| 摘要: |
| 从机器学习的角度研究贝叶斯方法及其学习机制,着重讨论了具有完整数据、不完整数据集,及在结构不确定时贝叶斯网络进行学习的方法,表明贝叶斯网络在数据采掘中是一个有力的工具,文后给出一个基于贝叶斯网络的学习的实例。 |
| 关键词: 贝叶斯网络 贝叶斯学习 机器学习 数据采掘 |
| DOI： |
| 投稿时间：2000-09-01 |
| 基金项目: |
|
| Bayesian Learing of Bayesian Network |
|
Hu Zhenyu, Lin Shimin
|
| (Dept. of Computer Science, Guangxi Normal University, Guilin, 541004) |
| Abstract: |
| The Bayesian method and its learning mechanism from the view of machine learning is explored. The Bayesian leaning approaches for different conditions such as complete data, incomplete data as well as uncertain network structure are discussed. It shows that Bayesian network is a powerful tool in data mining. An example from reality is given. |
| Key words: Bayesian approach Bayesian network machine learning data mining |
