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?


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

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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