Generating pattern-recognition systems using evolutionary learning

摘要

The E-morph learning algorithm combines a number of learning algorithms-genetic, evolutionary programming, clustering-into a hybrid learning system for solving multiclass pattern-recognition problems. Our work also shows that a randomly generated pool of primitive detectors, rather than manually coded features, can be enhanced and assembled into effective solution sets.