The final model that we will cover here for classification is called Naive bayes. In Chapter 2, Matrices, Probability, and Statistics, we discussed the Bayes rule, which forms the basis of this technique. Naive Bayes is a probability-based method like logistic regression, but its basic ideas and assumptions are different.
Naive Bayes is also implemented in github.com/sjwhitworth/golearn, which will allow us to easily try it out. However, there are a variety of other Go implementations including github.com/jbrukh/bayesian, github.com/lytics/multibayes, and github.com/cdipaolo/goml.
