Biometric Authentication: A Machine Learning Approach

4.1. Introduction

The study of linear classifiers with supervised training has a long history. As early as 1936, Fisher's discriminant had already laid the groundwork for statistical pattern recognition. Later, Rosenblatt's perceptron (1956) was the first neural classifier proposed; it shares many similarities with the learning techniques used in the support vector machine developed by Vapnik [358] and in an earlier paper by Boser, Guyon, and Vapnik [33].

Section 4.2 begins by introducing a simple two-class classifier, then goes on to derive the least-squares classifier and the classical Fisher discriminant linear analysis. The decision boundary of the least-squares classifier and the Fisher classifier is dictated (i.e., supported) by all of ...