Accounting for Underspecification in Statistical Claims of Model Superiority
NeutralArtificial Intelligence
Recent discussions in machine learning highlight concerns about the statistical robustness of reported improvements in medical imaging. Many small performance gains may actually be false positives, largely due to the issue of underspecification, where models with similar validation scores can perform differently on unseen data.
— Curated by the World Pulse Now AI Editorial System
