Now, it is time to develop a neural network using OOP concepts and explain the related theory. The project presented in the previous chapter was adapted to implement the perceptron and adaline rules, as well as the Delta rule.
NeuralNet class presented in the previous chapter has been updated to include the training dataset (input and target output), learning parameters, and activation function settings. The
InputLayer function was also updated to include one method. We added to the project the
Training classes. Details on the implementation of each class can be found in the codes. However, now, let's make the connection between the neural learning and the Java implementation of ...