Converged neural network states
3 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
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
0 commentaires
Réponse acceptée
Greg Heath
le 23 Avr 2015
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.
0 commentaires
Plus de réponses (1)
Voir également
Catégories
En savoir plus sur Deep Learning Toolbox dans Help Center et File Exchange
Produits
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!