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Forecasting Time Series Data with Facebook Prophet

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

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781800568532
Length 270 pages
Edition 1st 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 (18) Chapters Close

Preface 1. Section 1: Getting Started
2. Chapter 1: The History and Development of Time Series Forecasting FREE CHAPTER 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

Correcting outliers that cause seasonality swings

We'll be using a new dataset in this chapter to look at outliers: the average number of likes per day of posts on National Geographic's Instagram account, @NatGeo. This data was collected on November 21, 2019.

I've chosen this dataset because it exhibits several significant outliers, which are marked in the following plot:

Figure 9.1 – Outliers on National Geographic's Instagram account

Each dashed vertical line indicates a moment where the time series deviated significantly. The second line from the left indicates a radical trend change in the summer of 2015 but the other four lines indicate outliers, with the last two outliers spanning across wide time ranges. We'll specifically be looking at the line occurring in mid-2016, in August to be precise. This represents the most extreme outliers. The 2014 set of outliers can be safely ignored, as they do not affect the forecast...

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