Converged neural network states
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Hi -
I am wondering why I don’t arrive at the same trained network (net1f and net3f) even though I believe I have started from the same initial network state.
clear all, pack [x,t] = simplefit_dataset;
%% 1st trial net1i = feedforwardnet( 1); net1i= configure( net1i, x, t) ; IW1i= net1i.IW ; LW1i= net1i.LW ; b1i= net1i.b ; net1f = trainscg( net1i, x, t); IW1f= net1f.IW ; LW1f= net1f.LW ; b1f= net1f.b ;
%% 3rd trial with controlled initialization net3i = feedforwardnet( 1); net3i= configure( net3i, x, t) ; net3i.IW= IW1i ; net3i.LW= LW1i ; net3i.b= b1i ; net3f = trainscg( net3i, x, t); IW3f= net3f.IW ; LW3f= net3f.LW ; b3f= net3f.b ;
I appreciate your help.
Thanks. Siva
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Greg Heath
2015-4-23
You have to explicitly reset the RNG state to the same initial value. To illustrate this. Check the RNG state before each training.
Hope this helps.
Greg.
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