Title :
FF99: a novel fuzzy first-order logic learning system
Author :
Leung, Kwong-Sak ; King, Irwin ; Tse, Ming-Fun
Author_Institution :
Dept. of Comput. Sci. & Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
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 form of 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
Keywords :
fuzzy logic; fuzzy set theory; knowledge representation; learning (artificial intelligence); learning systems; data mining; first-order logic; fuzzy logic; fuzzy set theory; knowledge representation; learning system; machine learning; Costs; Data mining; Entropy; Fuzzy logic; Fuzzy set theory; Fuzzy systems; Iris; Learning systems; Machine learning; Relational databases;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.815544
