Let's now merge the theoretical content presented so far together into simple examples of learning algorithms. In this chapter, we are going to explore a couple of learning algorithms in single layer neural networks; multiple layers will be covered in the next chapter.
In the Java code, we will create one new superclass LearningAlgorithm in a new package edu.packt.neural.learn. Another useful package called edu.packt.neural.data will be created to handle datasets that will be processed by the neural network, namely the classes NeuralInputData, and NeuralOutputData, both referenced by the NeuralDataSet class. We recommend the reader takes a glance at the code documentation to understand how these classes are organized, to save text space here.
The LearningAlgorithm class has the following attributes and methods:
public abstract class LearningAlgorithm {
protected NeuralNet neuralNet;
public enum LearningMode {ONLINE,BATCH};
protected enum LearningParadigm...