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Grammatical Inference Algorithms in MATLAB

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6339))

Abstract

Although MATLAB has become one of the mainstream languages for the machine learning community, there is still skepticism among the Grammatical Inference (GI) community regarding the suitability of MATLAB for implementing and running GI algorithms. In this paper we will present implementation results of several GI algorithms, e.g., RPNI (Regular Positive and Negative Inference), EDSM (Evidence Driven State Merging), and k-testable machine. We show experimentally based on our MATLAB implementation that state merging algorithms can successfully be implemented and manipulated using MATLAB in the similar fashion as other machine learning tools. Moreover, we also show that MATLAB provides a range of toolboxes that can be leveraged to gain parallelism, speedup etc.

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References

  1. García, P., Vidal, E.: Inference of k-testable languages in the strict sense and application to syntactic pattern recognition. IEEE Trans. Pattern Anal. Mach. Intell. 12(9), 920–925 (1990)

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  4. de la Higuera, C.: Grammatical Inference: Learning Automata and Grammars. Cambridge University Press, Cambridge (2010)

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© 2010 Springer-Verlag Berlin Heidelberg

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Akram, H.I., de la Higuera, C., Xiao, H., Eckert, C. (2010). Grammatical Inference Algorithms in MATLAB. In: Sempere, J.M., García, P. (eds) Grammatical Inference: Theoretical Results and Applications. ICGI 2010. Lecture Notes in Computer Science(), vol 6339. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15488-1_22

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  • DOI: https://doi.org/10.1007/978-3-642-15488-1_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15487-4

  • Online ISBN: 978-3-642-15488-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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