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Predictive Analytics Using Rattle and Qlik Sense

You're reading from  Predictive Analytics Using Rattle and Qlik Sense

Product type Book
Published in Jun 2015
Publisher
ISBN-13 9781784395803
Pages 242 pages
Edition 1st Edition
Languages
Authors (2):
Ferran Garcia Pagans Ferran Garcia Pagans
Profile icon Ferran Garcia Pagans
Fernando G Pagans Fernando G Pagans
Profile icon Fernando G Pagans
View More author details

Table of Contents (16) Chapters

Predictive Analytics Using Rattle and Qlik Sense
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Getting Ready with Predictive Analytics 2. Preparing Your Data 3. Exploring and Understanding Your Data 4. Creating Your First Qlik Sense Application 5. Clustering and Other Unsupervised Learning Methods 6. Decision Trees and Other Supervised Learning Methods 7. Model Evaluation 8. Visualizations, Data Applications, Dashboards, and Data Storytelling 9. Developing a Complete Application Index

Summary


In this chapter, we saw different ways of analyzing the performance of supervised models. We started with regression model evaluation and then we moved on to classification models performance.

For regression models, we saw that the difference between predicted values and actual values is the most important measure. In this way, Rattle provides the Predicted versus Observed Plot.

We discovered that in classification, a false positive is different from a false negative. Based on this difference, we can create a confusion matrix and evaluate the performance of a classifier using different mechanisms such as a Risk Chart, or ROC Curve.

In this chapter, we've worked with Rattle because it provides the necessary tools to evaluate the performance of a model developed with it. In the next chapter, we'll come back to Qlik Sense to learn the key concepts of data visualization and learn how to communicate with data.

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