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I want to create a neural network, and then everytime it receives new data, instead of creating a new nnet, i want to use a backpropagation algorithm to adjust the weights in the already created nn. I'm using nnet package, I know that nn$wts gives the weights, but I cant find out which weights belong to which conections so I could implement the backpropagation algorithm myself. But if anyone

Hi, I'm currently trying desperately to get the nnet function for training a neural network (with one hidden layer) to perform a regression task. So I run it like the following: trainednet <- nnet(x=traindata, y=trainresponse, size = 30, linout = TRUE, maxit=1000) (where x is a matrix and y a numerical vector consisting of the target values for one variable) To see whether the network

Hi all, I am trying to write an application to monitor queues using the Asterisk Management API. So far I have had some level of sucess, basically reverse engineering the protocol and the event messages using ethereal etc. I know there are a couple of pages on the Wiki that attempt (no dis-respect to who ever did it as it has been a great help) to document the API and was wondering if there