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Optica Publishing Group
  • Applied Spectroscopy
  • Vol. 30,
  • Issue 2,
  • pp. 213-216
  • (1976)

Pattern Recognition Methods for the Classification of Binary Infrared Spectral Data

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Abstract

Five pattern recognition methods are compared for their ability to classify binary infrared spectra. Included is a discussion of the time vs success balance for each of the techniques. Predictive ability decreases in the order maximum likelihood > distance > Tanimoto similarity ~ Hamming distance > dot product. The time required for each prediction after the classifier has been developed increases in order maximum likelihood ~ distance ~ dot product < Tanimoto similarity ~ Hamming distance.

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