Answer Posted / Prakash Raj

Bayes' Theorem is a probability theory rule that calculates conditional probabilities. It states the probability of an event A given event B (P(A|B)) can be found by multiplying the prior probability of A (P(A)), the likelihood of B given A (P(B|A)), and the prior probability of B (P(B)) divided by the total evidence or marginal likelihood P(B). In machine learning, Bayes' Theorem is employed in classification algorithms such as Naive Bayes and Bayesian networks to make predictions based on conditional probabilities.

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