Converged neural network states

조회 수: 3(최근 30일)
Siva 2015년 4월 12일
답변: Siva 2015년 4월 23일
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

채택된 답변

Greg Heath
Greg Heath 2015년 4월 23일
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.

추가 답변(1개)

Siva 2015년 4월 23일
Thanks Greg!

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