nnet abstol
From the help page:
abstol: Stop if the fit criterion falls below 'abstol', indicating an
essentially perfect fit.
Now, what the `fit criterion' is depends on the other options that you
have not told us, but I don't see MSE mentioned anywhere on that help
page, and I do see `least-squares'.
On Wed, 9 Mar 2005, Kemp S E (Comp) wrote:
Hi, I am using nnet to learn transfer functions. For each transfer function I can estimate the best possible Mean Squared Error (MSE). So, rather than trying to grind the MSE to 0, I would like to use abstol to stop training once the best MSE is reached. Can anyone confirm that the abstol parameter in the nnet function is the MSE, or is it the Sum-of-Squares (SSE)?
Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595