Greetings list, I am new to programming in R, and am using nnet() function for a project on neural networking.
Firslty i widh to ask if there is any pdf explaining the algorithm nnet uses, which could tell me what the objects of the nnet class, like 'conn', 'nconn, 'nsunits', n and 'nunits' mean, and how weights are calculated. The package odf has little or no explanations, and the C +R surce code availabe at CRAN is too difficult to comprehend. Can anyone please help? Also, i wish to know how the *number* of wieghts is calculated. when the nnet() command is run, it ouputs, on the console, the number of weights, and values of 'value'. But how do you calculate the bnumber of weights in nnet, say, if you are feeding it an MxN inputs dataframe (i.e. M observations, each having N inputs, like the iris dataset has M=150 and N=4), and getting, say, x number of outouts for each observation? Thank you, Hafsa -- View this message in context: http://r.789695.n4.nabble.com/R-What-training-algorithm-does-nnet-package-use-tp813206p3632339.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
