The paper describes a novel computational tool for multiple concept learning. Unlike previous approaches like ID3 or C4.5, whose major goal is prediction on unseen instances rathe r than the legibility of the output, our MPD (Maximally Parsimonious Discrimination) program e mphasizes the conciseness and intelligibility of the resultant class descriptions, using three intuitive simplicity criteria to this end. We illustrate MPD with some additional application s than those commonly associated with the mentioned algorithms, such as learning verbal case f rames, translational correspondences or morphological rules. These include componential analys is (in lexicology and phonology), language typology, and speech pathology.

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