Regression and Classification Problems

We discussed two distinct methods, supervised learning and unsupervised learning, in Chapter 1, Fundamentals. Supervised learning problems aim to map input information to a known output value or label, but there are two further subcategories to consider. Supervised learning problems can be further divided into regression or classification problems. Regression problems, which are the subject of this chapter, aim to predict or model continuous values, for example, predicting the temperature tomorrow in degrees Celsius, from historical data, or forecasting future sales of a product on the basis of its sales history. In contrast, classification problems, rather than returning a continuous value, predict membership of one or more of a specified number of classes or categories. The example supervised learning problem in Chapter 1, Fundamentals, where we wanted to determine or predict whether a hairstyle was from the 1960s or 1980s, is a good example...