Using a Genetic Algorithm to Learn Prototypes for Case Retrieval and Classification

Learning

We describe how a genetic algorithm can identify prototypical examples from a case base that can be used reliably as reference instances for nearest neighbor classification. A case-based retrieval and classification system called Off Broadway implements this approach. Using the Fisher Iris data set as a case base, we describe an experiment showing that nearest neighbor classification accuracy of over 95% can be achieved with a set of prototypes that constitute less than 5% of the case base.