Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7667
Title: FF99: a novel fuzzy first-order logic learning system
Authors: Prof. LEUNG Kwong Sak 
King Irwin 
Tse Ming-Fun 
Issue Date: 1999
Publisher: IEEE
Source: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, 1999, vol. 5, pp. V-178 - V-184
Journal: Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 
Abstract: This paper describes a novel learning system, named FF99 that learns fuzzy first-order logic concepts from various kinds of data. FF99 builds on the ideas from both fuzzy set theory and first-order logic. Object relationships are described using fuzzy relations based on which FF99 generates classification rules expressed in a restricted from fuzzy first-order logic. This new system has been applied successfully to several tasks taken from the machine learning literature. We demonstrate its usefulness in the applications of data mining through several experiments.
Type: Conference Proceedings
URI: http://hdl.handle.net/20.500.11861/7667
ISSN: 08843627
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