© 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 ...

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