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Forecasting Time Series Data with Facebook Prophet

You're reading from  Forecasting Time Series Data with Facebook Prophet

Product type Book
Published in Mar 2021
Publisher Packt
ISBN-13 9781800568532
Pages 270 pages
Edition 1st Edition
Languages
Author (1):
Greg Rafferty Greg Rafferty
Profile icon Greg Rafferty

Table of Contents (18) Chapters

Preface 1. Section 1: Getting Started
2. Chapter 1: The History and Development of Time Series Forecasting 3. Chapter 2: Getting Started with Facebook Prophet 4. Section 2: Seasonality, Tuning, and Advanced Features
5. Chapter 3: Non-Daily Data 6. Chapter 4: Seasonality 7. Chapter 5: Holidays 8. Chapter 6: Growth Modes 9. Chapter 7: Trend Changepoints 10. Chapter 8: Additional Regressors 11. Chapter 9: Outliers and Special Events 12. Chapter 10: Uncertainty Intervals 13. Section 3: Diagnostics and Evaluation
14. Chapter 11: Cross-Validation 15. Chapter 12: Performance Metrics 16. Chapter 13: Productionalizing Prophet 17. Other Books You May Enjoy

Chapter 7: Trend Changepoints

During the development of Prophet, the engineering team recognized that real-world time series will frequently exhibit abrupt changes in their trajectories. As a fundamentally linear regression model, Prophet would not be capable of capturing these changes without special care being taken. You may have noticed in the previous chapters, however, that when we plotted the forecast components in our examples, the trend line was not always perfectly straight. Clearly, the Prophet team has developed a way for Prophet to capture these bends in the linear model. The locations of these bends are called changepoints.

Prophet will automatically identify these changepoints and allow the trend to adapt appropriately. However, there are several tools you can use to control this behavior if Prophet is underfitting or overfitting these rate changes. In this chapter, we'll look at Prophet's automatic changepoint detection to provide you with an understanding...

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