Kernel based methods in classification and regression

Kernel based methods like Kernel Principal Component Analysis, Kernel SIMCA, Kernel Partial Least Squares (KPLS), Support Vector Machines (SVM) etc... have become popular techniques for classification or regression of complex non-linear data sets. The modeling is performed by mapping the data in a high-dimensional feature space through a (linear or non-linear) kernel transformation, followed by a classification or regression step. The course will illustrate the basic principle of the kernel transformation many applications and hands-on