Abstract
Four supervised pattern-recognition procedures—linear discriminant analysis, soft-independent models of class analogy, a univariate expert system, and a multivariate expert system—were applied to pyrolysis-mass spectrometry data from five bacterial species. A test set was generated by individually modifying the tuning parameters of the mass spectrometer followed by collection of one spectrum for each bacteria. Five replicate pyrolysis-mass spectra of each bacteria were used as a training set for the classification of the test set. The multivariate expert system consistently scored over 92% correctly identified, while the other procedures resulted in less than 80% correctly identified. Under these harsh conditions, the multivariate expert system was not affected seriously by the mass spectrometer tuning changes.
PDF Article
More Like This
Effect of pyrolysis on microstructures made of various photoresists by two-photon polymerization: comparative study
M. I. Sharipova, T. G. Baluyan, K. A. Abrashitova, G. E. Kulagin, A. K. Petrov, A. S. Chizhov, T. B. Shatalova, D. Chubich, D. A. Kolymagin, A. G. Vitukhnovsky, V. O. Bessonov, and A. A. Fedyanin
Opt. Mater. Express 11(2) 371-384 (2021)
Cited By
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription