Chapter 5. More Classification Techniques – K-Nearest Neighbors and Support Vector Machines


"Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write."

 -- H.G. Wells

In Chapter 3, Logistic Regression and Discriminant Analysis we discussed using logistic regression to determine the probability that a predicted observation belongs to a categorical response—what we refer to as a classification problem. Logistic regression was just the beginning of classification methods, with a number of techniques that we can use to improve our predictions.

In this chapter, we will delve into two nonlinear techniques: K-Nearest Neighbors (KNN) and Support Vector Machines (SVM). These techniques are more sophisticated ...

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