Chapter 4. Models – Learning from Information
So far in this book, we have examined a range of tasks and techniques. We introduced the basics of data types, structures, and properties, and we familiarized ourselves with some of the machine learning tools that are available.
In this chapter, we will look at three broad types of model:
- Logical models
- Tree models
- Rule models
The next chapter will be devoted to another important type of model—the linear model. Much of the material in this chapter is theoretical, and its purpose is to introduce some of the mathematical and logical tools needed for machine learning tasks. I encourage you to work through these ideas and formulate them in ways that may help solve problems that we come across.
Logical models
Logical models divide the instance space, that is the set of all possible or allowable, instances, into segments. The goal is to ensure that the data in each segment is homogeneous with respect to a particular task. For example...
