Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Many current face recognition algorithms perform badly when the lighting or pose of the probe and gallery images differ. In this paper we present a novel algorithm designed for th...
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
A Generalized Nonlinear Discriminant Analysis (GNDA) method is proposed, which implements Fisher discriminant analysis in a nonlinear mapping space. Linear discriminant analysis i...
We present a new method that we call Generalized Discriminant Analysis (GDA) to deal with nonlinear discriminant analysis using kernel function operator. The underlying theory is ...