Rough Sets and Association Rule Generation

ASSOCIATION RULE see extraction methods have been developed as the main methods for mining of real life data in particular in Basket Data Analysis In this paper we present a novel ap proach to generation of association rule based on Rough Set and Boolean reasoning methods We show the relationship between the problems of association rule extraction for transaction data and relative reducts or reducts generation for a decision table Moreover the present ap proach can be used to extract association rules in general form The experimental results show that the presented methods are quite e cient Large number of association rules with given support and con dence can be extracted in a short time