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Iberoamerican Congress on Pattern Recognition

CIARP 2005: Progress in Pattern Recognition, Image Analysis and Applications pp 59–70Cite as

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Inference Improvement by Enlarging the Training Set While Learning DFAs

Inference Improvement by Enlarging the Training Set While Learning DFAs

  • Pedro García18,
  • José Ruiz18,
  • Antonio Cano18 &
  • …
  • Gloria Alvarez19 
  • Conference paper
  • 1066 Accesses

  • 2 Citations

  • 1 Altmetric

Part of the Lecture Notes in Computer Science book series (LNIP,volume 3773)

Abstract

A new version of the RPNI algorithm, called RPNI2, is presented. The main difference between them is the capability of the new one to extend the training set during the inference process. The effect of this new feature is specially notorious in the inference of languages generated from regular expressions and Non-deterministic Finite Automata (NFA). A first experimental comparison is done between RPNI2 and DeLeTe2, other algorithm that behaves well with the same sort of training data.

Keywords

  • Regular Expression
  • Target Language
  • Regular Language
  • Inclusion Relation
  • Grammatical Inference

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Work partially supported by Spanish CICYT under TIC2003-09319-C03-02

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References

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Author information

Authors and Affiliations

  1. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain

    Pedro García, José Ruiz & Antonio Cano

  2. Seccional Cali, Grupo de Investigación DESTINO, Pontificia Universidad Javeriana, Calle 18 118-250, Cali, Colombia

    Gloria Alvarez

Authors
  1. Pedro García
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  2. José Ruiz
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  3. Antonio Cano
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  4. Gloria Alvarez
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Editor information

Editors and Affiliations

  1. Dept. System Engineering and Automation, Universitat Politècnica de Catalunya (UPC) Barcelona, Spain

    Alberto Sanfeliu

  2. Pattern Recognition Group, ICIMAF, Havana, Cuba

    Manuel Lazo Cortés

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© 2005 Springer-Verlag Berlin Heidelberg

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García, P., Ruiz, J., Cano, A., Alvarez, G. (2005). Inference Improvement by Enlarging the Training Set While Learning DFAs. In: Sanfeliu, A., Cortés, M.L. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2005. Lecture Notes in Computer Science, vol 3773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11578079_7

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  • DOI: https://doi.org/10.1007/11578079_7

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  • Online ISBN: 978-3-540-32242-9

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