Since SAS Enterprise Miner was designed for very large data sets which often are fraught with problems such as missing values, there are several classical statistical techniques that are not calculated in SAS Enterprise Miner. In some cases, it is just not possible to compute those metrics for the number of observations in a typical data mining data set.
Instead of relying on those metrics, you can usually validate your model on holdout data in data mining. Candidate models are trained on a portion of the data and the best model can be chosen based on its performance on the holdout data. This would not work for classical methods for which data is often quite limited.
I hope this helps!
Doug
