A Bayesian classifier is based on the idea that the role of a (natural) class is to predict the values of features for members of that class. Examples are grouped in classes because they have common values for the features. Such classes are often called natural kinds. In this section, the target feature cor- responds to a discrete class, which is not necessarily binary.
P (Ci|x) = p(x|Ci) ∗ P (Ci)/p(x)
where, P(Ci—x) : Posterior Probability, the conditional probability that is assigned after the relevant evidence or background is taken into account
p(x—Ci) : Likelihood, it is about an infinite set of possible probabilities, given an outcome
P(Ci) : Prior, the probability an event will happen before you taken any new evidence into account.
p(x) : Evidence