Foundation of identification authentication

Supervised methods rely on some prior training of the system with objects known to belong to the class they define. Such methods can be of the discriminant or modeling types.11 Discriminant methods split the pattern space into as many regions as the classes encompassed by the training set and establish bounds that are shared by the spaces. These methods always classify an unknown sample as a specific class. The most common discriminant methods include discriminant analysis (DA),12 the K-nearest neighbor 

Not every PRM is suitable for constructing spectral identification libraries. These are usually compiled by using supervised modeling methods, and unknown samples are identified with those classes they resemble most. 

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