Improving Bayesian network local structure learning via data-driven symmetry correction methods

Learning the structure of a Bayesian network (BN) from data is NP-hard. To efficiently handle high-dimensional datasets, many BN local structure learning algorithms are proposed. These learning algorithms can be categorized into two types: constraint-based and score-based. These learning algorithms...

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Bibliographic Details
Main Authors: Zhao, Jianjun, Ho, Shen-Shyang
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/151697
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Institution: Nanyang Technological University
Language: English

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