# Demystifying Bayes’ Decision Rule

Bayesian decision theory is a fundamental statistical approach to solve classification problems. It relies on prior probabilities and class conditional densities to reach a decision. Often it is stated that Bayes classifier is the most *optimum* among all classifiers and it has the least *error*. In simple terms, it aims to minimize the probability of error in classification problems.

One should also think that if in fact Bayes’ classifier is the best classifier for any classification problem, why do we need other classification methods in the first place! Also, how do we…