Model uncertainty The uncertainty regarding the gap between the true risk minimizer h ⋆ and the pointwise Bayes predictor f ⋆ is called model uncertainty or model bias . It stems from inadequacies of the chosen hypothesis space H and reflects our lack of knowledge about the best way to model the underlying task. Factors such as the selection of features and model architecture contribute to this uncertainty . In essence, the more domain knowledge the modeler possesses, the lower the model uncertainty is likely to be.