Introduction to Kernel Methods: Classification of Multivariate Data

UMR 1201 DYNAFOR INRA & Institut National Polytechnique de Toulouse, Toulouse, France

Abstract

In this chapter, kernel methods are presented for the classification of multivariate data. An introduction example is given to enlighten the main idea of kernel methods. Then emphasis is done on the Support Vector Machine. Structural risk minimization is presented, and linear and non-linear SVM are described. Finally, a full example of SVM classification is given on simulated hyperspectral data.