We now begin to look at supervised learning, which is the theme for the next few chapters of the book, especially focusing on data classification. This chapter is about one major approach for classification, based on constructing some discriminant functions, mostly linear ones, whose values across the data space form territories and boundaries for all the classes. The location of classification boundaries will be optimized using various probabilistic and geometric principles to be introduced in detail.