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Forecasting Time Series Data with Prophet

You're reading from   Forecasting Time Series Data with Prophet Build, improve, and optimize time series forecasting models using Meta's advanced forecasting tool

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781837630417
Length 282 pages
Edition 2nd Edition
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Author (1):
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Greg Rafferty Greg Rafferty
Author Profile Icon Greg Rafferty
Greg Rafferty
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Table of Contents (20) Chapters Close

Preface 1. Part 1: Getting Started with Prophet
2. Chapter 1: The History and Development of Time Series Forecasting FREE CHAPTER 3. Chapter 2: Getting Started with Prophet 4. Chapter 3: How Prophet Works 5. Part 2: Seasonality, Tuning, and Advanced Features
6. Chapter 4: Handling Non-Daily Data 7. Chapter 5: Working with Seasonality 8. Chapter 6: Forecasting Holiday Effects 9. Chapter 7: Controlling Growth Modes 10. Chapter 8: Influencing Trend Changepoints 11. Chapter 9: Including Additional Regressors 12. Chapter 10: Accounting for Outliers and Special Events 13. Chapter 11: Managing Uncertainty Intervals 14. Part 3: Diagnostics and Evaluation
15. Chapter 12: Performing Cross-Validation 16. Chapter 13: Evaluating Performance Metrics 17. Chapter 14: Productionalizing Prophet 18. Index 19. Other Books You May Enjoy

Summary

In this chapter, you learned that the models we built in the first few chapters of this book all featured linear growth. You learned that the logistic function was developed to model population growth and then learned how to implement this in Prophet by modeling the growth of the wolf population in Yellowstone after their reintroduction in 1995.

Logistic growth in Prophet can be modeled as either increasing up to a saturation limit called the cap or decreasing to a saturation limit called the floor. Finally, you learned how to model flat (or no growth) trends, where the trend is fixed to one value for the entire data period but seasonality is still allowed to vary. Throughout this chapter, you used the add_changepoints_to_plot function in order to overlay the trend line on your forecast plots.

Choosing the correct growth mode is important, particularly so when forecasting further into the future. We looked at a couple of examples in this chapter where the incorrect growth...

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