The Bayes theorem helps us in finding posterior probability, given a certain condition:

P(A|B)= P(B|A) * P(A)/P(B)

A and B can be deemed as the target and features, respectively.

Where, P(A|B): posterior probability, which implies the probability of event A, given that B has taken place:

• P(B|A): The likelihood that implies the probability of feature B, given the target A
• P(A): The prior probability of target A
• P(B): The prior probability of feature B