A review of predictive uncertainty estimation with machine learning

arXiv:2209.08307v2 Announce Type: replace-cross
Abstract: Predictions and forecasts of machine learning models should take the form of probability distributions, aiming to increase the quantity of information communicated to end users. Although applications of probabilistic prediction and forecasting with machine learning models in academia and industry are becoming more frequent, related concepts and methods have not been formalized and structured under a holistic view of the entire field. Here, we review the topic of predictive uncertainty estimation with machine learning algorithms, …

abstract academia applications arxiv concepts cs.lg end users forecasting form industry information machine machine learning machine learning models math.st prediction predictions predictive probability review stat.ml stat.th type uncertainty