Two Cases of Learning Bayesian Network from Observable Variables

摘要：

In terms of differences the structure of the network and the variables, the process of learning Bayesian networks takes different forms. The variables can be observable or hidden in all or some of the data points, and the structure of the network can be known or unknown. Consequently, there are four cases of learning Bayesian networks from data: known structure and observable variables, unknown structure and observable variables, known structure and unobservable variables and unknown structure and unobservable variables. In this paper, we focus on known structure and observable variables, unknown structure and observable variables.

作者: Liu Hui CAO Yonghui

作者单位: School of Computer and Information Technology Henan Normal University Xinxiang, China School of Economics & Management Henan Institute of Science and Technology Xinxiang, China

会议类型: 国际会议

会议名称: 2010 International Conference on E-Health Networking,Digital Ecosystems and Techonlogies(2010电子健康网络、数字生态系统和技术国际会议 EDT 2010)

会议地点: 深圳

会议语种:英文

页码: 488-491

在线出版日期: 2010-04-17（万方平台首次上网日期，不代表论文的发表时间）