What is a calibration layer?
A post-prediction adjustment, typically to account for prediction bias.
calibration layer explained in plain English
A post-prediction adjustment, typically to account for prediction bias. The adjusted predictions and probabilities should match the distribution of an observed set of labels.
Example
Practitioners refer to calibration layer when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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