ABSTRACT
In this chapter we describe several linear methods of dimensionality reduction. We first discuss some classical methods such as principal component analysis (PCA), singular value decomposition (SVD), and factor analysis. Finally, we include a brief discussion of methods for determining the intrinsic dimensionality of a data set.
