Grammar-Guided Evolutionary Construction of Bayesian networks
Data(s) |
2011
|
---|---|
Resumo |
This paper proposes the EvoBANE system. EvoBANE automatically generates Bayesian networks for solving special-purpose problems. EvoBANE evolves a population of individuals that codify Bayesian networks until it finds near optimal individual that solves a given classification problem. EvoBANE has the flexibility to modify the constraints that condition the solution search space, self-adapting to the specifications of the problem to be solved. The system extends the GGEAS architecture. GGEAS is a general-purpose grammar-guided evolutionary automatic system, whose modular structure favors its application to the automatic construction of intelligent systems. EvoBANE has been applied to two classification benchmark datasets belonging to different application domains, and statistically compared with a genetic algorithm performing the same tasks. Results show that the proposed system performed better, as it manages different complexity constraints in order to find the simplest solution that best solves every problem. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Publicador |
Facultad de Informática (UPM) |
Relação |
http://oa.upm.es/12190/1/INVE_MEM_2011_91094.pdf http://www.iwinac.uned.es/current/ |
Direitos |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess |
Fonte |
Proceedings of the 4th International Conference on Interplay Between Natural and Artificial Computation, IWINAC'11 | 4th International Conference on Interplay Between Natural and Artificial Computation, IWINAC'11 | 30/05/2011 - 03/06/2011 | Las Palmas de Gran Canaria, España |
Palavras-Chave | #Matemáticas #Informática |
Tipo |
info:eu-repo/semantics/conferenceObject Ponencia en Congreso o Jornada PeerReviewed |