6.2: Different Feature Selection Methods

There are three broad approaches to feature selection. Filter method, Wrapper method, and Embedded method. We will discuss the first two methods in this chapter. For certain modeling techniques, feature selection and model training happen in a parallel fashion. These are called embedded methods of feature selection. Also, for certain modeling techniques, feature selection should be approached after keeping in mind the nuances of the technique. For certain techniques, feature selection is altogether discouraged. We will discuss these fine nuances in detail in chapter 7.

Apart from filter, wrapper, and embedded methods, there is another, 4th group of feature selection techniques. These are known as metaheuristic algorithms. In chapter 8, we will discuss these techniques in detail.