Introduction to Classification

This chapter introduces the fundamentals of classification in machine learning, beginning with an overview of the basics and the various challenges posed by class imbalance. Therefore, four key classification approaches: binary, multiclass, multilabel, and multiobjective are explored in this chapter. To provide a solid foundation, we delve into popular classification algorithms, including Support Vector Machines (SVM), decision trees, Naive Bayes, and neural networks, particularly focusing on their application in multiclass, multilabel and multiobjective classification scenarios. This chapter aims to equip readers with a comprehensive understanding of classification techniques and their practical implementations in handling diverse classification problems.