Abstract
In this paper, we propose an algorithm for cluster analysis inspired by the lymphocyte-cytokine network in the immune system. Our algorithm attempts to optimally represent a large data set by its principle subset whilst maximising the data kernel density distribution. Experiments show that the output data set created by our algorithm effectively represents the original input data set, according to the Kullback-Leibler divergence metric. We compare the performance of our approach with the well-known aiNet algorithm and find our approach provides a significant improvement on the representation of the final data set.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Silverman, B.W.: Density Estimation for Statistics and Data Analysis. Chapman and Hall, Sydney (1986)
de Castro, L.N., von Zuben, F.: Data Mining: A Heuristic Approach. Idea Group Publishing, USA (2001)
Kullback, S.: Information Therory and Statistics. John wiley & Sons, West Sussex (1959)
Cutello, V., Nicosia, G., Pavone, M., Stracquadanio, G.: An information-theoretic approach for clonal selection algorithms. In: Hart, E., McEwan, C., Timmis, J., Hone, A. (eds.) ICARIS 2010. LNCS, vol. 6209, pp. 144–157. Springer, Heidelberg (2010)
Stibor, T., Timmis, J.: An investigation on the compression quality of aiNet. In: Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, pp. 495–502 (2007)
Timmis, J.: Artificial immune systems: today and tomorrow. Natural Computing 6, 1–18 (2007)
Timmis, J., Hone, A., Stibor, T., Clark, E.: Theoretical advances in artificial immune systems. Theor. Comput. Sci. 403, 11–32 (2008)
Bezerra, G.B., Barra, T.V., de Castro, L.N., Von Zuben, F.J.: Adaptive radius immune algorithm for data clustering. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 290–303. Springer, Heidelberg (2005)
Violato, R.P.V., Azzolini, A.G., Von Zuben, F.J.: Antibodies with adaptive radius as prototypes of high-dimensional datasets. In: Hart, E., McEwan, C., Timmis, J., Hone, A. (eds.) ICARIS 2010. LNCS, vol. 6209, pp. 158–170. Springer, Heidelberg (2010)
Abbas, A., Lichtman, A., Pillai, S.: Cellular and Molecular Immunology, 6th edn. Saunders Elsevier (2007)
Hone, A., van den Berg, H.: Modelling a cytokine network. In: Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, Special session: Foundations of Artificial Immune Systems, pp. 389–393 (2007)
Liu, Y., Timmis, J., Clarke, T.: A neuro-immune inspired robust real time visual tracking system. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 188–199. Springer, Heidelberg (2008)
Neal, M.: Meta-stable memory in an artificial immune network. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 168–180. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, Y., Timmis, J., Clarke, T. (2011). A Lymphocyte-Cytokine Network Inspired Algorithm for Data Analysis. In: Liò, P., Nicosia, G., Stibor, T. (eds) Artificial Immune Systems. ICARIS 2011. Lecture Notes in Computer Science, vol 6825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22371-6_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-22371-6_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22370-9
Online ISBN: 978-3-642-22371-6
eBook Packages: Computer ScienceComputer Science (R0)