Numerical Machine Learning

Decision Tree

Author(s): Zhiyuan Wang*, Sayed Ameenuddin Irfan*, Christopher Teoh* and Priyanka Hriday Bhoyar *

Pp: 97-115 (19)

DOI: 10.2174/9789815136982123010006

* (Excluding Mailing and Handling)


In this chapter, we explore the concept of decision trees, prioritizing accessibility by minimizing abstract mathematical theories. We examine a concrete numerical example using a small dataset to predict the suitability of playing tennis based on weather conditions, guiding readers through the process step-by-step. Moreover, we provide sample codes and compare them with the decision tree classification model found in the scikit-learn library. Upon completing this chapter, readers will have gained a comprehensive understanding of the inner workings of decision tree machine learning, the relationship between the underlying principles, and the implementation and performance of the algorithm, preparing them to apply their knowledge to practical scenarios. 

Keywords: Decision Tree, Classification, Numerical Example, Small Dataset, Scikit-Learn

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