Model Construction and Function Realizing of Bayesian Network Based on Netica Platform
Jing Chen, Jingqi Fu, Wei Su · International Journal of Advancements in Computing Technology · 2013
At present, the Bayesian network soft wares have no visual model and can not realize probabilistic inference. Aiming at the typical problems, Netica platform was proposed to construct Bayesian network model. The paper described the representation, modeling and probabilistic reference of Bayesian network. According to constructing requirement of Bayesian network, we specified node variables of Bayesian network, defined the states of the selected node, and constructed Bayesian network model in Netica platform. Learned and optimized Bayesian network model from sample dataset. Based on Bayesian network model, the paper carry out probabilistic inference and analyze the node’s sensitivity to findings, i.e. realizing function of Bayesian network. The result shows that it is feasible and effective to construct Bayesian network model based Netica platform.