@inproceedings{e1d798ac591342d59fc83e97010c32f2,
title = "An efficient attribute ordering optimization in Bayesian networks for prognostic modeling of the metabolic syndrome",
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.",
author = "Park, {Han Saem} and Cho, {Sung Bae}",
year = "2006",
doi = "10.1007/11816102_42",
language = "English",
isbn = "3540372776",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "381--391",
booktitle = "Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings",
address = "Germany",
note = "International Conference on Intelligent Computing, ICIC 2006 ; Conference date: 16-08-2006 Through 19-08-2006",
}