Bayesian Networks Construction and Their Applications in Data Mining
贝叶斯学习,贝叶斯网络与数据采掘

Recently Bayesian networks(BN)become a noticeable research direction in Data Mining,ln this paper we introduce the structure of Bayesian networks ,and the process of constructing a BN ,with the emphasis on the basic methods of learning from prior knowledge and sample data,using Bayesian learning approach,to identify the structures and probabilities of BN. The merits of Bayesian networks are that prior knowledge can be combined with observed data,which is important'especially when data is scarce or expensive ,that causal relationships among data can be learned ,and incomplete data set can be readily handled,which other models are disable to do so. It can foresee that Bayesian networks will become a powerful tools in Data Mining.