In machine learning, the task of classification is that of dividing a set of observations (objects) into groups called classes, based on an analysis of their formal description. For classification, each observation (object) is mapped to a certain group or nominal category based on a certain qualitative property. Classification is a supervised task because it requires known classes for training samples. Labeling of a training set is usually done manually, with the involvement of specialists in the given field of study. It's also notable that if classes are not initially defined, then there will be a problem with clustering. Furthermore, in the classification task, there may be more than two classes (multi-class), and each of the objects may belong to more than one class (intersecting).
In this chapter, we will discuss various approaches to solving a classification...
