TY - CHAP

T1 - On selecting the optimal Bayesian Network model construction approach

AU - Achumba, Ifeyinwa E.

AU - Azzi, Djamel

AU - Bersch, Sebastian

AU - Ezebili, Ifeanyi

PY - 2012/7/4

Y1 - 2012/7/4

N2 - The construction of a Bayesian Network (BN) model entails two major tasks: realization of the model structure, and the calibration (parameterization) of the model. BN model constructors, ab initio, relied only on domain experts to define both the structure and parameters of a model.
Currently, algorithms exist to construct BN models from data. Consequently, there are three BN model construction techniques: total expert-centred, total data-centred, and semi data-centred. We empirically investigated which of these approaches is the optimal approach for the construction of a BN model for our intended application. The investigation yielded some interesting themes.

AB - The construction of a Bayesian Network (BN) model entails two major tasks: realization of the model structure, and the calibration (parameterization) of the model. BN model constructors, ab initio, relied only on domain experts to define both the structure and parameters of a model.
Currently, algorithms exist to construct BN models from data. Consequently, there are three BN model construction techniques: total expert-centred, total data-centred, and semi data-centred. We empirically investigated which of these approaches is the optimal approach for the construction of a BN model for our intended application. The investigation yielded some interesting themes.

M3 - Chapter (peer-reviewed)

SN - 9789881925213

T3 - Lecture notes in engineering and computer science

BT - Proceedings of the World Congress on Engineering 2012. Vol 2

PB - Newswood Limited

CY - Hong Kong

T2 - World Congress on Engineering

Y2 - 4 July 2012 through 6 July 2012

ER -