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The Unsupervised Learning Workshop

You're reading from   The Unsupervised Learning Workshop Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800200708
Length 550 pages
Edition 1st Edition
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Authors (3):
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Benjamin Johnston Benjamin Johnston
Author Profile Icon Benjamin Johnston
Benjamin Johnston
Christopher Kruger Christopher Kruger
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Christopher Kruger
Aaron Jones Aaron Jones
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Aaron Jones
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Toc

Table of Contents (11) Chapters Close

Preface
1. Introduction to Clustering 2. Hierarchical Clustering FREE CHAPTER 3. Neighborhood Approaches and DBSCAN 4. Dimensionality Reduction Techniques and PCA 5. Autoencoders 6. t-Distributed Stochastic Neighbor Embedding 7. Topic Modeling 8. Market Basket Analysis 9. Hotspot Analysis Appendix

The Organization of the Hierarchy

Both the natural and human-made world contain many examples of organizing systems into hierarchies and why, for the most part, it makes a lot of sense. A common representation that is developed from these hierarchies can be seen in tree-based data structures. Imagine that you have a parent node with any number of child nodes that can subsequently be parent nodes themselves. By organizing information into a tree structure, you can build an information-dense diagram that clearly shows how things are related to their peers and their larger abstract concepts.

An example from the natural world to help illustrate this concept can be seen in how we view the hierarchy of animals, which goes from parent classes to individual species:

Figure 2.2: The relationships of animal species in a hierarchical tree structure

In the preceding diagram, you can see an example of how relational information between varieties of animals can be...

You have been reading a chapter from
The Unsupervised Learning Workshop
Published in: Jul 2020
Publisher: Packt
ISBN-13: 9781800200708
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