清空筛选条件
清空筛选条件

Converged neural network states

3 次查看（过去 30 天）
Siva
Siva 2015-4-12
回答： Siva 2015-4-23
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

请先登录，再回答此问题。

采纳的回答

Greg Heath
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.

更多回答（1 个）

Siva
Siva 2015-4-23
Thanks Greg!
Siva

类别

在 Help Center 和 File Exchange 中查找有关 Deep Learning Toolbox 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by