Introduction to Intelligent Systems, Control, and Machine Learning using MATLAB

Starting with the perceptron, in Chapter 6 we discuss the functioning, the training, and the use of neural networks. For the different neural network structures, the corresponding script in Matlab is provided and the limitations of the different neural network architectures are discussed. A detailed discussion and the underlying mathematical concept of the Backpropagation learning algorithm is accompanied with simple examples as well as sophisticated implementations using Matlab. Chapter 6 also includesconsiderations on quality measures of trained neural networks, such as the accuracy, recall, specificity, precision, prevalence, and some of the derived quantities such as the F-score and the receiver operating characteristic plot. We also look at the overfitting problem and how to handle it during the neural network training process.