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Machine Learning with Qlik Sense

You're reading from   Machine Learning with Qlik Sense Utilize different machine learning models in practical use cases by leveraging Qlik Sense

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781805126157
Length 242 pages
Edition 1st Edition
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Author (1):
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Hannu Ranta Hannu Ranta
Author Profile Icon Hannu Ranta
Hannu Ranta
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Table of Contents (17) Chapters Close

Preface 1. Part 1:Concepts of Machine Learning
2. Chapter 1: Introduction to Machine Learning with Qlik FREE CHAPTER 3. Chapter 2: Machine Learning Algorithms and Models with Qlik 4. Chapter 3: Data Literacy in a Machine Learning Context 5. Chapter 4: Creating a Good Machine Learning Solution with the Qlik Platform 6. Part 2: Machine learning algorithms and models with Qlik
7. Chapter 5: Setting Up the Environments 8. Chapter 6: Preprocessing and Exploring Data with Qlik Sense 9. Chapter 7: Deploying and Monitoring Machine Learning Models 10. Chapter 8: Utilizing Qlik AutoML 11. Chapter 9: Advanced Data Visualization Techniques for Machine Learning Solutions 12. Part 3: Case studies and best practices
13. Chapter 10: Examples and Case Studies 14. Chapter 11: Future Direction 15. Index 16. Other Books You May Enjoy

Monitoring and debugging models

Debugging a model during development is a crucial development step. With Advanced Analytics Integration in on-premises environments, we have several options to debug our model and figure out how it is performing.

The first and most logical place to start debugging in an interactive scenario is to look at the chart output. If there is something wrong with the code, you will get an error message here. In the following example, we can see that a library called forecast is missing from the environment:

Figure 7.8: Error message in chart

Figure 7.8: Error message in chart

Sometimes, you may need more comprehensive information or debug prints from the actual R code. Since R is running as a service, there is no easy way to get debug prints during execution. You can, however, use file writing. Returning to our previous Rserve example, adding the following code will produce a file called debug.txt in our Rserve home folder (the added code is shown in bold):

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