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To: Vic Nyman who wrote (491)	12/21/1998 8:47:00 AM
From: Jay Hartzok	Read Replies (1) of 805

Andrew's Comments: ********************************************************* Training neural networks is not a deterministic process, two networks trained with identical data WILL result in two differently trained networks. Both BackProp and Simulated Annealing training use random starting points and random search patterns during training, it would take months or even years to do an exhaustive search of the solution space. The solution space for this application is incredibly huge, a typical network may have over 30 dimensions of mostly uncorrected data, hundreds of variables to balance and hundreds of thousands of computations per training pass. It is not very probable that two networks would take different paths and arrive at the same solution, that would be like two little ants searching for the tallest mountain on earth starting in different continents; most likely each will find the tallest mountain it can see but not always the tallest mountain there is (and that's only three dimensions! our problem is 10 to the 10th power more complex). I hope this helps, and remember that we are not trying to find the absolute best fit network, just one that gives us an edge. Andrew.

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