The impact of exact probabilistic learning algorithms in EDAs based on bayesian networks
| dc.contributor.author | Echegoyen Arruti, Carlos | |
| dc.contributor.author | Santana, Roberto | |
| dc.contributor.author | Lozano, José Antonio | |
| dc.contributor.author | Larrañaga, Pedro | |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.date.accessioned | 2025-01-16T14:14:18Z | |
| dc.date.available | 2025-01-16T14:14:18Z | |
| dc.date.issued | 2008 | |
| dc.date.updated | 2025-01-16T14:09:15Z | |
| dc.description.abstract | This paper discusses exact learning of Bayesian networks in estimation of distribution algorithms. The estimation of Bayesian network algorithm (EBNA) is used to analyze the impact of learning the optimal (exact) structure in the search. By applying recently introduced methods that allow learning optimal Bayesian networks, we investigate two important issues in EDAs. First, we analyze the question of whether learning more accurate (exact) models of the dependencies implies a better performance of EDAs. Secondly, we are able to study the way in which the problem structure is translated into the probabilistic model when exact learning is accomplished. The results obtained reveal that the quality of the problem information captured by the probability model can improve when the accuracy of the learning algorithm employed is increased. However, improvements in model accuracy do not always imply a more efficient search. | en |
| dc.description.sponsorship | This work has been partially supported by the Etortek, Saiotek and Research Groups 2007-2012 (IT-242-07) programs (Basque Government), TIN2005-03824 and Consolider Ingenio 2010 - CSD2007-00018 projects (Spanish Ministry of Education and Science) and COMBIOMED network in computational biomedicine (Carlos III Health Institute). | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Echegoyen, C., Santana, R., Lozano, J. A., Larrañaga, P. (2008) The impact of exact probabilistic learning algorithms in EDAs based on bayesian networks. In Chen, Y. P, Lim M-H. (Eds.), Linkage in Evolutionary Computation (pp. 109-139). Springer. https://doi.org/10.1007/978-3-540-85068-7_6 | |
| dc.identifier.doi | 10.1007/978-3-540-85068-7_6 | |
| dc.identifier.isbn | 978-3-540-85068-7 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/52961 | |
| dc.language.iso | eng | |
| dc.publisher | Springer | |
| dc.relation.ispartof | In Chen, Y. P; Lim, M-H. (Eds.). Linkage in Evolutionary Computation. Berlín: Springer; 2008. p. 109-139 | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MEC//TIN2005-03824/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/MEC//CSD2007-00018/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1007/978-3-540-85068-7_6 | |
| dc.rights | © 2008 Springer-Verlag Berlin Heidelberg. | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.subject | Bayesian network | en |
| dc.subject | Bayesian information criterion | en |
| dc.subject | Evolutionary computation | en |
| dc.subject | Frequency matrice | en |
| dc.subject | Distribution algorithm | en |
| dc.title | The impact of exact probabilistic learning algorithms in EDAs based on bayesian networks | en |
| dc.type | info:eu-repo/semantics/bookPart | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | cb45e960-5f19-491c-ba50-555e4ce5f169 | |
| relation.isAuthorOfPublication.latestForDiscovery | cb45e960-5f19-491c-ba50-555e4ce5f169 |