In the cоntext оf crоss-vаlidаtion for regulаrized regression, the leave-one-out cross-validation (LOOCV) score can be approximated by the sum of the training risk and a complexity penalty similar to that used in the Akaike Information Criterion (AIC), with the variance estimated from the submodel.