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The Machine Learning Workshop

You're reading from   The Machine Learning Workshop Get ready to develop your own high-performance machine learning algorithms with scikit-learn

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839219061
Length 286 pages
Edition 2nd Edition
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Author (1):
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Hyatt Saleh Hyatt Saleh
Author Profile Icon Hyatt Saleh
Hyatt Saleh
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Toc

The Decision Tree Algorithm

The decision tree algorithm performs classification based on a sequence that resembles a tree-like structure. It works by dividing the dataset into small subsets that serve as guides to develop the decision tree nodes. The nodes can be either decision nodes or leaf nodes, where the former represent a question or decision, and the latter represent the decisions made or the final outcome.

How Does the Decision Tree Algorithm Work?

Considering what we just mentioned, decision trees continually split the dataset according to the parameters defined in the decision nodes. Decision nodes have branches coming out of them, where each decision node can have two or more branches. The branches represent the different possible answers that define the way in which the data is split.

For instance, consider the following table, which shows whether a person has a pending student loan based on their age, highest education, and current income:

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