*Exploring Naive Bayes: Mathematics, How it works, Pros & Cons, and Applications*

*Exploring Naive Bayes: Mathematics, How it works, Pros & Cons, and Applications*

## What is Naïve Bayes Algorithm?

Naive Bayes is a classification technique that is based on Bayes’ Theorem with an assumption that all the features that predicts the target value are independent of each other. It calculates the probability of each class and then pick the one with the highest probability. It has been successfully used for many purposes, but it works particularly well with natural language processing (NLP) problems.

Bayes’ Theorem describes the probability of an event, based on a prior knowledge of conditions that might be related to that event.