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Advanced Analytics with R and Tableau

You're reading from   Advanced Analytics with R and Tableau Advanced analytics using data classification, unsupervised learning and data visualization

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781786460110
Length 178 pages
Edition 1st Edition
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Authors (3):
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Roberto Rösler Roberto Rösler
Author Profile Icon Roberto Rösler
Roberto Rösler
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
Jen Stirrup Jen Stirrup
Author Profile Icon Jen Stirrup
Jen Stirrup
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Table of Contents (10) Chapters Close

Preface 1. Advanced Analytics with R and Tableau FREE CHAPTER 2. The Power of R 3. A Methodology for Advanced Analytics Using Tableau and R 4. Prediction with R and Tableau Using Regression 5. Classifying Data with Tableau 6. Advanced Analytics Using Clustering 7. Advanced Analytics with Unsupervised Learning 8. Interpreting Your Results for Your Audience Index

Finding clusters in data


Cluster analysis partitions marks in the view into clusters, where the marks within each cluster are more similar to one another than they are to marks in other clusters.

In Tableau Desktop, you create clusters by dragging Cluster from the Analytics pane and dropping it in the view. Now you will see that there is a statistical object. Here, Tableau places it on the Color shelf. Note that, if there is already a field on Color, Tableau moves that field to Detail and replaces it on Color with the clustering results.

Using clustering, Tableau assigns each mark to one of the clusters on the canvas. If any of the marks do not fit well in one of the clusters, then it is put into a not clustered cluster.

Clustering has its own dialog box, which allows you to add a cluster, or edit a cluster that exists already. The clustering dialog box gives you a lot of flexibility and control over the clustering process, whilst also giving you the ability to use suggested features. For example...

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