 A small value of Cp means that the model is relatively precise.Mallows’s "Cp" has been shown to be equivalent to Akaike information criterion in the special case of Gaussian linear regression.Mallows’s "Cp" addresses the issue of overfitting, in which model selection statistics such as the residual sum of squares always get smaller as more variables are added to a model.