Hello there, Yes, I'd tried scale as well. I mean, I could do my preprocessing separately and it was working fine. I was just wondering how preProcess argument in train function works. As far as I know, when preProcess argument is set, it normalizes inputs but not outputs.
Then I've figured we could also use recipes and that normalizes both predictors and outcomes as you wish. Here <https://stackoverflow.com/questions/59126400/how-does-setting-preprocess-argument-in-train-function-in-caret-work?noredirect=1#comment104528951_59126400> you can take a look at the question I've asked on SO. You can see the use of recipe in comments below by "missuse". I will read the link you've shared as well. Thank you, Burak William Michels <w...@caa.columbia.edu>, 4 Ara 2019 Çar, 21:04 tarihinde şunu yazdı: > Hello, > > Have you tried alternative methods of pre-processing your data, such > as simply calling scale()? What is the effect on convergence, for both > the caret package and and the neuralnet package? There's an example > using scale() with the neuralnet package at the link below: > > https://datascienceplus.com/fitting-neural-network-in-r/ > > HTH, Bill. > > W. Michels, Ph.D. > > > > On Sun, Dec 1, 2019 at 10:04 AM Burak Kaymakci <burakayma...@gmail.com> > wrote: > > > > Hello there, > > > > I am using caret and neuralnet to train a neural network to predict times > > table. I am using 'backprop' algorithm for neuralnet to experiment and > > learn. > > > > Before using caret, I've trained a neuralnet without using caret, I've > > normalized my input & outputs using preProcess with 'range' method. Then > I > > predicted my test set, did the multiplication and addition on predictions > > to get the real values. It gave me good results. > > > > What I want to ask is, when I try to train my network using caret, I get > an > > error saying algorithm did not converge. I am thinking that I might be > > doing something wrong with my pre-processing, > > > > How would I go about using preProcess in train? > > Do I pass my not-normalized data set to the train function and train > > function handles normalization internally? > > > > You can find my R gist here > > <https://gist.github.com/andreyuhai/f299282f5a827e2a27c586afc9eb4eb5> > > > > Thank you, > > Burak > > ______________________________________________ > > 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.
