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A belief net is a
directed
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acyclic graph
composed of
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stochastic
variables.
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We get to
observe some of
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the variables
and we would
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like to solve two
problems:
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The
inference problem: Infer
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the states of
the unobserved
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variables.
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The
learning problem: Adjust
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the interactions
between
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variables to make
the
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network more
likely to
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generate the
observed data.
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