Confidence Estimators
MACEst
Introduced by Green et al. in MACEst: The reliable and trustworthy Model Agnostic Confidence EstimatorModel 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.
Source: MACEst: The reliable and trustworthy Model Agnostic Confidence Estimator
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
