A Method for Learning Bayesian Network Structure

被引：1
|
作者：
Li, Jingnan [1 ]
Zhang, Yingxia [1 ]
机构：
[1] Xidian Univ, Sch Math & Stat, Xian, Shanxi, Peoples R China
来源：
2014 SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC), VOL 2 | 2014年
关键词：
Bayesian network; structure learning; mutual information; conditional indepence test;
D O I：
10.1109/IHMSC.2014.156
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Bayesian network structures from data is an NP-hard problem, In this paper, we propose an approach based on mutual information and PC algorithm methods. This algorithm obain the initial undirected graph using mutual information firstly, obtain a PDAG using PC algorithm. Experimental results show that our method outperforms the PC algorithms under the same conditions, Thus the algorithm decreases the running time and the order of CI tests greatly than the PC algorithm.
引用
收藏
页码：222 / 225
页数：4
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