Mining fuzzy association rules of specified output field

This paper describes fast algorithms for extracting fuzzy association rules from a database. The objective of the algorithm is to improve the computational time of mining and to reduce the extracted redundant rules for the actual application. In this paper, for extracting fuzzy association rules, it is assumed that the conclusion part of the fuzzy rule is specified in advance, i.e. before starting mining computation. This assumption corresponds to actual problems, e.g. the diagnostics problem of the process, quality control action of manufacturing, and so on. The algorithm is based on the a priori algorithm for rule extraction of the specified output field or output fuzzy set. From the results of numerical experiments, the algorithm is found to be effective compared with the conventional method in terms of computational time.