Dear Frauke, Thank you very much for taking the time to respond.
You explanation was very helpful, and I now have that part figured out! Best Wishes, Dan Frauke Message: 3 Date: Mon, 12 Oct 2020 08:33:44 +0200 (CEST) From: =?UTF-8?Q?Frauke_G=C3=BCnther?= <guent...@leibniz-bips.de> To: "r-help@r-project.org" <r-help@r-project.org> Cc: William Michels <w...@caa.columbia.edu>, "s...@posteo.org" <s...@posteo.org> Subject: Re: [R] Fwd: Help using the exclude option in the neuralnet package Message-ID: <957726669.124476.1602484424...@srvmail.bips.eu> Content-Type: text/plain; charset="utf-8" Dear all, the exclude and constant.weights options are used as follows: exclude: A matrix with n rows and 3 columns will exclude n weights. The the first column refers to the layer, the second column to the input neuron and the third column to the output neuron of the weight. constant.weights: A vector specifying the values of the weights that are excluded from the training process and treated as fix. Please refer to the following example: Not using exclude and constant.weights (all weights are trained): > nn <- neuralnet(Species == "setosa" ~ Petal.Length + Petal.Width, > iris, linear.output = FALSE) > > nn$weights [[1]] [[1]][[1]] [,1] [1,] 6.513239 [2,] -0.815920 [3,] -5.859802 [[1]][[2]] [,1] [1,] -4.597934 [2,] 9.179436 Using exclude (2 weights are excluded --> NA): > nn <- neuralnet(Species == "setosa" ~ Petal.Length + Petal.Width, > iris, linear.output = FALSE, exclude = matrix(c(1,2,1, 2,2,1),byrow=T, nrow=2)) > nn$weights [[1]] [[1]][[1]] [,1] [1,] -0.2815942 [2,] NA [3,] 0.2481212 [[1]][[2]] [,1] [1,] -0.6934932 [2,] NA Using exclude and constant.weights (2 weights are excluded and treated as fix --> 100 and 1000, respectively): > nn <- neuralnet(Species == "setosa" ~ Petal.Length + Petal.Width, > iris, linear.output = FALSE, exclude = matrix(c(1,2,1, 2,2,1),byrow=T, nrow=2), constant.weights=c(100,1000)) > nn$weights [[1]] [[1]][[1]] [,1] [1,] 0.554119 [2,] 100.000000 [3,] 1.153611 [[1]][[2]] [,1] [1,] -0.3962524 [2,] 1000.0000000 I hope you will find this example helpful. Sincerely, Frauke > William Michels <w...@caa.columbia.edu mailto:w...@caa.columbia.edu > hat > am 10.10.2020 18:16 geschrieben: > > > Forwarding: Question re "neuralnet" package on the R-Help mailing list: > > https://stat.ethz.ch/pipermail/r-help/2020-October/469020.html > > If you are so inclined, please reply to: > > r-help@r-project.org mailto:r-help@r-project.org > <r-help@r-project.org mailto:r-help@r-project.org > > > ---------- Forwarded message --------- > From: Dan Ryan <dan.r...@unbc.ca mailto:dan.r...@unbc.ca > > Date: Fri, Oct 9, 2020 at 3:52 PM > Subject: Re: [R] Help using the exclude option in the neuralnet package > To: r-help@r-project.org mailto:r-help@r-project.org > <r-help@r-project.org mailto:r-help@r-project.org > > > Good Morning, > > I am using the neuralnet package in R, and am able to produce some > basic neural nets, and use the output. > > I would like to exclude some of the weights and biases from the > iteration process and fix their values. > > However I do not seem to be able to correctly define the exclude and > constant.weights vectors. > > Question: Can someone point me to an example where exclude and > contant.weights are used. I have search the R help archive, and > haven't found any examples which use these on the web. > > Thank you in advance for any help. > > Sincerely > > Dan > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailto:R-help@r-project.org mailing list -- To > UNSUBSCRIBE and more, see > 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. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.