Sensitivity to Evidence in Probabilistic Networks

dc.rights.license	CC-BY-NC-ND
dc.contributor.advisor	Gaag, L. C. van der
dc.contributor.advisor	Renooij, S.
dc.contributor.author	Meekes, M.
dc.date.accessioned	2013-11-19T18:01:11Z
dc.date.available	2013-11-19
dc.date.available	2013-11-19T18:01:11Z
dc.date.issued	2013
dc.identifier.uri	https://studenttheses.uu.nl/handle/20.500.12932/15330
dc.description.abstract	The probabilistic network framework is an approach to apply probability theory to reasoning with uncertainty in knowledge-based systems. Whereas researchers have studied the properties of parameter sensitivity analysis for probabilistic networks to quite some extent, evidence sensitivity analysis has received far less attention. The aim of my thesis is to present new, fundamental insights on sensitivity to evidence in probabilistic networks.
dc.description.sponsorship	Utrecht University
dc.format.extent	612620 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.title	Sensitivity to Evidence in Probabilistic Networks
dc.type.content	Master Thesis
dc.rights.accessrights	Open Access
dc.subject.keywords	bayesian networks, probabilistic networks, sensitivity analysis, probabilistic network pruning, evidence sensitivity set, evidence sensitivity function
dc.subject.courseuu	Computing Science