Title :
A new algorithm for mining fuzzy association rules
Author :
Gao, Ya ; Ma, Jun ; Ma, Lin
Author_Institution :
Sch. of Comput. & Commun. Eng., Southwest Jiaotong Univ., Sichuan, China
Abstract :
We introduce a new algorithm for mining the fuzzy association rules by removing redundant fuzzy association (RFA) rules. Firstly, we analyze some properties of fuzzy association rules and give the definition of RFA rules. Secondly, using the degree of implication on fuzzy implication operator, we introduce a new algorithm to mine fuzzy association rules from frequent itemsets. Finally, an example is given to illustrate our idea.
Keywords :
data mining; fuzzy set theory; mathematical operators; fuzzy association rule mining; fuzzy implication operator; redundant fuzzy association; Association rules; Data mining; Electronic mail; Fuzzy sets; Itemsets; Large-scale systems; Measurement standards; Partitioning algorithms; Pharmaceuticals; Transaction databases;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1382037
