Cellular Automata Based Pattern Classifying Machine for Distributed Data Mining

  • Pradipta Maji
  • P. Pal Chaudhuri
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

In this paper, we present the design and application of a pattern classifying machine (PCM) for distributed data mining (DDM) environment. The PCM is based on a special class of sparse network referred to as Cellular Automata (CA). The desired CA are evolved with an efficient formulation of Genetic Algorithm (GA). Extensive experimental results with respect to classification accuracy and memory overhead confirm the scalability of the PCM to handle distributed datasets.

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References

  1. 1.
    Ganguly, N., Maji, P., Dhar, S., Sikdar, B.K., Chaudhuri, P.P.: Evolving Cellular Automata as Pattern Classifier. In: Bandini, S., Chopard, B., Tomassini, M. (eds.) ACRI 2002. LNCS, vol. 2493, pp. 56–68. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  2. 2.
    Maji, P., Shaw, C., Ganguly, N., Sikdar, B.K., Chaudhuri, P.P.: Theory and Application of Cellular Automata For Pattern Classification. Accepted for publication in the special issue of Fundamenta Informaticae on Cellular Automata (2004)Google Scholar
  3. 3.
    Maji, P., Sikdar, B.K., Chaudhuri, P.P.: Cellular Automata Evolution For Distributed Data Mining. In: Sloot, P.M.A., Chopard, B., Hoekstra, A.G. (eds.) ACRI 2004. LNCS, vol. 3305, pp. 40–49. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Pradipta Maji
    • 1
  • P. Pal Chaudhuri
    • 1
  1. 1.Department of Computer Science and Engineering & Information TechnologyNetaji Subhash Engineering CollegeKolkataIndia

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