CT-EXT: An Algorithm for Computing Typical Testor Set

  • Guillermo Sanchez-Díaz
  • Manuel Lazo-Cortés
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)


Typical testors are a useful tool for feature selection and for determining feature relevance in supervised classification problems, especially when quantitative and qualitative features are mixed. Nowadays, computing all typical testors is a highly costly procedure; all described algorithms have exponential complexity. Existing algorithms are not acceptable methods owing to several problems (particularly run time) which are dependent on matrix size. Because of this, different approaches, such as sequential algorithms, parallel processing, genetic algorithms, heuristics and others have been developed. This paper describes a novel external type algorithm that improves the run time of all other reported algorithms. We analyze the behaviour of the algorithm in some experiments, whose results are presented here.


feature selection pattern recognition typical testors 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Guillermo Sanchez-Díaz
    • 1
  • Manuel Lazo-Cortés
    • 2
  1. 1.Center of Technologies Research on Information and Systems, UAEH, Carr. Pachuca-Tulancingo Km. 4.5, C.P. 42084, Pachuca, Hgo.Mexico
  2. 2.Institute of Cybernetics, Mathematics and Physics, 15 No. 551 Vedado, C.P. 10400, HavanaCuba

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