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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

Introduction

In the preceding chapter, we explored market basket analysis. Market basket analysis, as you hopefully recall, is an algorithm that seeks to understand the relationships between all the items and groups of items in transaction data. These relationships are then leveraged to help retailers optimize store layouts, more accurately order inventory, and adjust prices without shrinking the number of items in each transaction. We now change directions to explore hotspot modeling.

Let's consider an imaginary scenario: a new disease has begun spreading through numerous communities in the country that you live in and the government is trying to figure out how to confront this health emergency. Critical to any plan to confront this health emergency is epidemiological knowledge, including where the patients are located and how the disease is moving. The ability to locate and quantify problem areas (which are classically referred to as hotspots) can help health professionals...

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