例子:
% some random data
in = rand(100,5)';
out = rand(100,1)';
% create a feed-forward back-propagation neural network
% (1 hidden layer with 5 neurons)
net = newfit(in,out,5);
net.trainParam.showWindow = 0; % dont show GUI
% repeat 10 times
rmse = [];
t = [];
for i=1:10
net = init(net); % initialize network weights
tic
net = train(net,in,out); % train
predicted = sim(net, in); % test
t(i) = toc;
r = (out - predicted); % residuals
rmse(i) = sqrt(mean(r.^2)); % root mean square error
end
% plot errors and elapsed times
bar([t; rmse]', 'grouped'), xlabel('Runs')
legend({'Elapsed Time' 'RMSE'}, 'orientation','horizontal')
注:在R2010b中,newfit
功能已被否決有利於fitnet
,請使用以下內容而不是創建網絡:
% old
%net = newfit(in,out,5);
% new
net = fitnet(5); % create ANN
net = configure(net, in, out); % set input/output sizes according to data
非常感謝@Amro。這非常有幫助,很多。再次感謝。 – Lazer 2009-11-04 17:27:13