f <- function(x) -cos(pi * x) / (x * exp(x))

x <- runif(100, -5, 5)
d <- f(x)
d <- d + rnorm(length(d), sd=0.5)

library(nnet)

net <- nnet(x, d, linout=TRUE, size=10, maxit=1000) # size:rétegek_száma

x2 <- seq(-5, 5, length=200)
y2 <- predict(net, matrix(x2))

plot(f, -5, 5)
title(main=expression(f(x) == frac(-cos(pi * x), x * e^x)))
points(x, d, col="blue", pch=1)
points(x2, y2, col="red", pch=4)
legend("topright",
	c("Original function", "Training data", "Neural network"),
	col=c("black", "blue", "red"),
	lty=c("solid", "blank", "blank"),
	pch=c(-1, 1,4)
)