[Haskell-cafe] Neural networks and optimization in Haskell

[Tomasz Zielonka]

On 9/26/05, Joel Reymont <joelr1 at gmail.com> wrote:
>
> Folks,
>
> I got a project where I have a large number of variables and an
> outcome and I need to figure out which 20% of the variables has the
> largest effect on the outcome. Of course I also need to optimize the
> 20% of variables I end up with.
>
> This sounds like a job for a neural network to me, with arguments
> possibly optimized through genetic algorithms. I'm wondering, though,
> if I'm complicating things for myself and there's an easier approach
> to this. If not I'm wondering if there are ready-made NN or GA
> libraries for Haskell.
>
> Also, I'm curious if Haskell is really the best language for this
> type of problem and if lazy evaluation brings any specific advantages
> to the solution or would be a hindrance.


Check this paper - it seems they solved a similar problem with a
hill-climbing
algorithm:

http://www.cs.uu.nl/dazzle/f08-schrage.pdf

I would welcome any pointers and feedback, yes, someone is actually
> paying me to do this :-).
>
> Thanks, Joel
>
>
>
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