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Efficient and effective Bayesian network local structure learning |
Jianjun YANG1,*( ),Yunhai TONG1,Zitian WANG2,Shaohua TAN1 |
1. Center for Information Science, Peking University, Beijing 100871, China 2. Agricultural Bank of China, Beijing 100871, China |
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Abstract In this paper, we propose a more efficient Bayesian network structure learning algorithm under the framework of score based local learning (SLL). Our algorithm significantly improves computational efficiency by restricting the neighbors of each variable to a small subset of candidates and storing necessary information to uncover the spouses, at the same time guaranteeing to find the optimal neighbor set in the same sense as SLL. The algorithm is theoretically sound in the sense that it is optimal in the limit of large sample size. Empirical results testify its improved speed without loss of quality in the learned structures.
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Keywords
local structure learning
Bayesian network
Markov blanket
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Corresponding Author(s):
Jianjun YANG
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Issue Date: 11 August 2014
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