PARTIAL LEAST-SQUARES REGRESSION AS A MULTIVARIATE TOOL FOR THE INTERPRETATION OF INFRARED-SPECTRA

The potentials of partial least squares regression (PLS) as a tool for the automated interpretation of infrared spectra have been investigat ed. Class probabilities are obtained by applying a sigmoid function to the PLS predictions. Results are compared with those obtained from ar tificial neural networks (ANN) applied to full spectra and to the most relevant principal component scores. The predictions obtained from al l approaches appear to be comparable, but the time required for traini ng is considerably shorter for the extended PLS approach.