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A Fast Implementation of the CT_EXT Algorithm for the Testor Property Identification

  • Guillermo Sanchez-Diaz
  • Ivan Piza-Davila
  • Manuel Lazo-Cortes
  • Miguel Mora-Gonzalez
  • Javier Salinas-Luna
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6438)

Abstract

Typical testors are a useful tool for both feature selection and for determining feature relevance in supervised classification problems. Nowadays, generating all typical testors of a training matrix is computationally expensive; all reported algorithms have exponential complexity, depending mainly on the number of columns in the training matrix. For this reason, different approaches such as sequential and parallel algorithms, genetic algorithms and hardware implementations techniques have been developed. In this paper, we introduce a fast implementation of the algorithm CT_EXT (which is one of the fastest algorithms reported) based on an accumulative binary tuple, developed for generating all typical testors of a training matrix. The accumulative binary tuple implemented in the CT_EXT algorithm, is a useful way to simplifies the search of feature combinations which fulfill the testor property, because its implementation decreases the number of operations involved in the process of generating all typical testors. In addition, experimental results using the proposed fast implementation of the CT_EXT algorithm and the comparison with other state of the art algorithms that generated typical testors are presented.

Keywords

feature selection typical testors pattern recognition 

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References

  1. 1.
    Carrasco-Ochoa, J., Ruiz-Shulcloper, J., Diaz de Leon, J.: Sensitivity analisys in logical combinatorial pattern recognition. Computacion y Sistemas 6(1), 62–66 (2002)Google Scholar
  2. 2.
    De la Vega-Doria, L., Carrasco-Ochoa, A., Ruiz-Shucloper, J.: Fuzzy KORA-W algorithm. In: 6th European Conf. on Intelligent Techniques and Soft Computer, Germany, pp. 1190–1194 (1998)Google Scholar
  3. 3.
    Dmitriev, A.N., Zhuravlev, Y.I., Krendeliev, F.: About mathematical principles and phenomena classification. Diskretni Analiz. 7, 3–15 (1966)Google Scholar
  4. 4.
    Lazo-Cortes, M., Ruiz-Shulcloper, J., Alba-Cabrera, E.: An Overview of the evolution of the concept of testor. Pattern Recognition 34(4), 753–762 (2001)CrossRefzbMATHGoogle Scholar
  5. 5.
    Lias-Rodriguez, A., Pons-Porrata, A.: BR: A new method for computing all typical testors. In: Bayro-Corrochano, E., Eklundh, J.-O. (eds.) CIARP 2009. LNCS, vol. 5856, pp. 433–440. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Martinez-Trinidad, J.F., Guzman-Arenas, A.: The Logical Combinatorial approach for pattern recognition an overview through selected Works. Pattern Recognition 34(4), 741–751 (2001)CrossRefzbMATHGoogle Scholar
  7. 7.
    Ortiz-Posadas, M., Martinez-Trinidad, J., Ruiz-Shulcloper, J.: A new approach to diferential diagnosis of diseases. International Journal of Biomedical Computing 40(3), 179–185 (2001)CrossRefGoogle Scholar
  8. 8.
    Pons-Porrata, A., Gil-Garcia, R., Berlanga-Llavori, R.: Using Typical Testors for Feature Selection in Text Categorization. In: Rueda, L., Mery, D., Kittler, J. (eds.) CIARP 2007. LNCS, vol. 4756, pp. 643–652. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Pons-Porrata, A., Ruiz-Shulcloper, J., Berlanga-Llavori, R.: A Method for the Automatic Summarization of Topic-Based Clusters of Documents. In: Sanfeliu, A., Ruiz-Shulcloper, J. (eds.) CIARP 2003. LNCS, vol. 2905, pp. 596–603. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  10. 10.
    Rojas, A., Cumplido, R., Carrasco, A., Feregrino, C., Martinez, J.: On the design and implementation of a high performance configurable architecture for testor identification. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds.) IDEAL 2007. LNCS, vol. 4881, pp. 665–673. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Ruiz, J., Guzman, A., Martinez, J.: Logical combinatorial pattern recognition approach. In: Advances on pattern recognition series, Edit. Instituto Politecnico Nacional, Mexico (1999)Google Scholar
  12. 12.
    Ruiz-Shulcloper, J., Abidi, M.: Logical Combinatorial Pattern Recognition: A Review. In: Pandalai, S.G. (ed.) Recent Research Developments in Pattern Recognition, Transworld Research Networks, Kerala, India, pp. 133–176 (2002)Google Scholar
  13. 13.
    Sanchez-Diaz, G.: Developing and implementing efficient algorithms (bath and parallel) for calculating typical testors of a basic matrix. Master Thesis. Autonomous University of Puebla, Puebla, Mexico (1997)Google Scholar
  14. 14.
    Sanchez-Diaz, G., Lazo-Cortes, M.: CT_EXT: an external escale algorithm for generated typical testors. In: Rueda, L., Mery, D., Kittler, J. (eds.) CIARP 2007. LNCS, vol. 4756, pp. 506–514. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  15. 15.
    Sanchez-Diaz, G., Lazo-Cortes, M.: Modifications to BT algorithm for improving its run time execution. Revista Ciencias Matematicas 20(2), 129–136 (2002)MathSciNetGoogle Scholar
  16. 16.
    Sanchez-Diaz, G., Lazo-Cortes, M., Fuentes-Chavez, O.: Genetic algorithm for calculating typical testors of minimal cost. In: Iberoamerican Symposium on Pattern Recognition, pp. 207–213 (1999)Google Scholar
  17. 17.
    Sanchez-Diaz, G., Lazo-Cortes, M., Garcia-Fernandez, J.: Parallel and distributed models for calculating typical testors. In: Iberoamerican Workshop on Pattern Recognition, pp. 135–140 (1997)Google Scholar
  18. 18.
    Santiesteban-Alganza, Y., Pons-Porrata, A.: LEX: A new algorithm for calculating typical testors. Revista Ciencias Matematicas 21(1), 85–95 (2003)MathSciNetGoogle Scholar
  19. 19.
    UCI-Machine-Learning-Repository, University of California, http://archive.ics.uci.edu/ml

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Guillermo Sanchez-Diaz
    • 1
  • Ivan Piza-Davila
    • 2
  • Manuel Lazo-Cortes
    • 3
  • Miguel Mora-Gonzalez
    • 4
  • Javier Salinas-Luna
    • 1
  1. 1.Universidad de Guadalajara, Centro Universitario de los VallesMexico
  2. 2.Instituto Tecnologico y de Estudios Superiores de OccidenteTlaquepaqueMexico
  3. 3.Universidad de las Ciencias InformaticasTorrensCuba
  4. 4.Universidad de Guadalajara, Centro Universitario de los LagosMexico

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