XPost: comp.ai.neural-nets, comp.theory, sci.stat.math   
   From: ted.dunning@gmail.com   
      
   Read David Heckerman's tutorial on the topic.   
      
   In one sentence, Bayesian networks reduce the dimensionality of the   
   learning problem by assuming some (but not all) inputs are independent.   
      
      
   The pattern of independence assumptions is given by the graph (aka   
   network).  Sometimes this graph is heuristically defined, sometimes it   
   is learned.   
      
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