Here is the code:
inputs = readmatrix(‘C:UserstanmoDownloadsInput-Station-2.xlsx’);
targets = readmatrix(‘C:UserstanmoDownloadsTarget-Station-2.xlsx’);
inputs = inputs’; % Transpose if necessary
targets = targets’; % Transpose if necessary
net = feedforwardnet([10 10]);
net.trainFcn = ‘trainlm’; % Using Levenberg-Marquardt backpropagation
net.trainParam.epochs = 50;
net.trainParam.lr = 0.01;
net.trainParam.max_fail = 50; % Maximum validation failures
net.divideParam.trainRatio = 0.70;
net.divideParam.valRatio = 0.15;
net.divideParam.testRatio = 0.15;
net.trainParam.goal = 0; % Essentially remove the performance goal// added later
net.trainParam.min_grad = 1e-10; % Set a very small gradient goal

[net, tr]= train(net, inputs, targets);
outputs = net(inputs);
performance = perform(net, targets, outputs);
plotperform(tr)
I can’t fix the number of iteration or epoch. It does a random iteration in different time and plots graph for random epoch values.Here is the code:
inputs = readmatrix(‘C:UserstanmoDownloadsInput-Station-2.xlsx’);
targets = readmatrix(‘C:UserstanmoDownloadsTarget-Station-2.xlsx’);
inputs = inputs’; % Transpose if necessary
targets = targets’; % Transpose if necessary
net = feedforwardnet([10 10]);
net.trainFcn = ‘trainlm’; % Using Levenberg-Marquardt backpropagation
net.trainParam.epochs = 50;
net.trainParam.lr = 0.01;
net.trainParam.max_fail = 50; % Maximum validation failures
net.divideParam.trainRatio = 0.70;
net.divideParam.valRatio = 0.15;
net.divideParam.testRatio = 0.15;
net.trainParam.goal = 0; % Essentially remove the performance goal// added later
net.trainParam.min_grad = 1e-10; % Set a very small gradient goal

[net, tr]= train(net, inputs, targets);
outputs = net(inputs);
performance = perform(net, targets, outputs);
plotperform(tr)
I can’t fix the number of iteration or epoch. It does a random iteration in different time and plots graph for random epoch values. Here is the code:
inputs = readmatrix(‘C:UserstanmoDownloadsInput-Station-2.xlsx’);
targets = readmatrix(‘C:UserstanmoDownloadsTarget-Station-2.xlsx’);
inputs = inputs’; % Transpose if necessary
targets = targets’; % Transpose if necessary
net = feedforwardnet([10 10]);
net.trainFcn = ‘trainlm’; % Using Levenberg-Marquardt backpropagation
net.trainParam.epochs = 50;
net.trainParam.lr = 0.01;
net.trainParam.max_fail = 50; % Maximum validation failures
net.divideParam.trainRatio = 0.70;
net.divideParam.valRatio = 0.15;
net.divideParam.testRatio = 0.15;
net.trainParam.goal = 0; % Essentially remove the performance goal// added later
net.trainParam.min_grad = 1e-10; % Set a very small gradient goal

[net, tr]= train(net, inputs, targets);
outputs = net(inputs);
performance = perform(net, targets, outputs);
plotperform(tr)
I can’t fix the number of iteration or epoch. It does a random iteration in different time and plots graph for random epoch values. epoch, iteration, ann MATLAB Answers — New Questions

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