O'Reilly logo

Mastering Predictive Analytics with R - Second Edition by Rui Miguel Forte, James D. Miller

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Summary

In this chapter, we presented the maximal margin hyperplane as a decision boundary that is designed to separate two classes by finding the maximum distance from either of them. When the two classes are linearly separable, this creates a situation where the space between the two classes is evenly split.

We've seen that there are circumstances where this is not always desirable, such as when the classes are close to each other because of a few observations. An improvement to this approach is the support vector classifier that allows us to tolerate a few margin violations, or even misclassifications, in order to obtain a more stable result. This also allows us to handle classes that aren't linearly separable. The form of the support vector ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required