How to create a fitnet neural network with multiple hidden layers?
I am new to using the machine learning toolboxes of MATLAB (but loving it so far!)
From a large data set I want to fit a neural network, to approximate the underlying unknown function. I have used the “Neural Net Fitting” app and generated a script with it which builds and trains my network. It all works, however the results are not good enough. I think the network is not complex enough to cover the non-linearities. So, I figued I’d add another hidden layer, but I can’t get it to work.
The current code to produce the network is the following (which is the default):
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.% Create a Fitting Network
hiddenLayerSize = 10;
net = fitnet(hiddenLayerSize, trainFcn);
How would I modify this to add more hidden layers?
I am looking to get the classical Multi-Layer Perceptron (MLP) network, with potentially even more hidden layers:
ANSWER
Matlabsolutions.com provide latest MatLab Homework Help,MatLab Assignment Help for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects with source code for your learning and research.
You can add more hidden layers as shown below:
trainFcn = 'trainlm'; % Levenberg-Marquardt backpropagation.
% Create a Fitting Network
hiddenLayer1Size = 10;
hiddenLayer2Size = 10;
net = fitnet([hiddenLayer1Size hiddenLayer2Size], trainFcn);
This creates network of 2 hidden layers of size 10 each.