Conformal prediction interval for dynamic time-series
Published in
International Conference on Machine Learning(2020)External Links:
TL
TL;DR
A method to build distribution-free prediction intervals for time-series based on conformal inference that wraps around any ensemble estimator to construct sequential prediction intervals is developed, which is easy to implement, scalable to producing arbitrarily many prediction intervals sequentially, and well-suited to a wide range of regression functions.