What Is Meant By Bayes Theorem
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Bayes' Theorem:
The Bayes theorem describes the probability of an event based on the prior knowledge of the conditions that might be related to the event. If we know the conditional probability , we can use the bayes rule to find out the reverse probabilities . If the event "A" has happened, then the probability of the event "B" is the probability of the event "A" happening when the event "B" has happened times the probability of the event "B" happening with no prior events all divided by the probability of the event "A" happening with no prior events.
P(A|B) = P(A) * P(B|A) / P(B)
A, B = events
P(A|B) = probability of A given B is true
P(B|A) = probability of B given A is true
P(A), P(B) = the independent probabilities of A and B.
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The Bayes theorem describes the probability of an event based on the prior knowledge of the conditions that might be related to the event. If we know the conditional probability , we can use the bayes rule to find out the reverse probabilities . If the event "A" has happened, then the probability of the event "B" is the probability of the event "A" happening when the event "B" has happened times the probability of the event "B" happening with no prior events all divided by the probability of the event "A" happening with no prior events.
P(A|B) = P(A) * P(B|A) / P(B)
A, B = events
P(A|B) = probability of A given B is true
P(B|A) = probability of B given A is true
P(A), P(B) = the independent probabilities of A and B.
glad to help!
Plz mark as Brainliest
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