An efficient attribute ordering optimization in Bayesian networks for prognostic modeling of the metabolic syndrome

Han Saem Park, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

The metabolic syndrome has become a significant problem in Asian countries recently due to the change in dietary habit and life style. Bayesian networks provide a robust formalism for probabilistic modeling, so they have been used as a method for prognostic model in medical domain. Since K2 algorithm is influenced by an input order of the attributes, optimization of BN attribute ordering is studied. This paper proposes an evolutionary optimization of attribute ordering in BN to solve this problem using a genetic algorithm with medical knowledge. Experiments have been conducted with the dataset obtained in Yonchon County of Korea, and the proposed model provides better performance than the comparable models.

Original languageEnglish
Title of host publicationComputational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings
PublisherSpringer Verlag
Pages381-391
Number of pages11
ISBN (Print)3540372776, 9783540372776
Publication statusPublished - 2006 Jan 1
EventInternational Conference on Intelligent Computing, ICIC 2006 - Kunming, China
Duration: 2006 Aug 162006 Aug 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4115 LNBI -III
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Intelligent Computing, ICIC 2006
CountryChina
CityKunming
Period06/8/1606/8/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Park, H. S., & Cho, S. B. (2006). An efficient attribute ordering optimization in Bayesian networks for prognostic modeling of the metabolic syndrome. In Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings (pp. 381-391). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4115 LNBI -III). Springer Verlag.