Chapter 14: Naïve Bayes Classification
In this chapter, we will examine situations where naïve Bayes might be a more efficient classifier than the ones we have examined so far. Naïve Bayes is a very intuitive and easy-to-implement classifier. Assuming our features are independent, we may even get improved performance over logistic regession, particularly if we are not using regularization with the latter.
In this chapter, we will discuss the fundamental assumptions of naïve Bayes and how the algorithm is used to tackle some of the modeling challenges we have already explored, as well as some new ones, such as text classification. We will consider when naïve Bayes is a good option and when it is not. We will also examine the interpretation of ...
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