Why the results of my Elman network are different every time?

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Heather Zhang
Heather Zhang 2015-7-31
评论： Greg Heath 2015-8-13
I created a elman network. But the results every time I run the code were different.I got different "errors","regression" and "avg_error" Could anyone tell me why? Appreciate SO MUCH!
Here is the code.
clear all
load('input4_train.mat');
load('output4_train.mat');
load('input4_test.mat');
load('output4_test.mat');
inputSeries = tonndata(input4_train,false,false);
targetSeries = tonndata(output4_train,false,false);
inputTest = tonndata(input4_test,false,false);
outputTest = tonndata(output4_test,false,false);
% Create a Network
hiddenLayerSize = 5;
net=newelm(inputSeries,targetSeries,[10,3,1], {'tansig','logsig','purelin'});
% Setup Division of Data for Training, Validation, Testing
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
net.trainParam.epochs = 2000;
% Initial net
net = init(net);
% Train the Network
net = adapt(net,inputSeries,targetSeries);
% Test the Network
outputs = sim(net,inputTest);
errors = gsubtract(outputTest,outputs);
error = cell2mat(errors);
for i = 1:10
error(i)=abs(error(i));
end
avg_error = sum(error)/10;
performance = perform(net,outputTest,outputs)
% View the Network
view(net)
% Plots
figure, plotregression(outputTest,outputs)
figure, plotresponse(outputTest,outputs)
figure, ploterrcorr(errors)
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Greg Heath
Greg Heath 2015-8-1
编辑：Walter Roberson 2015-8-2
% load('input4_train.mat');
% load('output4_train.mat');
% load('input4_test.mat');
% load('output4_test.mat');
%
% inputSeries = tonndata(input4_train,false,false);
% targetSeries = tonndata(output4_train,false,false);
% inputTest = tonndata(input4_test,false,false);
% outputTest = tonndata(output4_test,false,false);
whos
% % Create a Network
% hiddenLayerSize = 5;
Value never used
% net=newelm(inputSeries,targetSeries,[10,3,1], {'tansig','logsig','purelin'});
No justification for 3 hidden layers. One is sufficient.
% % Setup Division of Data for Training, Validation, Testing
% net.divideParam.trainRatio = 70/100;
% net.divideParam.valRatio = 15/100;
% net.divideParam.testRatio = 15/100;
Above 3 commands unnecessary for default values.
% net.trainParam.epochs = 2000;
%
% % Initial net
% net = init(net);
%
% % Train the Network
% net = adapt(net,inputSeries,targetSeries);
%
% % Test the Network
% outputs = sim(net,inputTest);
%
% errors = gsubtract(outputTest,outputs);
% error = cell2mat(errors);
% for i = 1:10
% error(i)=abs(error(i));
% end
% avg_error = sum(error)/10;
Above 5 commands unnecessary.
help mae
doc mae
% performance = perform(net,outputTest,outputs)
% % View the Network
% view(net)
%
% % Plots
% figure, plotregression(outputTest,outputs)
% figure, plotresponse(outputTest,outputs)
% figure, ploterrcorr(errors)
Defaults: Above 3 commands unnecessary;
Heather Zhang
Heather Zhang 2015-8-2
Thank you so much for your detailed,Greg! I need your help on my code. I will answer your questions.
Q2. What scenario did you use it for? Why was it used instead of timedelaynet or narxnet? I use it for dealing with a time series prediction issue.
Q3. Where did you obtain this code? Many of the options chosen make little sense. I coded it according to BP network code. I knew "newelm" function is for build an Elman network and "sim" is for testing a network. So I coded it by myself. I can tell there should be something wrong in it, but I don't know where the mistakes are.
So pleas help me on this code, and that would be appreciated very much!

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采纳的回答

Walter Roberson
Walter Roberson 2015-7-31
Neural Networks initialize their weights randomly usually. If you want repeatability you can initialize the weights yourself or you can set the random number generator seed.
  2 个评论
Heather Zhang
Heather Zhang 2015-8-2
Thank you so much,Walter! I use 'init' function to initialize the weights. Am I right? Looking forward to your answer.

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