A Flexible Software System for Learning Bayesian Networks from data

dc.contributor.advisor	Langseth, Helge	nb_NO
dc.contributor.author	Aabakken, Trond	nb_NO
dc.date.accessioned	2014-12-19T13:30:45Z
dc.date.available	2014-12-19T13:30:45Z
dc.date.created	2010-09-02	nb_NO
dc.date.issued	2007	nb_NO
dc.identifier	346708	nb_NO
dc.identifier	ntnudaim:3524	nb_NO
dc.identifier.uri	http://hdl.handle.net/11250/250089
dc.description.abstract	Bayesian networks, also referred to as belief networks, originates from the artificial intelligence field where they were used to reason about uncertain knowledge. They differ from other knowledge representation schemes as they constitute a model of the environment rather than a model of the reasoning process. Among the Bayesian networks' main assets is that they offer a sound methodology for combining (a priori) information a domain expert may have with information available in databases. In this report a software system for learning Bayesian networks from data is described.	nb_NO
dc.language	eng	nb_NO
dc.publisher	Institutt for datateknikk og informasjonsvitenskap	nb_NO
dc.subject	ntnudaim	no_NO
dc.subject	SIF2 datateknikk	no_NO
dc.subject	Intelligente systemer	no_NO
dc.title	A Flexible Software System for Learning Bayesian Networks from data	nb_NO
dc.type	Master thesis	nb_NO
dc.source.pagenumber	39	nb_NO
dc.contributor.department	Norges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for datateknikk og informasjonsvitenskap	nb_NO