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.