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## Default S3 method:
nnet(x, y, weights, size, Wts, mask,
linout = FALSE, entropy = FALSE, softmax = FALSE,
censored = FALSE, skip = FALSE, rang = 0.7, decay = 0,
maxit = 100, Hess = FALSE, trace = TRUE, MaxNWts = 1000,
abstol = 1.0e-4, reltol = 1.0e-8, ...)Look at MaxNWts
Cerviņo Beresi Ulises wrote:
Hello all,
Ive been playing with nnet (package 'nnet') and Ive come across this problem. nnet doesnt seems to like to have more than 1000 weights. If I do:
data(iris) names(iris)[5] <- "species" net <- nnet(species ~ ., data=iris, size=124, maxit=10)
# weights: 995 initial value 309.342009 iter 10 value 21.668435 final value 21.668435 stopped after 10 iterations
table(iris$species[], predict(net, iris[], type="class"))
setosa versicolor virginica setosa 50 0 0 versicolor 0 46 4 virginica 0 0 50
It works just fine, but if I do:
net <- nnet(species ~ ., data=iris, size=125, maxit=10)
Error in nnet.default(x, y, w, softmax = TRUE, ...) : Too many (1003) weights
Ive only changed 'size' from 124 to 125 giving me more than 1000 weights.
Any ideas? Im I doing something wrong?
version
_ platform i386-pc-linux-gnu arch i386 os linux-gnu system i386, linux-gnu status major 2 minor 0.1 year 2004 month 11 day 15 language R
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