A procedure for multi-class discrimination and some linguistic applications

Authors:
Vladimir Pericliev;Raúl E. Valdés-Pérez
Affiliations:
Institute of Mathematics & Informatics, Sofia, Bulgaria;Carnegie Mellon University, Pittsburgh, PA
Venue:
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Year:
1998

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Abstract

The paper describes a novel computational tool for multiple concept learning. Unlike previous approaches, whose major goal is prediction on unseen instances rather than the legibility of the output, our MPD (Maximally Parsimonious Discrimination) program emphasizes the conciseness and intelligibility of the resultant class descriptions, using three intuitive simplicity criteria to this end. We illustrate MPD with applications in componential analysis (in lexicology and phonology), language typology, and speech pathology.