I am using nnet package in R for training Artificial Neural Network. Some tell that weights are assigned to each case in training set, and some say that no. of weights are equal to the no. of connections in structure of neural network. I didn't understand this. Can anybody help me out.
I looked at the R code of nnet i.e.
What is the difference between weights & Wts in the nnet code below?
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, ...)