Why the results of my Elman network are different every time?
2 ビュー (過去 30 日間)
古いコメントを表示
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)
3 件のコメント
Greg Heath
2015 年 8 月 1 日
編集済み: Walter Roberson
2015 年 8 月 2 日
% 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;
採用された回答
Walter Roberson
2015 年 7 月 31 日
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 件のコメント
その他の回答 (0 件)
参考
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!