dc.contributor.author | Santana Hermida, Roberto | |
dc.contributor.author | Bielza, Concha | |
dc.contributor.author | Larrañaga, Pedro | |
dc.contributor.author | Lozano Alonso, José Antonio | |
dc.contributor.author | Echegoyen, Carlos | |
dc.contributor.author | Mendiburu Alberro, Alexander | |
dc.contributor.author | Armañanzas Arnedillo, Rubén | |
dc.contributor.author | Shakya, Siddartha | |
dc.date.accessioned | 2014-03-31T18:25:31Z | |
dc.date.available | 2014-03-31T18:25:31Z | |
dc.date.issued | 2010-07 | |
dc.identifier.citation | Journal of Statistical Software 35(7) : 1-30 (2010) | es |
dc.identifier.issn | 1548-7660 | |
dc.identifier.uri | http://hdl.handle.net/10810/11887 | |
dc.description.abstract | This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based on undirected and directed probabilistic graphical models. The implementation contains several methods commonly employed by EDAs. It is also conceived as an open package to allow users to incorporate different combinations of selection, learning, sampling, and local search procedures. Additionally, it includes methods to extract, process and visualize the structures learned by the probabilistic models. This way, it can unveil previously unknown information about the optimization problem domain. Mateda-2.0 also incorporates a module for creating and validating function models based on the probabilistic models learned by EDAs. | es |
dc.description.sponsorship | Partially supported by the Saiotek and Research Groups 2007-2012 (IT-242-07) programs (Basque Government), TIN2008-06815-C02-01, TIN- 2008-06815-C02-02, TIN2007-62626 and Consolider Ingenio 2010 - CSD2007-00018 projects (Spanish Ministry of Science and Innovation), the CajalBlueBrain project, and the COMBIOMED network in computational biomedicine (Carlos III Health Institute). | es |
dc.language.iso | eng | es |
dc.publisher | Journal of Statistical Software, UCLA Dept. Statistics | es |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.subject | estimation of distribution algorithms | es |
dc.subject | probabilistic models | es |
dc.subject | statistical learning; | es |
dc.subject | optimization | es |
dc.subject | MATLAB | es |
dc.subject | evolutionary algorithms | es |
dc.subject | Kikuchi approximations | es |
dc.subject | model; | es |
dc.subject | classifier | es |
dc.subject | networks | es |
dc.title | Mateda-2.0: Estimation of Distribution Algorithms in MATLAB | es |
dc.type | info:eu-repo/semantics/article | es |
dc.rights.holder | This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) | es |
dc.relation.publisherversion | http://www.jstatsoft.org/v35/i07 | es |
dc.departamentoes | Arquitectura y Tecnología de Computadores | es_ES |
dc.departamentoeu | Konputagailuen Arkitektura eta Teknologia | es_ES |
dc.subject.categoria | SOFTWARE | |
dc.subject.categoria | STATISTICS AND PROBABILITY | |