The term Naive Bayes denotes that there is an naive assumption such that every feature is independent of other features and Bayes refers as a name of statistician Thomas Bayes.

Naive Bayes is one of the most simple algorithms for the classification and for large datasets.

The Bayes equation is

where,

P(A|B) = Probability of A is true given that B is true.

P(B|A) = Probability of B is true given that A is true.

P(A)= Probability of A to be true.

P(B)= Probability of B to be true.

There are four terms in this equation,

Posterior, Likelihood, Prior, Marginal/Evidence