Classification and query evaluation using modelling with words

Authors:
N. J. Randon;J. Lawry
Affiliations:
A.I. Group, Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TR, United Kingdom;A.I. Group, Department of Engineering Mathematics, University of Bristol, Bristol BS8 1TR, United Kingdom
Venue:
Information Sciences: an International Journal
Year:
2006

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Abstract

A random set based knowledge representation framework for learning linguistic models is presented. Within this framework a number of algorithms for learning prototypes are proposed, based on grouping certain sets of attributes and evaluating joint mass assignments on labels. These mass assignments can then be combined with a Semi-Naive Bayes classifier in order to determine classification probabilities. The potential of such linguistic classifiers is then illustrated by their application to a number of toy and benchmark problems. This framework also allows for the evaluation of linguistic queries as will be demonstrated on several well known data sets.