In this chapter the authors present an overview of pattern classification. In particular, they focus on the mathematical background of pattern classification rather than discussing the practical analysis of various pattern classification methods, and present the derivation of classification rules from a mathematical aspect. First, the authors define the pattern space without the loss of generality. Then, the categorisation of pattern classification is presented according to the design of classification systems. The mathematical formulation of each category of pattern classification is also given. Theoretical discussion using mathematical formulations is presented for distance-based pattern classification and statistical pattern classification. For statistical pattern classification, the standard assumption is made where patterns from each class follow normal distributions with different means and variances.
Selecting Fuzzy Rules for Pattern Classification Systems
