It basically first considers the point in between the two Classifiers and then tries to predict the probability to guess in which class it belongs to . Then it tries to calculate the Posterior Probability from the product of likelihood and the prior probability . We can ignore the Marginal likelihood{ p(x) } because when we compare the posterior probability ofthe different classifications then it cancels out .
This is suitable for Sentiment Analysis problems with two output labels .