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 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]]
>
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--
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University
Looking to arrange a meeting? Check my public calendar:
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~ Certainty is folly... I think. ~
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and provide commented, minimal, self-contained, reproducible code.