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	Incremental Learning Bayesian Network Structures Efficiently
	Shi, Da ; Tan, Shaohua
	2010
关键词	Bayesian network structure learning incremental learning
英文摘要	In this paper, a new hybrid incremental learning algorithm for Bayesian network structures is proposed. It develops a polynomial-time constraint-based technique to build up a candidate parents set for each domain variable, and a hill climbing search procedure is then employed to refine the current network structure under the guidance of those candidate parents sets. Our algorithm always offers considerable computational complexity savings while obtaining better model accuracy compared to existing incremental algorithms when dealing with complex real-world problems. The more complex the real-world problems are, the more significant the advantage our algorithm keeps is.; Automation & Control Systems; Engineering, Electrical & Electronic; Nanoscience & Nanotechnology; Robotics; EI; CPCI-S(ISTP); 0
语种	英语
DOI标识	10.1109/ICARCV.2010.5707313
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/293262]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Shi, Da,Tan, Shaohua. Incremental Learning Bayesian Network Structures Efficiently. 2010-01-01.

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