Pattern Recognition

7Special classifiers

The remaining chapters of this book collect some further topics of pattern recognition. Except for Section 9.4, these chapters deal with certain important classifier methods. In contrast to the techniques of Chapters 3 to 5, these classifiers do not estimate a distribution first, but try to find a classification rule directly from the given data instead. This means that these classifiers follow the transduction path from Figure 5.1.

7.1Linear discriminants

A linear discriminant is a linear function that operates on the feature space. With two classes (c= 2), w ∈ d and b∈ , it is given by

$\left(m\right)=w^{⊺}m+b$