Mining for interesting action rules

In this paper, we give a strategy for constructing all action rules from a given information system and show that action rules constructed by system DEAR, cover only a small part of all action rules. Clearly, we are not interested in all action rules as we are not interested in extracting all possible rules from an information system. Classical strategies like See5, LERS, CART, Rosetta, Weka discover rules whose classification part is either the shortest or close to the shortest. This approach basically rules out all other classification rules unless they are surprising rules. In this paper, we introduce the notion of cost of an action rule and define interesting action rules as rules of the smallest cost. We give a strategy showing how interesting action rules can be generated from action rules discovered by system DEAR.