Machine Learning for Engineers

In this chapter, we use the optimization tools presented in Chapter 5 to develop supervised learning algorithms that move beyond the simple settings studied in Chapter 4 for which the training problem could be solved exactly, typically by addressing an LS problem. We will focus specifically on binary and multi-class classification, with a brief discussion at the end of the chapter about the (direct) extension to regression problems. Following Chapter 4, the presentation will mostly concentrate on parametric model classes, but we will also touch upon mixture models and non-parametric methods.