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Artificial Immune Recognition System (AIRS): An Immune Inspired Supervised Machine Learning Algorithm
Andrew Watkins, Jon Timmis, and Lois Boggess
Genetic Programming and Evolvable Machines, 5(1):182-196, March 2004.Abstract
This paper presents the inception and subsequent revisions of an immune-inspired supervised learning algorithm, Artificial Immune Recognition System (AIRS). It presents the immunological components that inspired the algorithm and describes the initial algorithm in detail. The discussion then moves to revisions of the basic algorithm that remove certain unnecessary complications of the original version. Experimental results for both versions of the algorithm and are discussed and these results indicate that the revisions to the algorithm do not sacrifice accuracy while increasing the data reduction capabilities of AIRS.
Bibtex Record
@article{1634, author = {Andrew Watkins and Jon Timmis and Lois Boggess}, title = {Artificial {I}mmune {R}ecognition {S}ystem ({AIRS}): {A}N {I}mmune {I}nspired {S}upervised {M}achine {L}earning {A}lgorithm}, month = {March}, year = {2004}, pages = {182-196}, keywords = {determinacy analysis, Craig interpolants}, note = {}, doi = {}, url = {http://www.cs.kent.ac.uk/pubs/2004/1634}, publication_type = {article}, submission_id = {26863_1056529121}, journal = {Genetic Programming and Evolvable Machines}, volume = {5}, number = {1}, publisher = {Kluwer}, }