Chapter 8. Fine-Tuning Classification Algorithms
Note
Learning Objectives
By the end of this chapter, you will be able to:
Use some of the most common classification algorithms from the scikit-learn machine learning library
Describe the logic behind tree-based models
Choose the performance metrics required for classification problems
Optimize and evaluate the best classification algorithm for customer churn prediction
Note
This chapter covers other classification algorithms such as support vector machines, decision trees, random forest, and explains how to evaluate them.
