I have t开发者_Python百科his code:
in = [5 columns of data-points];
out = [1 column of data-points];
net = newfit(in,out,5);
net = train(net,in,out);
now I want to
- access the error variable that is generated (so that I can calculate the mean error etc.)
- run this in a loop, so I want to re-initialize weights between loops.
- access the variable that stores the time it took to run
How can these three things be done from command line?
[I know how these things can be done with nntool
GUI]
Example:
% 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')
NOTE: In R2010b, newfit
function was deprecated in favor of fitnet
, use the following code instead to create the network:
% old
%net = newfit(in,out,5);
% new
net = fitnet(5); % create ANN
net = configure(net, in, out); % set input/output sizes according to data
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