Learning context-free grammar using improved tabular representation
Applied Soft Computing
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This paper juxtaposes performance of the grammarbased classifier system (GCS) with tabular representation algorithm (TBL) on the task of inducing context-free grammars from partially structured examples. In both cases structured examples rapidly improve the efficiency of learning algorithms, although there are substantial differences in the way they work. GCS requires more attention while setting initial system parameters and structured examples provide a bit more information than in TBL but on the other hand it is more efficient when tested against the same examples' sets.