Hi,
How can I set up a loop to train at least 10 neural networks with the same parameters and save only the best performance, regression and histogram error, and the matrix-only MATLAB function for neural network code?
More specifically, for example, what do I need to change in the following code provided by MATLAB:
inputs = houseInputs; targets = houseTargets;
% Create a Fitting Network hiddenLayerSize = 10; net = fitnet(hiddenLayerSize);
% Set up Division of Data for Training, Validation, Testing net.divideParam.trainRatio = 70/100; net.divideParam.valRatio = 15/100; net.divideParam.testRatio = 15/100;
% Train the Network [net,tr] = train(net,inputs,targets);
% Test the Network outputs = net(inputs); errors = gsubtract(outputs,targets); performance = perform(net,targets,outputs)
% View the Network view(net)
% Plots % Uncomment these lines to enable various plots. % figure, plotperform(tr) % figure, plottrainstate(tr) % figure, plotfit(targets,outputs) % figure, plotregression(targets,outputs) % figure, ploterrhist(errors)
