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The Supervised Learning Workshop - Second Edition

You're reading from  The Supervised Learning Workshop - Second Edition

Product type Book
Published in Feb 2020
Publisher Packt
ISBN-13 9781800209046
Pages 532 pages
Edition 2nd Edition
Languages
Authors (4):
Blaine Bateman Blaine Bateman
Profile icon Blaine Bateman
Ashish Ranjan Jha Ashish Ranjan Jha
Profile icon Ashish Ranjan Jha
Benjamin Johnston Benjamin Johnston
Profile icon Benjamin Johnston
Ishita Mathur Ishita Mathur
Profile icon Ishita Mathur
View More author details

Classification Using Decision Trees

Another powerful classification method that we will be examining in this chapter is decision trees, which have found particular use in applications such as natural language processing, for example. There are a number of different machine learning algorithms that fall within the overall umbrella of decision trees, such as Iterative Dichotomiser 3 (ID3) and Classification and Regression Tree (CART). In this chapter, we will investigate the use of the ID3 method in classifying categorical data, and we will use the scikit-learn CART implementation as another method of classifying the dataset. So, what exactly are decision trees?

As the name suggests, decision trees are a learning algorithm that apply a sequential series of decisions based on input information to make the final classification. Recalling your childhood biology class, you may have used a process similar to decision trees in the classification of different types of animals via dichotomous...

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