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A New Hybrid Fuzzy-Rough Dendritic Cell Immune Classifier

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Advances in Swarm Intelligence (ICSI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7928))

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Abstract

The Dendritic Cell Algorithm (DCA) is an immune-inspired classification algorithm based on the behavior of natural dendritic cells (DC). This paper proposes a novel version of the DCA based on a two-level hybrid fuzzy-rough model. In the top-level, the proposed algorithm, named RST-MFDCM, applies rough set theory to build a solid data pre-processing phase. In the second level, RST-MFDCM applies fuzzy set theory to smooth the crisp separation between the DC’s semi-mature and mature contexts. The experimental results show that RST-MFDCM succeeds in obtaining significantly improved classification accuracy.

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References

  1. Greensmith, J., Aickelin, U., Cayzer, S.: Introducing dendritic cells as a novel immune-inspired algorithm for anomaly detection. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 153–167. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  2. Greensmith, J., Aickelin, U.: The deterministic dendritic cell algorithm. In: Bentley, P.J., Lee, D., Jung, S. (eds.) ICARIS 2008. LNCS, vol. 5132, pp. 291–302. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  3. Chelly, Z., Elouedi, Z.: Further exploration of the fuzzy dendritic cell method. In: Liò, P., Nicosia, G., Stibor, T. (eds.) ICARIS 2011. LNCS, vol. 6825, pp. 419–432. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  4. Kaiser, H.: A note on guttman’s lower bound for the number of common factors. British Journal of Mathematical and Statistical Psychology 14, 1–2 (1961)

    Article  Google Scholar 

  5. Chelly, Z., Elouedi, Z.: RST-DCA: A dendritic cell algorithm based on rough set theory. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part III. LNCS, vol. 7665, pp. 480–487. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  6. Pawlak, Z.: Rough sets. International Journal of Computer and Information Science 11, 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  7. Gu, F., Greensmith, J., Oates, R., Aickelin, U.: Pca 4 dca: The application of principal component analysis to the dendritic cell algorithm. In: Proceedings of the 9th Annual Workshop on Computational Intelligence (2009)

    Google Scholar 

  8. Zimmermann, J.: Fuzzy set theory and its applications. European Journal of Operational Research 1, 227–228 (1996)

    Google Scholar 

  9. Asuncion, A., Newman, D.J.: UCI machine learning repository, (2007), http://mlearn.ics.uci.edu/mlrepository.html

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Chelly, Z., Elouedi, Z. (2013). A New Hybrid Fuzzy-Rough Dendritic Cell Immune Classifier. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_60

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  • DOI: https://doi.org/10.1007/978-3-642-38703-6_60

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38702-9

  • Online ISBN: 978-3-642-38703-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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