1. A method for identifying and correcting systematic noise in a pattern recognition classifier, comprising: rejecting a plurality of input patterns determined not to be associated with any of a set of at least one represented output class by the pattern recognition classifier; selecting a subset of pattern samples from the rejected input patterns based upon the similarity of each pattern to one of the represented output classes; subjecting the selected pattern samples to an independent review to determine if they were correctly rejected; and retraining the classifier based upon the independent review of the selected pattern samples.