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.