Pattern Recognition Methods for the Classification of Binary Infrared Spectral Data

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.