# Naive Bayes

The *Naive Bayes* algorithm is part of a family of *classifier* algorithms that aim to predict the *category* of an observation. It is a Maximum Likelihood (MLE) *generative* model that suggests each class is generated by its features. At its core, the algorithm uses Bayes theorem. In this post, we walk through the application of the *Naive Bayes* algorithm and demonstrate the conditions under which the algorithm excels, does poorly, and is improved through feature engineering.