Feature Selection Using Typical ε: Testors, Working on Dynamical Data

  • Jesús Ariel Carrasco-Ochoa
  • José Ruiz-Shulcloper
  • Lucía Angélica De-la-Vega-Doría
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3287)


Typical e:testors are useful to do feature selection in supervised classification problems with mixed incomplete data, where similarity function is not the total coincidence, but it is a one threshold function. In this kind of problems, modifications on the training matrix can appear very frequently. Any modification of the training matrix can change the set of all typical ε:testors, so this set must be recomputed after each modification. But, complexity of algorithms for calculating all typical ε:testors of a training matrix is too high. In this paper we analyze how the set of all typical ε:testors changes after modifications. An alternative method to calculate all typical ε:testors of the modified training matrix is exposed. The new method’s complexity is analyzed and some experimental results are shown.


  1. 1.
    Martínez-Trinidad, J.F., Guzmán-Arenas, A.: The logical combinatorial approach to pattern recognition an overview through selected works. Pattern Recognition 34(4), 741–751 (2001)zbMATHCrossRefGoogle Scholar
  2. 2.
    Ruiz-Shulcloper, J., Lazo-Cortés, M.: Mathematical Algorithms for the Supervised Classification Based on Fuzzy Partial Precedence. Mathematical and Computer Modeling 29(4), 111–119 (1999)zbMATHCrossRefGoogle Scholar
  3. 3.
    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)zbMATHCrossRefGoogle Scholar
  4. 4.
    Dmitriev, A.N., Zhuravlev, Y.I., Krendeliev, F.P.: About mathematical principles of objects and phenomena classification. Diskretni Analiz 7, 3–15 (1966) (in Russian)Google Scholar
  5. 5.
    Carrasco-Ochoa, J.A., Ruiz-Shulcloper, J.: Sensitivity Problems of the Set of Typical Testors of a Boolean Matrix”. In: Proceedings of the III Iberoamerican Symposium on Pattern Recognition. SIARP 1998, Mexico, pp. 257–266 (1998) (in Spanish)Google Scholar
  6. 6.
    Carrasco-Ochoa, J.A.: Sensitivity in Logical Combinatorial Pattern Recognition. PhD Thesis, CIC-IPN, Mexico (2001)Google Scholar
  7. 7.

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jesús Ariel Carrasco-Ochoa
    • 1
  • José Ruiz-Shulcloper
    • 2
  • Lucía Angélica De-la-Vega-Doría
    • 1
  1. 1.Computer Science DepartmentNational Institute of Astrophysics, Optics and ElectronicsSta María TonanzintlaMexico
  2. 2.Advanced Technologies and Application CenterMINBAS (Cuba) 

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