Evidence evaluation: a study of likelihoods and independence
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Publication date
2016
Editors
Antonucci, Alessandro
Corani, Giorgio
Campos, Cassio Polpo
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Part of book
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Abstract
In the context of evidence evaluation, where the probability of evidence given a certain hypothesis is considered, different pieces of evidence are often combined in a naive way by assuming conditional independence. In this paper we present a number of results that can be used to assess both the importance of a reliable likelihood-ratio estimate and the impact of neglecting dependencies among pieces of evidence for the purpose of evidence evaluation. We analytically study the effect of changes in dependencies between pieces of evidence on the likelihood ratio, and provide both theoretical and empirical bounds on the error in likelihood occasioned by assuming independences that do not hold in practice. In addition, a simple measure of influence strength between pieces of evidence is proposed.
Keywords
Evidence evaluation, independence violations, error in overall likelihood, influence measures
Citation
Renooij, S 2016, Evidence evaluation: a study of likelihoods and independence. in A Antonucci, G Corani & C P Campos (eds), Conference on Probabilistic Graphical Models, 6-9 September 2016, Lugano, Switzerland. Journal of Machine Learning Research Workshop and Conference Proceedings, vol. 52, MLResearchPress, pp. 426-473, International Conference on Probabilistic Graphical Models, Lugano, Switzerland, 6/09/16. < https://proceedings.mlr.press/v52/renooij16.html >, conference