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@jemoka / Jemoka Knowledge Base / wiki/concepts/bayes_normalization_constant.md
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--- title: "Bayes Normalization Constant" type: concept related: [Baysian Network] source: https://www.jemoka.com/posts/kbhbayes_normalization_constant/ confidence: high status: active --- For some Baysian Network situation, you will note that there’s some bodge of values below: \begin{equation} P(A|M) = \frac{P(M|A)P(A)}{P(M)} \end{equation} if we are only interested in a function in terms of different values of \(a\), \(P(M)\) is not that interesting. Therefore, we can just calculate \(A\) for all \(a\), and then normalize it to sum to 1: \begin{equation} P(A|M) \propto P(M|A)P(A) \end{equation} and then, after calculating each \(P(M|A)P(A)\) , we just ensure that each thing sums to one.