Probabilistic predictions: probabilistic forecasting with sktime and probabilistic regression with skpro
Probabilistic predictions are predictions that include some statements about uncertainty of the prediction, e.g., prediction intervals that make statements about a likely range of values that a prediction can take.
This workshop gives an introduction on making probabilistic predictions with the sktime and skpro python packages, for forecasting and supervised regression. Both packages are sklearn-compatible, built using skbase, with composable and modular interfaces.
The presentation includes a practical primer of different types of probabilistic predictions, algorithms and estimators, and evaluation workflows, with python code examples.