Abstract: A method and computer program product is disclosed for automatically establishing a system architecture for a pattern recognition system with a plurality of output classes. Feature data is extracted from a plurality of pattern samples corresponding to a selected set of feature variables. A clustering algorithm is then applied to the extracted feature data to identify a plurality of clusters, including at least one cluster containing more than one output class. The identified clusters are arranged into a first level of classification that discriminates between the clusters using the selected set of feature variables. Finally, the output classes within each cluster containing more than one output class are arranged into at least one sublevel of classification that discriminates between the output classes within the cluster using at least one alternate set of feature variables.