Abstract
A k-piecewise testable language (k-PWT) is defined by the subwords (sequences of symbols which are not necessarely consecutive) no longer than k that are contained in its words. We propose an algorithm that identifies in the limit the class of k-PWT languages from positive data. The proposed algorithm has polynomial time complexity on the length of the received data. As the class of k-PTW languages is finite, the algorithm can be used for PAC- learning.
Work partially supported by the Spanish CICYT under grant TIC93-0633-CO2
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Ruiz, J., García, P. (1996). Learning k-piecewise testable languages from positive data. In: Miclet, L., de la Higuera, C. (eds) Grammatical Interference: Learning Syntax from Sentences. ICGI 1996. Lecture Notes in Computer Science, vol 1147. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033355
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DOI: https://doi.org/10.1007/BFb0033355
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