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Chain graphs structure learning given local background knowledge
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AI
DOI：10.1016/j.ijar.2025.109524.png)
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Abstract
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• We propose the CGLGK algorithm given local background knowledge to further refine the relationship between variables. • We introduce skeleton correction rules and locally valid orientation rules to refine edge connections and edge orientation. • Theoretical analysis demonstrates its correctness, and experiments on simulated and real datasets validate its effectiveness.
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