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Posterior Probability

The probability of a hypothesis after conditioning on observed evidence, computed by Bayes' theorem as prior times likelihood renormalized; it is the quantity soft assignments and MAP estimates are built from.

Questions this Concept answers

Why does a posterior probability change when the prior changes, even if the observed data stay the same?

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Bayes' theorem

A posterior probability is the probability assigned to a hypothesis after observing evidence, as opposed to the prior probability held before. Bayes' theorem computes it by multiplying the prior by t…