Fuzzy Rule Extraction of Specified Output Field

Abstract

This paper presents fast algorithms for extracting fuzzy association rules from 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 conclusion part of the fuzzy rule is specified in advance. This assumption corresponds to actual problems, e.g. diagnostics problem of the process, quality control action of manufacturing, and so on. The algorithm is based on the Apriori 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 efficiency.