Inference improvement by enlarging the training set while learning DFAs

Pedro García; José Ruiz; Antonio Cano; Gloria Alvarez

doi:10.1007/11578079_7

Inference improvement by enlarging the training set while learning DFAs

Pedro García, José Ruiz, Antonio Cano, Gloria Alvarez

Polytechnic University of Valencia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

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.¹

Original language	English
Title of host publication	Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings
Publisher	Springer Verlag
Pages	59-70
Number of pages	12
ISBN (Print)	3540298509, 9783540298502
DOIs	https://doi.org/10.1007/11578079_7
State	Published - 2005
Event	10th Iberoamerican Congress on Pattern Recognition, CIARP 2005 - Havana, Cuba Duration: 15 Nov 2005 → 18 Nov 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3773 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th Iberoamerican Congress on Pattern Recognition, CIARP 2005
Country/Territory	Cuba
City	Havana
Period	15/11/05 → 18/11/05

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10.1007/11578079_7

Cite this

García, P., Ruiz, J., Cano, A., & Alvarez, G. (2005). Inference improvement by enlarging the training set while learning DFAs. In Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings (pp. 59-70). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3773 LNCS). Springer Verlag. https://doi.org/10.1007/11578079_7

García, Pedro ; Ruiz, José ; Cano, Antonio et al. / Inference improvement by enlarging the training set while learning DFAs. Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings. Springer Verlag, 2005. pp. 59-70 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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García, P, Ruiz, J, Cano, A & Alvarez, G 2005, Inference improvement by enlarging the training set while learning DFAs. in Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3773 LNCS, Springer Verlag, pp. 59-70, 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Havana, Cuba, 15/11/05. https://doi.org/10.1007/11578079_7

Inference improvement by enlarging the training set while learning DFAs. / García, Pedro; Ruiz, José; Cano, Antonio et al.
Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings. Springer Verlag, 2005. p. 59-70 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3773 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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García P, Ruiz J, Cano A, Alvarez G. Inference improvement by enlarging the training set while learning DFAs. In Progress in Pattern Recognition, Image Analysis and Applications - 10th Iberoamerican Congress on Pattern Recognition, CIARP 2005, Proceedings. Springer Verlag. 2005. p. 59-70. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11578079_7

Inference improvement by enlarging the training set while learning DFAs

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