Chapter 9. Bayesian learning

In this chapter, we will go back to covering an important, statistical-based method of learning called the Bayesian method learning, and in particular, the Naïve Bayes algorithm among others. The statistical models generally have an explicit probability model, which reveals the probability of an instance belonging to a particular class rather than just classification while solving a classification problem. Before taking a deep dive into the Bayesian learning, you will learn some important concepts under statistics such as probability distribution and the Bayes theorem which is the heart of Bayesian learning.

Bayesian learning is a supervised learning technique where the goal is to build a model of the distribution of class labels that have a concrete definition of the target attribute. Naïve Bayes is based on applying Bayes' theorem with the naïve assumption of independence between each and every pair of features.

You will learn the basics and advanced concepts...