Section 8 An Overview of Classification

In this chapter, we study approaches for predicting qualitative responses, a process that is known as Classification.

Predicting a qualitative response for an observation can be referred to as classifying that observation, since it involves assigning the observation to a category, or class. On the other hand, often the methods used for classification first predict the probability that the observation belongs to each of the categories of a qualitative variable, as the basis for making the classification.

Generally, we discuss some widely-used classifiers:

  1. Logistic Regression

  2. Linear Discriminant Analysis

  3. Quadratic Dislogistic Regression

  4. Naive Bayes

  5. K-nearest Neighbors

The discussion of logistic regression is used as a jumping-off point for a discussion of Generalized Linear Models, and in particular, Poisson Regression.