[R] What training algorithm does nnet package use?

[Hafsa Hassan]

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

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