In this section, you will learn about support vector machines (SVMs), or, to be more specific, linear support vector machines. In order to understand support vector machines, you will need to know what support vectors are. They are illustrated for you in the following diagram:
The concept of support vectors
In the preceding diagram, the following applies:
- The linear support vector machine is a form of linear classifier. A linear decision tree boundary is constructed, and the observations on one side of the boundary (the circles) belong to one class, while the observations on the other side of the boundary (the squares) belong to another class.
- The support vectors are the observations that have a triangle on them.
- These are the observations that are either very close to the linear decision boundary or have been incorrectly classified.
- We can define...
