Ellipsoid-based fuzzy association rule mining algorithm

Abstract

Fuzzy ellipsoid theory was introduced to mining fuzzy association rule from quantitative data. The algorithm includes two steps. First, fuzzy clustering procedure is taken to get fuzzy ellipsoids of the feature space. Second, mining procedure is taken to get fuzzy association rule based on the projection regions of fuzzy ellipsoids. The algorithm was compared with a Apriori-based fuzzy association rule mining algorithm. Results show that the algorithm is considerably quicker, especially when mining from large databases. Experiments on real-life data also show that the algorithm is effective to find association rules.