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You can try something like this:
http://pubs.acs.org/doi/abs/10.1021/ci050022a
Basically similar idea to what is done in random forests: permute predictor
variable one at a time and see how much that degrades prediction performance.
Cheers,
Andy
-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Giulia Di Lauro
Sent: Wednesday, December 04, 2013 6:42 AM
To: r-help at r-project.org
Subject: [R] Variable importance - ANN
Hi everybody,
I created a neural network for a regression analysis with package ANN, but
now I need to know which is the significance of each predictor variable in
explaining the dependent variable. I thought to analyze the weight, but I
don't know how to do it.
Thanks in advance,
Giulia Di Lauro.
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
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If you are using the nnet package, the caret package has a variable importance method based on Gevrey, M., Dimopoulos, I., & Lek, S. (2003). Review and comparison of methods to study the contribution of variables in artificial neural network models. Ecological Modelling, 160(3), 249-264. It is based on the estimated weights. Max On Wed, Dec 4, 2013 at 6:41 AM, Giulia Di Lauro <giulia.dilauro@gmail.com>wrote:> Hi everybody, > I created a neural network for a regression analysis with package ANN, but > now I need to know which is the significance of each predictor variable in > explaining the dependent variable. I thought to analyze the weight, but I > don't know how to do it. > > Thanks in advance, > Giulia Di Lauro. > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. >-- Max [[alternative HTML version deleted]]