[BioC] Neural networks.
mailinglist.honeypot at gmail.com
Thu Sep 3 16:23:01 CEST 2009
On Sep 3, 2009, at 4:40 AM, Marcus Gry wrote:
> Dear list members.
> I am trying to make a sensitivity analysis (as derived by Zurada
> 1994, Engelbrecht 1995) of input parameters (gene expression data)
> when applying a neural network to classify different cancer
> subtypes. Since I am no expert in the field, (rather a newbie), I
> wonder if there exists an implementation in R that can be used to
> measure the relative importance of the input variables for the
> neural network. I read that the sensitivity matrix is the Jacobian
> matrix of the output parameters over the input parameters. I think
> that somehow I can grasp the concept, I just don’t know how to
> implement it in R. Any help, or guidelines would be greatly
First suggestion is to check out the machine learning view on cran:
You'll see where to get a neural network implementation there from
Are you can calculate a jacobian matrix? Try searching the R-help list
You might also get more help from the general R-help mailing list ...
even though your specific application is related to biological data, I
think your questions might be better addressed there since there
somehow more general in nature.
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
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