We will now cover one of the oldest classification methods; naïve Bayes is an early 18th century model. It is a supervised learning model that solves binary and multiclass classification problems. The word naïve derives from the assumption that the model makes about the data. We consider it naïve because it assumes that variables are independent of each other, meaning there is no dependency on the data. This rarely occurs in the actual world. We can reduce the naïve Bayes theorem into Equation 9-1.
(Equation ...
