brshallo / handling-uncertainty-predictions-slides

Slides for User2022 Elevator pitch

Handling Uncertainty in Predictions (UseR! 2022, pitch)

.pdf of slides for UseR! 2022 elevator pitch on "Handling Uncertainty in Predictions, Approaches to Building Prediction Intervals Within a tidymodels Framework"

The .pptx of the slides (including a rough script in the notes can be found here.)

The pitch was primarily a set-up for my series of posts from last year on building prediction intervals in the tidymodels ecosystem, which can be found at my blog.

• Part 1: Understanding Prediction Intervals
• Part 2: Simulating Prediction Intervals
• Part 3: Quantile Regression Forests for Prediction Intervals

Abstract

In many settings your predictive model must output a range rather than just a point estimate. Three common approaches for outputting prediction intervals are to use...

1. a parametric method where the prediction intervals are solved for analytically
2. a simulation or conformal inference based approach
3. a method that outputs quantiles

In this elevator pitch, I will briefly walk through examples of how you can do each from within the tidymodels ecosystem. (See bryanshalloway.com for more detailed written examples.)