions on how sensitive the conclusion is to the evidence provided. After the basic definitions and an example we conclude that the heart of sensitivity analysis is to compute probabilities for the ...
Jensen, F. V. +2 more
openaire +2 more sources
2002
We present a bayesian framework for XML document retrieval. This framework allows us to consider content only and content and structure queries. We perform the retrieval task using inference in our network. Our model can adapt to a specific corpora through parameter learning.
Piwowarski, Benjamin +2 more
openaire +2 more sources
We present a bayesian framework for XML document retrieval. This framework allows us to consider content only and content and structure queries. We perform the retrieval task using inference in our network. Our model can adapt to a specific corpora through parameter learning.
Piwowarski, Benjamin +2 more
openaire +2 more sources
Bayesian learning for neural networks: an algorithmic survey
Artificial Intelligence Review, 2023Alexandros Iosifidis, Martin Magris
exaly
Discrete Bayesian Network Classifiers: A Survey
ACM Computing Surveys, 2014Concha Bielza, Pedro Larranaga
exaly
The use of Bayesian network modelling for maintenance planning in a manufacturing industry
Reliability Engineering and System Safety, 2010Zaili Yang, Jin Wang, I Jenkinson
exaly
Advantages and challenges of Bayesian networks in environmental modelling
Ecological Modelling, 2007Laura Uusitalo
exaly
Incorporation of human factors into maritime accident analysis using a data-driven Bayesian network
Reliability Engineering and System Safety, 2020Eduardo Blanco-Davis +2 more
exaly
Learning Bayesian networks: The combination of knowledge and statistical data
Machine Learning, 1995Dan Geiger
exaly

