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757Belief Networks (Conditional independence in Bayesian Networks)

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  • orondojones
    May 3, 2007
      I've read in the 2nd edition, that a node is conditionally independent
      of its non-descendants given its parents or given its Markov blanket.
      The 2nd edition makes reference to the 1st edition regarding d-
      separation and I have read the 1st edition's information about d-
      separation; however, I have come across in some additonal reading
      something called Berkson's paradox.

      This paradox seems to show circumstances that contradict the
      statements made about d-separation and Markov blankets. Am I correct
      in thinking that Berkson's paradox is an exception to rules regarding
      d-separation and Markov blankets?
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