Prediction bias is the difference between the average of a model’s predictions and the average of the corresponding labels. It is a diagnostic signal about systematic overprediction or underprediction and is distinct from ethical bias or a model’s bias parameter.
A value indicating how far apart the average of
predictions is from the average of labels
in the dataset.
Not to be confused with the bias term in machine learning models
or with bias in ethics and fairness.