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Advanced Analytics with R and Tableau

You're reading from  Advanced Analytics with R and Tableau

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781786460110
Pages 178 pages
Edition 1st Edition
Languages
Authors (3):
Ruben Oliva Ramos Ruben Oliva Ramos
Profile icon Ruben Oliva Ramos
Jen Stirrup Jen Stirrup
Profile icon Jen Stirrup
Roberto Rösler Roberto Rösler
View More author details

Table of Contents (16) Chapters

Advanced Analytics with R and Tableau
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Advanced Analytics with R and Tableau 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

Modeling and evaluating data in Tableau


Neural networks are often difficult to understand. When the data is loaded into Tableau, we can visually understand the distinctions made by the underlying model. Since we can easily load data into Tableau, we can do this on an ongoing basis.

In this example, we will use Tableau as part of the testing process. We will present the model with data, and see how well the R model can distinguish between the three types of iris. Once we have set up the Tableau workbook, we can load more data into the workbook, using the connect to data facility. This would help us to see if the model continues to distinguish between the model types, and we could continue to test the model on an ongoing basis.

Using Tableau to evaluate data

Let's load more data into Tableau. For our testing purposes, we will reuse the iris data that we used in the earlier example. However, if this was real life, this would not be the best practice for testing purposes. Here, we are reusing the...

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