8. Fine-Tuning Classification Algorithms

Overview

This chapter will help you optimize predictive analytics using classification algorithms such as support vector machines, decision trees, and random forests, which are some of the most common classification algorithms from the scikit-learn machine learning library. Moreover, you will learn how to implement tree-based classification models, which you have used previously for regression. Next, you will learn how to choose appropriate performance metrics for evaluating the performance of a classification model. Finally, you will put all these skills to use in solving a customer churn prediction problem where you will optimize and evaluate the best classification algorithm for predicting whether a given customer will churn or not.