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Wednesday, July 27 • 3:40pm - 4:00pm
Introducing workboots: Generate prediction intervals from tidymodel workflows

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Sometimes, we want a model that generates a range of possible outcomes around each prediction. Other times, we just care about point predictions and may opt to use a fancy model like XGBoost. But what if we want the best of both worlds: getting a range of predictions while still using a fancy model? That’s where bootstrapping comes to the rescue! By using bootstrap resampling, we can create many models that produce a prediction distribution – regardless of the model type! In this talk, I’ll give an overview of bootstrap resampling for prediction, the pros/cons of this method, and how to implement it as a part of a tidymodel workflow with the workboots package.

Talk materials are available at https://github.com/markjrieke/rstudio-conf-2022.

avatar for Mark Rieke

Mark Rieke

Memorial Hermann Health System
I am a senior consumer experience (CX) analyst at Memorial Hermann Health System where I use R and tidymodels to provide actionable insights from patient satisfaction survey data. I love making beautiful charts, working on home improvement projects, and playing jazzy piano. I live... Read More →

Wednesday July 27, 2022 3:40pm - 4:00pm EDT
2. Potomac D