Now, let's implement all the theory that we've discussed so far. Here, we use the classes that define the ANN structures
Neuron, and so on. Now, we add
OutputLayer functions, which are inherited from the
Layer class, to implement multilayer neural networks.
We also implement the two learning algorithms that we've presented in this chapter: Backpropagation and Levenberg–Marquardt. In the
Training class, we add two new terms to the enum Training types:
In order to make the execution of the Levenberg–Marquardt algorithm possible, we add a new package called
edu.packt.neuralnet.util and two more classes, namely
IdentityMatrix. These classes ...