Hello Diego,
I understand that you are trying to build an ANN with hidden layer of varying sizes and following parameters.
- Training function: trainlm
- Learning function: learngdm
- Performance function: MSE
I am attaching a sample code that creates an ANN with the given parameters. You can use the “createnetwork()” function to define network with varying hidden layer sizes.
net = createnetwork([10,8]); % create a network
% number_hidden_layers is a vector of number of neurons required in each layer [10,8] means a network with 2 layers of sizes 10 and 8 respectively.
function net = createnetwork(number_hidden_layers)
net = feedforwardnet(number_hidden_layers); % Specify the number of hidden layers and neurons per layer
% Set the training function, adaptation learning function, and performance function
net.trainFcn = 'trainlm';
net.adaptFcn = 'learngdm';
net.performFcn = 'mse';
% Divide the data into training, validation, and testing sets
net.divideFcn = 'dividerand';
net.divideMode = 'sample';
net.divideParam.trainRatio = 0.7;
net.divideParam.valRatio = 0.15;
net.divideParam.testRatio = 0.15;
end
Hope this helps!
Regards,
Aditi
