1. A method, operative within a pattern recognition system with a plurality of represented output classes, for identifying output classes with multi-modal dispersion in feature space and incorporating multi-modal structure into a system architecture, said method comprising: rejecting a plurality of input pattern samples determined not to be associated with any of a plurality of represented output classes by a pattern recognition classifier; grouping the rejected pattern samples into clusters according to the similarities between the pattern samples; identifying clusters that contain pattern samples associated with a represented output class via independent review; retraining the classifier to recognize the identified clusters as output pseudoclasses separate from the represented output class with which they are associated; reorganizing the system architecture to incorporate the output pseudoclasses; and rejoining the output pseudoclasses to their associated classes after classification.