Data Science Revealed: With Feature Engineering, Data Visualization, Pipeline Development, and Hyperparameter Tuning

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021

T. C. NokeriData Science Revealedhttps://doi.org/10.1007/978-1-4842-6870-4_8

8. Classification Using Decision Trees

Tshepo Chris Nokeri¹  

(1)

Pretoria, South Africa

 

This chapter presents the most widespread ensemble method, the decision tree. A decision tree classifier estimates a categorical dependent variable or a continuous dependent. It solves binary and multiclass classification problems. We base the model on a tree-like structure. It breaks down the data into small, manageable chunks while incrementally developing a decision tree. The outcome is a tree-like structure with decision nodes and leaf nodes. We consider it a greedy model since its primary ...