[Haskell-cafe] Backpropagation implementation for a neural net library

[Alp Mestan]

Dear List,

I'm working with a friend of mine on a Neural Net library in Haskell.

There are 3 files : neuron.hs, layer.hs and net.hs.
neuron.hs defines the Neuron data type and many utility functions, all of
which have been tested and work well.
layer.hs defines layer-level functions (computing the output of a whole
layer of neurons, etc). Tested and working.
net.hs defines net-level functions (computing the output of a whole neural
net) and the famous -- but annoying -- back-propagation algorithm.

You can find them there : http://mestan.fr/haskell/nn/html/

The problem is that here when I ask for final_net or test_output (anything
after the train call, in net.hs), it seems to loop and loop around, as if it
never gets the error under 0.1.

So I was just wondering if there was one or more Neural Nets and Haskell
wizard in there to check the back-propagation implementation, given in
net.hs, that seems to be wrong.

Thanks a lot !

-- 
Alp Mestan
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