Approximating function with Neural Network

The following scirits are stolen from one of the stackoverflow anwser to Approximating function with Neural Network

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set.seed(1405)
x <- sort(10*runif(50))
y <- sin(x) + 0.2*rnorm(x)
nn <- nnet(x, y, size=6, maxit=40, linout=TRUE)

# weights:  19
initial  value 22.620862 
iter  10 value 19.387017
iter  20 value 12.562669
iter  30 value 2.542834
iter  40 value 1.196062
final  value 1.196062 
stopped after 40 iterations

plot(x, y)
plot(sin, 0, 10, add=TRUE)

x1 <- seq(0, 10, by=0.1)
lines(x1, predict(nn, data.frame(x=x1)), col="green")

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