Feature extraction from spectral and other data by the principal components and discriminant function techniques

Abstract

Principal component analysis is applied to the interpretation of 13C-n.m.r. spectra and to the resolution of mass spectral data. A procedure is given for determining the relative amounts of pure components, with and without the use of pure mass lines, in mass spectra of mixtures. The use of the Fisher discriminant method in combination with the principal components technique is demonstrated in the treatment of trace element data on hair for environmental purposes. The importance of feature generation and selection is emphasized.