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Bayes Rule

$P(A|B) = {{P(B|A)P(A)} \over {P(B)}}$

B P(B|A) P(B|A) P(A) P(B)
Posterior Likelyhood Prior I Likelyhood

B is like evidence and A is causes.

B is usualy calculated by total probability formula: $P(B) = \sum_{a}^{} P(B|A=a) P(A=a)$

Bayes Network

Three parameters:

  • P(A)
  • P(B|A)
  • P(B,!A).

\[ P(\overline{A}|B) = {{P(B|\overline{A})P(\overline{A})} \over {P(B)}}\]

P(B) — nominator

\[ P^{'}(A|B) = P(B|A) P(A) P^{'}(\overline{A}|B) = P(B|\overline{A}) P(\overline{A}) \]

-- SashaMazurov - 25-Oct-2011

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Topic revision: r2 - 2020-08-19 - TWikiAdminUser
 
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