Naive Bayes classifier

Na?ve Bayes classifier is a ML algorithm based on Bayes' theorem. The algorithm is comparable to how a belief system evolves. Bayes' theorem was initially introduced by an English mathematician, Thomas Bayes, in 1776. This algorithm has various applications, and has been used for many historic tasks for more than two centuries. One of the most famous applications of this algorithm was by Alan Turing during the Second World War, where he used Bayes' theorem to decrypt the German Enigma code. Bayes' theorem has also found an important place in ML for algorithms such as Bayesian Net and Naive Bayes algorithm. The Na?ve Bayes algorithm is very popular for ML due to its low complexity and transparency regarding why it makes the prediction.