Transformation-Based Classifiers

One of the first approaches to accomplish multilabel classification was based on data transformation techniques. These are aimed to produce binary or multiclass datasets from the multilabel original ones, thus allowing the use of traditional classification algorithms to solve the problem. The goal of this chapter is to introduce the most relevant transformation-based MLC methods, as well as to experimentally test the most popular ones. Section 4.1 provides a broad introduction to the chapter contents. The main data transformation approaches are defined in Sect. 4.2; then, several methods based on each approach are described in Sects. 4.3 and 4.4. Four of these methods are experimentally tested in Sect. 4.5. Section 4.6 summarizes the chapter.