Naive Bayes Classifier From Scratch

The Naive Bayes algorithm is a classification technique based on Bayes Theorem. It assumes that the presence of a feature in a class is unrelated to the presence on any other feature. The algorithm rely on the posterior probability of the class given a predictor, as we can see in the following formula:

where:

P(c|x) - the posterior probability of class given a predictor P(x|c) - the probability of the predictor $$x$$ given the class. Also known as Likelihood P(c) - the prior probability of the class P(x) - the prior probability of predictor.

Find here the blog post for a better understanding.