关键词: 连续贝叶斯网络, 预测能力, 最小切割集

Abstract: In this paper, the definition of forecasting ability and its calculational method are presented between two continuous variables. A method of learning continuous Bayesian networks structure from data set based on forecasting ability is developed. This method is made up of two parts. Each part is combined with checking a cyclic route in a directed graph. firstly, an elementary Bayesian network structure is set up. Secondly, this elementary Bayesian network structure is regulated ,including to increase the losed arcs, to delete superfluous arcs and to regulate direction of arcs. The experiment is made by using simulant data and the experimental results are shown by the means of contrasting.

Key words: continuous Bayesian network, forecasting ability, minimum d-separating set