A comparison of a common approach to partial least squares-discriminant analysis and classical least squares in hyperspectral imaging

Int J Pharm. 2009 May 21;373(1-2):179-82. doi: 10.1016/j.ijpharm.2009.02.014. Epub 2009 Mar 3.

Abstract

In hyperspectral analysis, PLS-discriminant analysis (PLS-DA) is being increasingly used in conjunction with pure spectra where it is often referred to as PLS-Classification (PLS-Class). PLS-Class has been presented as a novel approach making it possible to obtain qualitative information about the distribution of the compounds in each pixel using little a priori knowledge about the image (only the pure spectrum of each compound is needed). In this short note it is shown that the PLS-Class model is the same as a straightforward classical least squares (CLS) model and it is highlighted that it is more appropriate to view this approach as CLS rather than PLS-DA. A real example illustrates the results of applying both PLS-Class and CLS.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Discriminant Analysis
  • Least-Squares Analysis
  • Models, Statistical*
  • Signal Processing, Computer-Assisted*
  • Spectroscopy, Near-Infrared / methods*
  • Spectrum Analysis / methods