Clonal Selection-Based Neural Classifier

A. Lanaridis, V. Karakasis, A. Stafylopatis
2008 2008 Eighth International Conference on Hybrid Intelligent Systems  
Artificial Immune Systems (AIS) constitute an emerging and promising field, and have been applied to pattern recognition and classification tasks to a limited extent so far. This work is a first attempt of applying the clonal selection principle to the training of Multi-Layer Perceptrons (MLPs). The Clonal Selectionbased Neural Classifier (CSNC) uses the basic concepts of clonal selection to evolve MLPs, which are represented as real-valued linear antibodies. The proposed system is actually a
more » ... lti-classifier, consisting of multiple sets of MLPs, each one devoted to the recognition of a different class of the input data. The final trained classifier is comprised of the best MLPs from each set. The proposed classifier is tested against a set of benchmark problems and yields promising results.
doi:10.1109/his.2008.82 dblp:conf/his/LanaridisKS08 fatcat:b732vzuemzbtbizsmgpjis4sny