Neural Network Implementation in SAS
Warren S. Sarle · 1994
The estimation or training methods in the neural network literature are usually some simple form of gradient descent algorithm suitable for implementation in hardware using massively parallel computations. For ordinary computers that are not massively parallel, optimization algorithms such as those in several SAS procedures are usually far more efficient. This talk shows how to fit neural networks using SAS/OR R , SAS/ETS R , and SAS/STAT R software.