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Are there any algorithms for combining multiple Bayesian networks? For example, let's say I have 5 variables A, B, C, D and E, and I build 5 Bayesian networks on different random subsets of these, let's say:

  1. A, B, C
  2. C, D
  3. A, E, D
  4. B, E, A
  5. A, D

Is it possible to recover a single BN that is an aggregate of these 5 individual BNs in the general case?

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closed as unclear what you're asking by Michael Chernick, mdewey, kjetil b halvorsen, user158565, mkt Jan 14 at 13:29

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

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    $\begingroup$ Could you clarify how you are building the individual networks and what is the purpose of the combination? $\endgroup$ – Juho Kokkala Jan 10 at 6:54