Projected random forests and conformal prediction of circular data
The episode discusses a paper titled "Projected random forests and conformal prediction of circular data." The hosts explain how to apply machine learning to cyclical data, such as wind direction. They detail a method using projected random forests and out-of-bag predictions to provide precise, reliable prediction intervals for real-world applications.