MACEst

2000년 도입 · 논문 1편에서 사용

Model Agnostic Confidence Estimator, or MACEst, is a model-agnostic confidence estimator. Using a set of nearest neighbours, the algorithm differs from other methods by estimating confidence independently as a local quantity which explicitly accounts for both aleatoric and epistemic uncertainty. This approach differs from standard calibration methods that use a global point prediction model as a starting point for the confidence estimate.

출처: MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator

소개 논문: MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator