uncertainty-calibration
Uncertainty calibration techniques enhance prediction reliability in domains like computational advertising and medical diagnosis. This collection reviews parametric, non-parametric, and hybrid approaches, featuring methods such as Platt scaling and innovative models like Mix-n-Match, summarizing advancements in calibration metrics and practical applications. This resource supports research with datasets and evaluation metrics from leading tech companies and academic contributions.
