Can you post some example code from what you were doing with NNFlex? It sounds like you've probably got an unsolvable dataset.

I'm surprised you're having a problem with the cars example, as that is usually very stable. Did you run it more than once? Backprop nets are very much dependent on the starting position, which is randomised, so it is possible for one run to fail and the next to work perfectly. This is also why the same network can take thousands of epochs to learn, or a few tens - it's not related to running on w32 or linux.

You'd probably find the same things happening with NNEasy anyway, as the algorithm was derived from an early version of NNFlex.

For discussion of neural net theory, try comp.ai.neural-nets.

(and if you've mailed the contact email address on the NNFlex docs and not had an answer, sorry. I can only get the mail from that account at weekends).

Update: Ouch! Just checked on my source. The cars example has a line

errorfunction=>'atanh',

that should not be there. It's an experimental approach that makes the network much faster on the rare occasions it converges, but very unstable! Remove that line, and you should find cars.pl runs OK.

--------------------------------------------------------------

g0n, backpropagated monk

In reply to Re: NNflex problems (win32) by g0n
in thread NNflex problems (win32) by tlpriest

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