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Abstract
Pattern recognition methods have been applied to a wide variety of chemical problems. In a typical pattern recognition study, samples are classified according to a specific property using measurements that are indirectly related to the property of interest. An empirical relationship or classification rule is developed from a set of samples for which the property of interest and the measurements are known. The classification rule can then be used to predict the property in samples that are not part of the original training set. In this review, the three major subdivisions of pattern recognition methodology are discussed and the analytical literature is surveyed. Much of the literature on pattern recognition focuses on novel and not so novel applications. Only the more interesting applications of pattern recognition methods are referenced in this review article.