R help - Mar 2009 - find the important inputs to the neural network model in "nnet" package

Hi, I have a binary variable and many explanatory variables and I want to 
use the package "nnet"  to model these data, (instead of logistic
regression).
I want to find the more effective  variables (inputs to the network) in 
the neural network model. how can I do this?
thanks.



      
	[[alternative HTML version deleted]]

One thought is to train the net and obtain a performance measure on a
testing corpus. Next, for each input, run the testing corpus again,
but zero all values for that input and obtain a measure of
performance. Zeroing an important node will hurt performance more than
zeroing an unimportant node.

On Tue, Mar 10, 2009 at 9:41 AM, abbas tavassoli <tavassoli_85 at
yahoo.com> wrote:
>
> Hi, I have a binary variable and many explanatory variables and I want to
> use the package "nnet" ?to model these data, (instead of logistic
regression).
> I want to find the more effective ?variables (inputs to the network) in
> the neural network model. how can I do this?
> thanks.
>
>
>
>
> ? ? ? ?[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at 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.
>


-- 
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University

Looking to arrange a meeting? Check my public calendar:
http://tinyurl.com/mikes-public-calendar

~ Certainty is folly... I think. ~