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
Hi Alp,
- even with correctly programmed back-propagation, it is usually hard to
make the net converge.
- usually you initialize neuron weights with somewhat random values, when
working with back-propagation.
- do some debug prints of the net error while training to see how it is
going
- xor
On Mon, Jun 15, 2009 at 5:00 PM, Trin Trin trin...@gmail.com wrote:
Hi Alp,
- even with correctly programmed back-propagation, it is usually hard to
make the net converge.
Yeah, I know, that's why we're training it until the quadratic error goes
under 0.1.
- usually you initialize neuron
