Machine Learning with R Cookbook - Second Edition

How it works...

The support vector machine constructs a hyperplane (or set of hyperplanes) that maximize the margin width between two classes in a high dimensional space. In these, the cases that define the hyperplane are support vectors, as shown in the following figure:

Support vector machine

The support vector machine starts by constructing a hyperplane that maximizes the margin width. Then, it extends the definition to a nonlinear separable problem. Lastly, it maps the data to a high dimensional space where the data can be more easily separated with a linear boundary.

The advantage of using SVM is that it builds a highly accurate model ...