Summary

This chapter taught you how to apply conformal prediction to time series forecasting. Conformal prediction is a powerful technique for crafting PIs for point forecasting models.

This chapter also offered insights into how to harness this method using open source platforms.

We began by exploring UQ in a time series, delving into the significance of PIs, and showcasing various strategies to generate them.

The concept of conformal prediction and its application in forecasting scenarios was central to this chapter. At this point, you are equipped with the knowledge to apply these methodologies in real-world settings, empowering your forecasting models with precise uncertainty bounds. Adding confidence measures to predictions ensures that the forecasts are accurate and reliable.

With a solid understanding of conformal prediction for time series, we will now focus on another critical application area – computer vision.