TR Available: The Use of Cross-Validation in Neural Network

[Christopher Gordon]

I apologize to anyone who tried to unsuccesfully uncompress the file 
gordon.extrapolation.ps.Z which is advertized below. It was compressed with 
gzip not unix compress. gzip can be used to uncompress it. I will be replacing 
it with a unix compressed version as soon as possible. I will post another message 
when I have do so. 


> FTP-host: archive.cis.ohio-state.edu
> FTP-filename: /pub/neuroprose/gordon.extrapolation.ps.Z
> 
> --------------------------------------------------------------------
> 
> The following 12 page paper is now available by ftp:
> 
> The Use of Cross-Validation in Neural Network
> Extrapolation of Forest Tree Growth.
> 
> C. Gordon, University of the Witwatersrand.
> 
> Presented at PRASA (1994).
> 
> Abstract:
> A back-propagation multilayer Artificial Neural 
> Network (ANN) is used to model the mean growth
> rate of different plots of Pine trees.
> Cross-validation is found to be essential in 
> providing a good extrapolation. Predictions are 
> made for different plots which have different 
> initial densities and different artificial thinning
> regimes. Comparisons are made  with a
> standard nonlinear regression solution.
> 
> 
> * FTP procedure:
>  unix> ftp archive.cis.ohio-state.edu (or 128.146.8.52)
>  Name: anonymous
>  Password: (email address) 
>  ftp> cd pub/neuroprose
>  ftp> binary
>  ftp> get gordon.extrapolation.ps.Z
>  ftp> quit
 



 ******************************************************************
* Christopher Gordon                                               *
* Department of Applied Maths                                      *  
* University of the Witwatersrand                                  *  
* Internet : CHRIS at gauss.cam.wits.ac.za                                 *
* Snail Mail : PO Box 65684, Benmore 2010, South Africa            *
* Tel: (011)716-3229(W)                                           *
*                                                                  * 
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