Introduction

In the previous chapters, you learned about common classification algorithms such as logistic regression, SVM, decision tree, and random forest. You also learned the advantages and disadvantages of each of these algorithms. You implemented these algorithms using the most popular machine learning API, scikit-learn, and fine-tuned, optimized, and evaluated different machine learning models.

In this chapter, you will start by exploring multiclass classification. Then, you will deep dive into the intuition behind multiclass classification problems and see how to tackle class-imbalanced data. Finally, you will create a multiclass classification classifier.