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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

What is Clustering?


Here we represent the elbow curve and the best number of clusters on it, which are represented on the curve line:

Clustering is a way of analyzing data so that the items are grouped into similar groups, or clusters, according to their similarity. Clustering is the process of finding interesting patterns in data, and it is used to categorize and classify data into groups, as well as to distinguish groups of data from each other. Before we start to cluster the data, we don't know the cluster where each data point resides.

Clustering is an example of an unsupervised method. In unsupervised methods of machine learning, unsupervised methods are not focused on trying to predict an outcome. Instead, unsupervised methods are focused on discovering patterns in the data. Using unsupervised methods means that you can take a fresh look at the data for patterns that you may not have considered previously, such as neural networks or clustering, for example.

Clustering is a great tool...

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