On 15 Oct 2003 at 14:35, Tokuyasu, Taku wrote: There is an argument to nnet setting the maximum number of weights. Default is 1000. I have successfully used this. Try ?nnet and read carefully!
Kjetil Halvorsen > I am using library(nnet) to train up an ANN with what I believe is a > moderately sized dataset, but R is complaining about too many weights: > > --- > > nn.1 <- nnet(t(data), targets, size = 4, rang = 0.1, decay = 5e-4, maxit = > 200) > Error in nnet.default(t(data), targets, size = 4, rang = 0.1, decay = 5e-04, > : > Too many (1614) weights > > dim(targets) > [1] 146 2 > > dim(data) ## Note I'm using the transpose as input > [1] 400 146 > --- > > Is there a way around this? Pointers to relevant docs/code or the source of > the problem would be greatly appreciated. > > Thanks, > > _Taku > > --- > Taku A. Tokuyasu, PhD > UCSF Cancer Center, Box 0128 > San Francisco, CA 94143-0128 > Tel: (415) 514-1530 Fax: (415) 502-3179 > Email: [EMAIL PROTECTED] > > > > [[alternative HTML version deleted]] > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://www.stat.math.ethz.ch/mailman/listinfo/r-help ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
