momentum factor

The momentum factor, alpha, is the learning coefficient used by Qnet’s training algorithms. The momentum factor damps high frequency weight changes and helps with overall algorithm stability, while still promoting fast learning. For the majority of networks, alpha can be set in the 0.8 to 0.9 range and left there. However, there is no definitive rule regarding alpha. Some networks may train better with alpha values set at a lower level. Some networks train well with no alpha term used at all (set to 0). It is most common to use higher momentum values, since the damping effect usually helps training characteristics. If training problems occur with a given alpha value, it may be useful to experiment with different values.

The momenum factor can be set in the Training Setup/Training Parameters dialog.