In this release of SNNS, three model selection criteria are
implemented: the Schwarz's Bayesian criterion (SBC), Akaikes information
criterion (AIC) and the conservative mean square error of prediction (CMSEP).
The * SBC*, the default criterion, is more conservative compared to
the * AIC*. Thus, pruning via the * SBC* will produce smaller networks
than pruning via the * AIC*.
Be aware that both * SBC* and * AIC* are selection criteria for *
linear* models, whereas the * CMSEP* does not rely on any statistical
theory, but happens to work pretty well in an application. These
selection criteria for linear model can sometimes directly be applied
to nonlinear models, if the sample size is large.

Niels.Mache@informatik.uni-stuttgart.de

Tue Nov 28 10:30:44 MET 1995