Structural Learning about Directed Acyclic Graphs from Multiple Databases

Qiang Zhao

Abstract and Applied Analysis, 2012, vol. 2012, 1-9

Abstract:

We propose an approach for structural learning of directed acyclic graphs from multiple databases. We first learn a local structure from each database separately, and then we combine these local structures together to construct a global graph over all variables. In our approach, we do not require conditional independence, which is a basic assumption in most methods.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:579543

DOI: 10.1155/2012/579543

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