Abstract
Mass spectral classifiers for 54 structural properties have been developed using a library of 90 000 spectra and applying four complementary classification methods ( k-nearest neighbor, linear discriminant analysis, SIMCA, and a neural network). Neural networks yielded best results; however, only a few structural properties could be classified with a sufficiently high predictive ability. The main difficulties to be solved for future work are the construction of a library with high-quality spectra, and the definition of structural properties that are actually reflected in low resolution mass spectra. Werther, W., Lohninger, H., Stancl, F. and Varmuza, K., 1994. Classification of mass spectra. A comparison of yes/no classification methods for the recognition of simple structural properties. Chemometrics and Intelligent Laboratory Systems, 22: 63–76.
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