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Let assume that we have dataset of variables (random events), I apriori would like to set dependency conditions between some of them and perform structure learning to figure out the rest of the net. How it can be done practically (e.g. some libs like bnlearn etc.) or at least in theory?

I was trying to google it but haven't found anything related

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Hill Climbing algo or Constraint-based structure learning algorithms implemented accept whitelist or blacklist arguments permitting or prohibitting some arcs.

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