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"Moses Chan" <moses_w_chan@raytheon.com> wrote in message

news:e2175f.0201251517.55b6e409@posting.google.com...

*> Hi all,
*

*>
*

*> Could someone comment on how would Bayesian Network encode these rules:
*

*>
*

*> 1) if A then (B and C);
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*> 2) if A then (B or C);
*

*> 3) if (A and B) and C;
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*> 4) if (A or B) then C.
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*>
*

*> Specifically, how would one determine the difference between conjunctive
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and

*> disjunctive term using conditional independency?
*

In general, for solid Bayesian networks you should use individual

probabilities for every joined fact. If this is not possible, you could use

joined probabilities for joined conditional facts. For joined results

(especially "AND") the only thing you can do is combine any previous

(statistical) knowledge about A, B, C and produce some estimation on joined

facts using inclusion-exclusion theory from sets. For example, if B and C

are statistically independent, then P{(B.and.C)|A) should be equal to

P(B|A)*P(C|A).

--Harris

- 'Malo e lelei ki he pongipongi!'

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